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//paip/script/lpr/detectron2_LPR/detectron2_LPR_detect.ipynb
{"cells":[{"cell_type":"markdown","metadata":{"id":"5f3aKHN-Vh25"},"source":["### Install detectron2"]},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5234,"status":"ok","timestamp":1653380770379,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"78DqvEppVcGA","outputId":"9ac1d401-4c39-4057-d82d-b40ad32af796"},"outputs":[{"output_type":"stream","name":"stdout","text":["Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Collecting pyyaml==5.1\n"," Downloading PyYAML-5.1.tar.gz (274 kB)\n","\u001b[K |████████████████████████████████| 274 kB 7.0 MB/s \n","\u001b[?25hBuilding wheels for collected packages: pyyaml\n"," Building wheel for pyyaml (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Created wheel for pyyaml: filename=PyYAML-5.1-cp37-cp37m-linux_x86_64.whl size=44092 sha256=ae1b628cca854b1c6b054fc6b4ca85d71e8cb724e324e88eed19aaf1daa4a096\n"," Stored in directory: /root/.cache/pip/wheels/77/f5/10/d00a2bd30928b972790053b5de0c703ca87324f3fead0f2fd9\n","Successfully built pyyaml\n","Installing collected packages: pyyaml\n"," Attempting uninstall: pyyaml\n"," Found existing installation: PyYAML 3.13\n"," Uninstalling PyYAML-3.13:\n"," Successfully uninstalled PyYAML-3.13\n","Successfully installed pyyaml-5.1\n"]}],"source":["!pip3 install pyyaml==5.1"]},{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":37931,"status":"ok","timestamp":1653381056668,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"_Nrhmnje07cu","outputId":"4644aff9-8184-4017-c3a8-8d4a08415f91"},"outputs":[{"output_type":"stream","name":"stdout","text":["Reading package lists... Done\n","Building dependency tree \n","Reading state information... Done\n","Note, selecting 'cuda-cusparse-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-3-config-common' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-npp-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-config-common' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nvprune-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nvgraph-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvgraph-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvgraph-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cublas-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-418' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-440' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-450' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-455' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-460' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-465' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-470' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-495' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-510' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-515' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-grid' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute--10-0' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-curand-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-curand-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-curand-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-curand-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-visual-tools-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cublas-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-branch' for glob 'cuda*'\n","Note, selecting 'cuda-repo-ubuntu1204' for glob 'cuda*'\n","Note, selecting 'cuda-nvjpeg-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvjpeg-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvjpeg-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-dev-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-dev-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-cccl-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-cccl-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-cccl-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-cccl-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-drivers' for glob 'cuda*'\n","Note, selecting 'cuda-repo-ubuntu1404' for glob 'cuda*'\n","Note, selecting 'cuda-repo-ubuntu1410' for glob 'cuda*'\n","Note, selecting 'cuda-thrust-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-thrust-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-thrust-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-thrust-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-thrust-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-minimal-build-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-cufft-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-repo-ubuntu1504' for glob 'cuda*'\n","Note, selecting 'cuda-license-7-5' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-7-config-common' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cusolver-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cusolver-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cusolver-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-dev-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-dev-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-dev-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-dev-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-dev-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-dev-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-dev-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-cupti-dev-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-libraries-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-repo-ubuntu1804' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-diagnostic' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-runtime-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-cusparse-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cusparse-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cusparse-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvjpeg-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvjpeg-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvjpeg-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cufft-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cufft-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cufft-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nvrtc-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-cusparse-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cusparse-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cusparse-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-systems-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-npp-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-npp-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-npp-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-tools-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-tools-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-tools-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-6-config-common' for glob 'cuda*'\n","Note, selecting 'cuda-keyring' for glob 'cuda*'\n","Note, selecting 'cuda-tools-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-tools-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-tools-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-tools-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-tools-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-tools-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-tools-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-tools-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nvtx-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-license-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-license-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-license-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-samples-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-samples-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-samples-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cusolver-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nvdisasm-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-samples-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-samples-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-samples-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-samples-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-samples-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-samples-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-samples-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-cross-qnx' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-documentation-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-compat-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-compat-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-compat-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-compat-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-compat-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-compat-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-compat-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-compat-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-compat-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-compat-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-compat-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-repo-ubuntu1404-7-5-local' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nvcc-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nvvp-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-5-config-common' for glob 'cuda*'\n","Note, selecting 'cuda-nvgraph-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvgraph-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvgraph-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cuxxfilt-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-cuxxfilt-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-cuxxfilt-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-cuxxfilt-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-cuxxfilt-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-cuxxfilt-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-cub-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-cub-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-cub-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-cub-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-dev-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nvml-dev-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-gpu-library-advisor-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-gpu-library-advisor-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cublas-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-core-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-core-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-core-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cusolver-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cusolver-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cusolver-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-driver-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-api-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-sanitizer-api-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-npp-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-npp-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-npp-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-compiler-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-demo-suite-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-curand-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-curand-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-curand-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cufft-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cufft-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cufft-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager-450' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager-455' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager-460' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager-465' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager-470' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager-495' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-repo-ubuntu1504-7-5-local' for glob 'cuda*'\n","Note, selecting 'cuda-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager-510' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager-515' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-command-line-tools-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager-branch' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-driver-dev-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-misc-headers-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-drivers-fabricmanager' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-11-4-config-common' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-10-2' for glob 'cuda*'\n","Note, selecting 'cuda' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-memcheck-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-cudart-cross-qnx-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-toolkit-config-common' for glob 'cuda*'\n","Note, selecting 'cuda-misc-headers-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-misc-headers-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-misc-headers-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-gdb-src-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-11-0' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-11-1' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-11-2' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-11-3' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-11-4' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-11-5' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-11-6' for glob 'cuda*'\n","Note, selecting 'cuda-cuobjdump-11-7' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nsight-compute-10-2' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-10-0' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-10-1' for glob 'cuda*'\n","Note, selecting 'cuda-nvprof-10-2' for glob 'cuda*'\n","Package 'cuda-license-7-5' is not installed, so not removed\n","Package 'cuda-repo-ubuntu1204' is not installed, so not removed\n","Package 'cuda-repo-ubuntu1404' is not installed, so not removed\n","Package 'cuda-repo-ubuntu1404-7-5-local' is not installed, so not removed\n","Package 'cuda-repo-ubuntu1410' is not installed, so not removed\n","Package 'cuda-repo-ubuntu1504' is not installed, so not removed\n","Package 'cuda-repo-ubuntu1504-7-5-local' is not installed, so not removed\n","Note, selecting 'cuda-cccl-11-4' instead of 'cuda-cub-11-4'\n","Note, selecting 'cuda-cccl-11-4' instead of 'cuda-thrust-11-4'\n","Note, selecting 'cuda-cccl-11-5' instead of 'cuda-cub-11-5'\n","Note, selecting 'cuda-cccl-11-5' instead of 'cuda-thrust-11-5'\n","Note, selecting 'cuda-cccl-11-6' instead of 'cuda-cub-11-6'\n","Note, selecting 'cuda-cccl-11-6' instead of 'cuda-thrust-11-6'\n","Package 'cuda-cudart-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-driver-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-misc-headers-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-cusolver-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-cublas-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-cufft-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-curand-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-cusparse-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-npp-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-drivers-grid' is not installed, so not removed\n","Note, selecting 'cuda-cccl-11-7' instead of 'cuda-cub-11-7'\n","Note, selecting 'cuda-cccl-11-7' instead of 'cuda-thrust-11-7'\n","Package 'cuda-drivers-fabricmanager-460' is not installed, so not removed\n","Package 'cuda-11-2' is not installed, so not removed\n","Package 'cuda-11-3' is not installed, so not removed\n","Package 'cuda-11-4' is not installed, so not removed\n","Package 'cuda-11-5' is not installed, so not removed\n","Package 'cuda-11-6' is not installed, so not removed\n","Package 'cuda-command-line-tools-11-2' is not installed, so not removed\n","Package 'cuda-command-line-tools-11-3' is not installed, so not removed\n","Package 'cuda-command-line-tools-11-4' is not installed, so not removed\n","Package 'cuda-command-line-tools-11-5' is not installed, so not removed\n","Package 'cuda-command-line-tools-11-6' is not installed, so not removed\n","Package 'cuda-compat-10-0' is not installed, so not removed\n","Package 'cuda-compat-10-1' is not installed, so not removed\n","Package 'cuda-compat-10-2' is not installed, so not removed\n","Package 'cuda-compat-11-2' is not installed, so not removed\n","Package 'cuda-compat-11-3' is not installed, so not removed\n","Package 'cuda-compat-11-5' is not installed, so not removed\n","Package 'cuda-compat-11-6' is not installed, so not removed\n","Package 'cuda-compiler-11-2' is not installed, so not removed\n","Package 'cuda-compiler-11-3' is not installed, so not removed\n","Package 'cuda-compiler-11-4' is not installed, so not removed\n","Package 'cuda-compiler-11-5' is not installed, so not removed\n","Package 'cuda-compiler-11-6' is not installed, so not removed\n","Package 'cuda-drivers-418' is not installed, so not removed\n","Package 'cuda-drivers-440' is not installed, so not removed\n","Package 'cuda-drivers-455' is not installed, so not removed\n","Package 'cuda-drivers-460' is not installed, so not removed\n","Package 'cuda-drivers-465' is not installed, so not removed\n","Package 'cuda-drivers-495' is not installed, so not removed\n","Package 'cuda-drivers-510' is not installed, so not removed\n","Package 'cuda-drivers-diagnostic' is not installed, so not removed\n","Package 'cuda-libraries-11-2' is not installed, so not removed\n","Package 'cuda-libraries-11-3' is not installed, so not removed\n","Package 'cuda-libraries-11-4' is not installed, so not removed\n","Package 'cuda-libraries-11-5' is not installed, so not removed\n","Package 'cuda-libraries-11-6' is not installed, so not removed\n","Package 'cuda-libraries-dev-11-2' is not installed, so not removed\n","Package 'cuda-libraries-dev-11-3' is not installed, so not removed\n","Package 'cuda-libraries-dev-11-4' is not installed, so not removed\n","Package 'cuda-libraries-dev-11-5' is not installed, so not removed\n","Package 'cuda-libraries-dev-11-6' is not installed, so not removed\n","Package 'cuda-minimal-build-11-2' is not installed, so not removed\n","Package 'cuda-minimal-build-11-3' is not installed, so not removed\n","Package 'cuda-minimal-build-11-4' is not installed, so not removed\n","Package 'cuda-minimal-build-11-5' is not installed, so not removed\n","Package 'cuda-minimal-build-11-6' is not installed, so not removed\n","Package 'cuda-nsight-compute-11-2' is not installed, so not removed\n","Package 'cuda-nsight-compute-11-3' is not installed, so not removed\n","Package 'cuda-nsight-compute-11-4' is not installed, so not removed\n","Package 'cuda-nsight-compute-11-5' is not installed, so not removed\n","Package 'cuda-nsight-compute-11-6' is not installed, so not removed\n","Package 'cuda-nsight-systems-11-2' is not installed, so not removed\n","Package 'cuda-nsight-systems-11-3' is not installed, so not removed\n","Package 'cuda-nsight-systems-11-4' is not installed, so not removed\n","Package 'cuda-nsight-systems-11-5' is not installed, so not removed\n","Package 'cuda-nsight-systems-11-6' is not installed, so not removed\n","Package 'cuda-repo-ubuntu1804' is not installed, so not removed\n","Package 'cuda-runtime-11-2' is not installed, so not removed\n","Package 'cuda-runtime-11-3' is not installed, so not removed\n","Package 'cuda-runtime-11-4' is not installed, so not removed\n","Package 'cuda-runtime-11-5' is not installed, so not removed\n","Package 'cuda-runtime-11-6' is not installed, so not removed\n","Package 'cuda-toolkit-11-2' is not installed, so not removed\n","Package 'cuda-toolkit-11-3' is not installed, so not removed\n","Package 'cuda-toolkit-11-4' is not installed, so not removed\n","Package 'cuda-toolkit-11-5' is not installed, so not removed\n","Package 'cuda-toolkit-11-6' is not installed, so not removed\n","Package 'cuda-tools-11-2' is not installed, so not removed\n","Package 'cuda-tools-11-3' is not installed, so not removed\n","Package 'cuda-tools-11-4' is not installed, so not removed\n","Package 'cuda-tools-11-5' is not installed, so not removed\n","Package 'cuda-tools-11-6' is not installed, so not removed\n","Package 'cuda-visual-tools-11-2' is not installed, so not removed\n","Package 'cuda-visual-tools-11-3' is not installed, so not removed\n","Package 'cuda-visual-tools-11-4' is not installed, so not removed\n","Package 'cuda-visual-tools-11-5' is not installed, so not removed\n","Package 'cuda-visual-tools-11-6' is not installed, so not removed\n","Package 'cuda-10-2' is not installed, so not removed\n","Package 'cuda-cccl-11-4' is not installed, so not removed\n","Package 'cuda-cccl-11-5' is not installed, so not removed\n","Package 'cuda-cccl-11-6' is not installed, so not removed\n","Package 'cuda-command-line-tools-10-2' is not installed, so not removed\n","Package 'cuda-compiler-10-2' is not installed, so not removed\n","Package 'cuda-core-10-0' is not installed, so not removed\n","Package 'cuda-core-10-1' is not installed, so not removed\n","Package 'cuda-core-10-2' is not installed, so not removed\n","Package 'cuda-cross-qnx-10-0' is not installed, so not removed\n","Package 'cuda-cross-qnx' is not installed, so not removed\n","Package 'cuda-cudart-10-2' is not installed, so not removed\n","Package 'cuda-cudart-11-2' is not installed, so not removed\n","Package 'cuda-cudart-11-3' is not installed, so not removed\n","Package 'cuda-cudart-11-4' is not installed, so not removed\n","Package 'cuda-cudart-11-5' is not installed, so not removed\n","Package 'cuda-cudart-11-6' is not installed, so not removed\n","Package 'cuda-cudart-dev-10-2' is not installed, so not removed\n","Package 'cuda-cudart-dev-11-2' is not installed, so not removed\n","Package 'cuda-cudart-dev-11-3' is not installed, so not removed\n","Package 'cuda-cudart-dev-11-4' is not installed, so not removed\n","Package 'cuda-cudart-dev-11-5' is not installed, so not removed\n","Package 'cuda-cudart-dev-11-6' is not installed, so not removed\n","Package 'cuda-cufft-10-2' is not installed, so not removed\n","Package 'cuda-cufft-dev-10-2' is not installed, so not removed\n","Package 'cuda-cuobjdump-10-2' is not installed, so not removed\n","Package 'cuda-cuobjdump-11-2' is not installed, so not removed\n","Package 'cuda-cuobjdump-11-3' is not installed, so not removed\n","Package 'cuda-cuobjdump-11-4' is not installed, so not removed\n","Package 'cuda-cuobjdump-11-5' is not installed, so not removed\n","Package 'cuda-cuobjdump-11-6' is not installed, so not removed\n","Package 'cuda-cupti-10-2' is not installed, so not removed\n","Package 'cuda-cupti-11-2' is not installed, so not removed\n","Package 'cuda-cupti-11-3' is not installed, so not removed\n","Package 'cuda-cupti-11-4' is not installed, so not removed\n","Package 'cuda-cupti-11-5' is not installed, so not removed\n","Package 'cuda-cupti-11-6' is not installed, so not removed\n","Package 'cuda-cupti-dev-10-2' is not installed, so not removed\n","Package 'cuda-cupti-dev-11-2' is not installed, so not removed\n","Package 'cuda-cupti-dev-11-3' is not installed, so not removed\n","Package 'cuda-cupti-dev-11-4' is not installed, so not removed\n","Package 'cuda-cupti-dev-11-5' is not installed, so not removed\n","Package 'cuda-cupti-dev-11-6' is not installed, so not removed\n","Package 'cuda-curand-10-2' is not installed, so not removed\n","Package 'cuda-curand-dev-10-2' is not installed, so not removed\n","Package 'cuda-cusolver-10-2' is not installed, so not removed\n","Package 'cuda-cusolver-dev-10-2' is not installed, so not removed\n","Package 'cuda-cusparse-10-2' is not installed, so not removed\n","Package 'cuda-cusparse-dev-10-2' is not installed, so not removed\n","Package 'cuda-cuxxfilt-11-2' is not installed, so not removed\n","Package 'cuda-cuxxfilt-11-3' is not installed, so not removed\n","Package 'cuda-cuxxfilt-11-4' is not installed, so not removed\n","Package 'cuda-cuxxfilt-11-5' is not installed, so not removed\n","Package 'cuda-cuxxfilt-11-6' is not installed, so not removed\n","Package 'cuda-demo-suite-10-2' is not installed, so not removed\n","Package 'cuda-demo-suite-11-2' is not installed, so not removed\n","Package 'cuda-demo-suite-11-3' is not installed, so not removed\n","Package 'cuda-demo-suite-11-4' is not installed, so not removed\n","Package 'cuda-demo-suite-11-5' is not installed, so not removed\n","Package 'cuda-demo-suite-11-6' is not installed, so not removed\n","Package 'cuda-documentation-10-2' is not installed, so not removed\n","Package 'cuda-documentation-11-2' is not installed, so not removed\n","Package 'cuda-documentation-11-3' is not installed, so not removed\n","Package 'cuda-documentation-11-4' is not installed, so not removed\n","Package 'cuda-documentation-11-5' is not installed, so not removed\n","Package 'cuda-documentation-11-6' is not installed, so not removed\n","Package 'cuda-driver-dev-10-2' is not installed, so not removed\n","Package 'cuda-driver-dev-11-2' is not installed, so not removed\n","Package 'cuda-driver-dev-11-3' is not installed, so not removed\n","Package 'cuda-driver-dev-11-4' is not installed, so not removed\n","Package 'cuda-driver-dev-11-5' is not installed, so not removed\n","Package 'cuda-driver-dev-11-6' is not installed, so not removed\n","Package 'cuda-drivers-fabricmanager-455' is not installed, so not removed\n","Package 'cuda-drivers-fabricmanager-465' is not installed, so not removed\n","Package 'cuda-drivers-fabricmanager-495' is not installed, so not removed\n","Package 'cuda-drivers-fabricmanager-510' is not installed, so not removed\n","Package 'cuda-gdb-10-2' is not installed, so not removed\n","Package 'cuda-gdb-11-2' is not installed, so not removed\n","Package 'cuda-gdb-11-3' is not installed, so not removed\n","Package 'cuda-gdb-11-4' is not installed, so not removed\n","Package 'cuda-gdb-11-5' is not installed, so not removed\n","Package 'cuda-gdb-11-6' is not installed, so not removed\n","Package 'cuda-gdb-src-10-0' is not installed, so not removed\n","Package 'cuda-gdb-src-10-1' is not installed, so not removed\n","Package 'cuda-gdb-src-10-2' is not installed, so not removed\n","Package 'cuda-gdb-src-11-0' is not installed, so not removed\n","Package 'cuda-gdb-src-11-1' is not installed, so not removed\n","Package 'cuda-gdb-src-11-2' is not installed, so not removed\n","Package 'cuda-gdb-src-11-3' is not installed, so not removed\n","Package 'cuda-gdb-src-11-4' is not installed, so not removed\n","Package 'cuda-gdb-src-11-5' is not installed, so not removed\n","Package 'cuda-gdb-src-11-6' is not installed, so not removed\n","Package 'cuda-libraries-10-2' is not installed, so not removed\n","Package 'cuda-libraries-dev-10-2' is not installed, so not removed\n","Package 'cuda-license-10-2' is not installed, so not removed\n","Package 'cuda-memcheck-10-2' is not installed, so not removed\n","Package 'cuda-memcheck-11-2' is not installed, so not removed\n","Package 'cuda-memcheck-11-3' is not installed, so not removed\n","Package 'cuda-memcheck-11-4' is not installed, so not removed\n","Package 'cuda-memcheck-11-5' is not installed, so not removed\n","Package 'cuda-memcheck-11-6' is not installed, so not removed\n","Package 'cuda-minimal-build-10-0' is not installed, so not removed\n","Package 'cuda-minimal-build-10-1' is not installed, so not removed\n","Package 'cuda-minimal-build-10-2' is not installed, so not removed\n","Package 'cuda-minimal-build-11-0' is not installed, so not removed\n","Package 'cuda-misc-headers-10-2' is not installed, so not removed\n","Package 'cuda-npp-10-2' is not installed, so not removed\n","Package 'cuda-npp-dev-10-2' is not installed, so not removed\n","Package 'cuda-nsight-10-2' is not installed, so not removed\n","Package 'cuda-nsight-11-2' is not installed, so not removed\n","Package 'cuda-nsight-11-3' is not installed, so not removed\n","Package 'cuda-nsight-11-4' is not installed, so not removed\n","Package 'cuda-nsight-11-5' is not installed, so not removed\n","Package 'cuda-nsight-11-6' is not installed, so not removed\n","Package 'cuda-nsight-compute--10-0' is not installed, so not removed\n","Package 'cuda-nsight-compute-10-2' is not installed, so not removed\n","Package 'cuda-nsight-systems-10-2' is not installed, so not removed\n","Package 'cuda-nvcc-10-2' is not installed, so not removed\n","Package 'cuda-nvcc-11-2' is not installed, so not removed\n","Package 'cuda-nvcc-11-3' is not installed, so not removed\n","Package 'cuda-nvcc-11-4' is not installed, so not removed\n","Package 'cuda-nvcc-11-5' is not installed, so not removed\n","Package 'cuda-nvcc-11-6' is not installed, so not removed\n","Package 'cuda-nvdisasm-10-2' is not installed, so not removed\n","Package 'cuda-nvdisasm-11-2' is not installed, so not removed\n","Package 'cuda-nvdisasm-11-3' is not installed, so not removed\n","Package 'cuda-nvdisasm-11-4' is not installed, so not removed\n","Package 'cuda-nvdisasm-11-5' is not installed, so not removed\n","Package 'cuda-nvdisasm-11-6' is not installed, so not removed\n","Package 'cuda-nvgraph-10-2' is not installed, so not removed\n","Package 'cuda-nvgraph-dev-10-2' is not installed, so not removed\n","Package 'cuda-nvjpeg-10-2' is not installed, so not removed\n","Package 'cuda-nvjpeg-dev-10-2' is not installed, so not removed\n","Package 'cuda-nvml-dev-10-2' is not installed, so not removed\n","Package 'cuda-nvml-dev-11-2' is not installed, so not removed\n","Package 'cuda-nvml-dev-11-3' is not installed, so not removed\n","Package 'cuda-nvml-dev-11-4' is not installed, so not removed\n","Package 'cuda-nvml-dev-11-5' is not installed, so not removed\n","Package 'cuda-nvml-dev-11-6' is not installed, so not removed\n","Package 'cuda-nvprof-10-2' is not installed, so not removed\n","Package 'cuda-nvprof-11-2' is not installed, so not removed\n","Package 'cuda-nvprof-11-3' is not installed, so not removed\n","Package 'cuda-nvprof-11-4' is not installed, so not removed\n","Package 'cuda-nvprof-11-5' is not installed, so not removed\n","Package 'cuda-nvprof-11-6' is not installed, so not removed\n","Package 'cuda-nvprune-10-2' is not installed, so not removed\n","Package 'cuda-nvprune-11-2' is not installed, so not removed\n","Package 'cuda-nvprune-11-3' is not installed, so not removed\n","Package 'cuda-nvprune-11-4' is not installed, so not removed\n","Package 'cuda-nvprune-11-5' is not installed, so not removed\n","Package 'cuda-nvprune-11-6' is not installed, so not removed\n","Package 'cuda-nvrtc-10-2' is not installed, so not removed\n","Package 'cuda-nvrtc-11-2' is not installed, so not removed\n","Package 'cuda-nvrtc-11-3' is not installed, so not removed\n","Package 'cuda-nvrtc-11-4' is not installed, so not removed\n","Package 'cuda-nvrtc-11-5' is not installed, so not removed\n","Package 'cuda-nvrtc-11-6' is not installed, so not removed\n","Package 'cuda-nvrtc-dev-10-2' is not installed, so not removed\n","Package 'cuda-nvrtc-dev-11-2' is not installed, so not removed\n","Package 'cuda-nvrtc-dev-11-3' is not installed, so not removed\n","Package 'cuda-nvrtc-dev-11-4' is not installed, so not removed\n","Package 'cuda-nvrtc-dev-11-5' is not installed, so not removed\n","Package 'cuda-nvrtc-dev-11-6' is not installed, so not removed\n","Package 'cuda-nvtx-10-2' is not installed, so not removed\n","Package 'cuda-nvtx-11-2' is not installed, so not removed\n","Package 'cuda-nvtx-11-3' is not installed, so not removed\n","Package 'cuda-nvtx-11-4' is not installed, so not removed\n","Package 'cuda-nvtx-11-5' is not installed, so not removed\n","Package 'cuda-nvtx-11-6' is not installed, so not removed\n","Package 'cuda-nvvp-10-2' is not installed, so not removed\n","Package 'cuda-nvvp-11-2' is not installed, so not removed\n","Package 'cuda-nvvp-11-3' is not installed, so not removed\n","Package 'cuda-nvvp-11-4' is not installed, so not removed\n","Package 'cuda-nvvp-11-5' is not installed, so not removed\n","Package 'cuda-nvvp-11-6' is not installed, so not removed\n","Package 'cuda-runtime-10-2' is not installed, so not removed\n","Package 'cuda-samples-10-2' is not installed, so not removed\n","Package 'cuda-samples-11-2' is not installed, so not removed\n","Package 'cuda-samples-11-3' is not installed, so not removed\n","Package 'cuda-samples-11-4' is not installed, so not removed\n","Package 'cuda-samples-11-5' is not installed, so not removed\n","Package 'cuda-samples-11-6' is not installed, so not removed\n","Package 'cuda-sanitizer-11-2' is not installed, so not removed\n","Package 'cuda-sanitizer-11-3' is not installed, so not removed\n","Package 'cuda-sanitizer-11-4' is not installed, so not removed\n","Package 'cuda-sanitizer-11-5' is not installed, so not removed\n","Package 'cuda-sanitizer-11-6' is not installed, so not removed\n","Package 'cuda-sanitizer-api-10-2' is not installed, so not removed\n","Package 'cuda-thrust-11-3' is not installed, so not removed\n","Package 'cuda-toolkit-10-2' is not installed, so not removed\n","Package 'cuda-tools-10-2' is not installed, so not removed\n","Package 'cuda-visual-tools-10-2' is not installed, so not removed\n","Package 'cuda-toolkit-11-3-config-common' is not installed, so not removed\n","Package 'cuda-toolkit-11-4-config-common' is not installed, so not removed\n","Package 'cuda-toolkit-11-5-config-common' is not installed, so not removed\n","Package 'cuda-toolkit-11-6-config-common' is not installed, so not removed\n","Package 'cuda' is not installed, so not removed\n","Package 'cuda-11-7' is not installed, so not removed\n","Package 'cuda-cccl-11-7' is not installed, so not removed\n","Package 'cuda-command-line-tools-11-7' is not installed, so not removed\n","Package 'cuda-compat-11-7' is not installed, so not removed\n","Package 'cuda-compiler-11-7' is not installed, so not removed\n","Package 'cuda-cudart-11-7' is not installed, so not removed\n","Package 'cuda-cudart-dev-11-7' is not installed, so not removed\n","Package 'cuda-cuobjdump-11-7' is not installed, so not removed\n","Package 'cuda-cupti-11-7' is not installed, so not removed\n","Package 'cuda-cupti-dev-11-7' is not installed, so not removed\n","Package 'cuda-cuxxfilt-11-7' is not installed, so not removed\n","Package 'cuda-demo-suite-11-7' is not installed, so not removed\n","Package 'cuda-documentation-11-7' is not installed, so not removed\n","Package 'cuda-driver-dev-11-7' is not installed, so not removed\n","Package 'cuda-drivers-fabricmanager' is not installed, so not removed\n","Package 'cuda-drivers-fabricmanager-515' is not installed, so not removed\n","Package 'cuda-gdb-11-7' is not installed, so not removed\n","Package 'cuda-gdb-src-11-7' is not installed, so not removed\n","Package 'cuda-libraries-11-7' is not installed, so not removed\n","Package 'cuda-libraries-dev-11-7' is not installed, so not removed\n","Package 'cuda-memcheck-11-7' is not installed, so not removed\n","Package 'cuda-minimal-build-11-7' is not installed, so not removed\n","Package 'cuda-nsight-11-7' is not installed, so not removed\n","Package 'cuda-nsight-compute-11-7' is not installed, so not removed\n","Package 'cuda-nsight-systems-11-7' is not installed, so not removed\n","Package 'cuda-nvcc-11-7' is not installed, so not removed\n","Package 'cuda-nvdisasm-11-7' is not installed, so not removed\n","Package 'cuda-nvml-dev-11-7' is not installed, so not removed\n","Package 'cuda-nvprof-11-7' is not installed, so not removed\n","Package 'cuda-nvprune-11-7' is not installed, so not removed\n","Package 'cuda-nvrtc-11-7' is not installed, so not removed\n","Package 'cuda-nvrtc-dev-11-7' is not installed, so not removed\n","Package 'cuda-nvtx-11-7' is not installed, so not removed\n","Package 'cuda-nvvp-11-7' is not installed, so not removed\n","Package 'cuda-runtime-11-7' is not installed, so not removed\n","Package 'cuda-sanitizer-11-7' is not installed, so not removed\n","Package 'cuda-toolkit-11-7' is not installed, so not removed\n","Package 'cuda-toolkit-11-7-config-common' is not installed, so not removed\n","Package 'cuda-toolkit-11-config-common' is not installed, so not removed\n","Package 'cuda-toolkit-config-common' is not installed, so not removed\n","Package 'cuda-tools-11-7' is not installed, so not removed\n","Package 'cuda-visual-tools-11-7' is not installed, so not removed\n","Package 'cuda-compat-11-0' is not installed, so not removed\n","Package 'cuda-compat-11-4' is not installed, so not removed\n","Package 'cuda-drivers-450' is not installed, so not removed\n","Package 'cuda-drivers-470' is not installed, so not removed\n","Package 'cuda-drivers-fabricmanager-450' is not installed, so not removed\n","Package 'cuda-drivers-fabricmanager-470' is not installed, so not removed\n","The following packages were automatically installed and are no longer required:\n"," default-jre dkms freeglut3 freeglut3-dev keyboard-configuration libargon2-0\n"," libcap2 libcryptsetup12 libcublas-dev-11-0 libcufft-11-0 libcufft-11-1\n"," libcufft-dev-11-0 libcufft-dev-11-1 libcurand-11-0 libcurand-11-1\n"," libcurand-dev-11-0 libcurand-dev-11-1 libcusolver-11-0 libcusolver-11-1\n"," libcusolver-dev-11-0 libcusolver-dev-11-1 libcusparse-11-0\n"," libcusparse-dev-11-0 libdevmapper1.02.1 libfontenc1 libidn11 libip4tc0\n"," libjansson4 libnpp-11-0 libnpp-dev-11-0 libnvidia-cfg1-515\n"," libnvidia-common-460 libnvidia-common-515 libnvidia-decode-515\n"," libnvidia-encode-515 libnvidia-extra-515 libnvidia-fbc1-515 libnvidia-gl-515\n"," libnvjpeg-11-0 libnvjpeg-11-1 libnvjpeg-dev-11-0 libnvjpeg-dev-11-1\n"," libpam-systemd libpolkit-agent-1-0 libpolkit-backend-1-0\n"," libpolkit-gobject-1-0 libxfont2 libxi-dev libxkbfile1 libxmu-dev\n"," libxmu-headers libxnvctrl0 libxtst6 nsight-compute-2020.2.1\n"," nsight-compute-2022.2.0 nsight-systems-2020.3.2 nsight-systems-2020.3.4\n"," nsight-systems-2022.1.3 nvidia-compute-utils-515 nvidia-dkms-515\n"," nvidia-driver-515 nvidia-kernel-common-515 nvidia-kernel-source-515\n"," nvidia-modprobe nvidia-settings nvidia-utils-515 openjdk-11-jre policykit-1\n"," policykit-1-gnome python3-xkit screen-resolution-extra systemd systemd-sysv\n"," udev x11-xkb-utils xserver-common xserver-xorg-core-hwe-18.04\n"," xserver-xorg-video-nvidia-515\n","Use 'apt autoremove' to remove them.\n","The following additional packages will be installed:\n"," libcublas-dev libcublas10\n","The following packages will be REMOVED:\n"," cuda-10-0* cuda-10-1* cuda-11-0* cuda-11-1* cuda-command-line-tools-10-0*\n"," cuda-command-line-tools-10-1* cuda-command-line-tools-11-0*\n"," cuda-command-line-tools-11-1* cuda-compat-11-1* cuda-compiler-10-0*\n"," cuda-compiler-10-1* cuda-compiler-11-0* cuda-compiler-11-1*\n"," cuda-cublas-10-0* cuda-cublas-dev-10-0* cuda-cudart-10-0* cuda-cudart-10-1*\n"," cuda-cudart-11-0* cuda-cudart-11-1* cuda-cudart-dev-10-0*\n"," cuda-cudart-dev-10-1* cuda-cudart-dev-11-0* cuda-cudart-dev-11-1*\n"," cuda-cufft-10-0* cuda-cufft-10-1* cuda-cufft-dev-10-0* cuda-cufft-dev-10-1*\n"," cuda-cuobjdump-10-0* cuda-cuobjdump-10-1* cuda-cuobjdump-11-0*\n"," cuda-cuobjdump-11-1* cuda-cupti-10-0* cuda-cupti-10-1* cuda-cupti-11-0*\n"," cuda-cupti-11-1* cuda-cupti-dev-11-0* cuda-cupti-dev-11-1* cuda-curand-10-0*\n"," cuda-curand-10-1* cuda-curand-dev-10-0* cuda-curand-dev-10-1*\n"," cuda-cusolver-10-0* cuda-cusolver-10-1* cuda-cusolver-dev-10-0*\n"," cuda-cusolver-dev-10-1* cuda-cusparse-10-0* cuda-cusparse-10-1*\n"," cuda-cusparse-dev-10-0* cuda-cusparse-dev-10-1* cuda-demo-suite-10-0*\n"," cuda-demo-suite-10-1* cuda-demo-suite-11-0* cuda-demo-suite-11-1*\n"," cuda-documentation-10-0* cuda-documentation-10-1* cuda-documentation-11-0*\n"," cuda-documentation-11-1* cuda-driver-dev-10-0* cuda-driver-dev-10-1*\n"," cuda-driver-dev-11-0* cuda-driver-dev-11-1* cuda-drivers* cuda-drivers-515*\n"," cuda-gdb-10-0* cuda-gdb-10-1* cuda-gdb-11-0* cuda-gdb-11-1*\n"," cuda-gpu-library-advisor-10-0* cuda-gpu-library-advisor-10-1* cuda-keyring*\n"," cuda-libraries-10-0* cuda-libraries-10-1* cuda-libraries-11-0*\n"," cuda-libraries-11-1* cuda-libraries-dev-10-0* cuda-libraries-dev-10-1*\n"," cuda-libraries-dev-11-0* cuda-libraries-dev-11-1* cuda-license-10-0*\n"," cuda-license-10-1* cuda-memcheck-10-0* cuda-memcheck-10-1*\n"," cuda-memcheck-11-0* cuda-memcheck-11-1* cuda-minimal-build-11-1*\n"," cuda-misc-headers-10-0* cuda-misc-headers-10-1* cuda-npp-10-0*\n"," cuda-npp-10-1* cuda-npp-dev-10-0* cuda-npp-dev-10-1* cuda-nsight-10-0*\n"," cuda-nsight-10-1* cuda-nsight-11-0* cuda-nsight-11-1*\n"," cuda-nsight-compute-10-0* cuda-nsight-compute-10-1*\n"," cuda-nsight-compute-11-0* cuda-nsight-compute-11-1*\n"," cuda-nsight-systems-10-1* cuda-nsight-systems-11-0*\n"," cuda-nsight-systems-11-1* cuda-nvcc-10-0* cuda-nvcc-10-1* cuda-nvcc-11-0*\n"," cuda-nvcc-11-1* cuda-nvdisasm-10-0* cuda-nvdisasm-10-1* cuda-nvdisasm-11-0*\n"," cuda-nvdisasm-11-1* cuda-nvgraph-10-0* cuda-nvgraph-10-1*\n"," cuda-nvgraph-dev-10-0* cuda-nvgraph-dev-10-1* cuda-nvjpeg-10-0*\n"," cuda-nvjpeg-10-1* cuda-nvjpeg-dev-10-0* cuda-nvjpeg-dev-10-1*\n"," cuda-nvml-dev-10-0* cuda-nvml-dev-10-1* cuda-nvml-dev-11-0*\n"," cuda-nvml-dev-11-1* cuda-nvprof-10-0* cuda-nvprof-10-1* cuda-nvprof-11-0*\n"," cuda-nvprof-11-1* cuda-nvprune-10-0* cuda-nvprune-10-1* cuda-nvprune-11-0*\n"," cuda-nvprune-11-1* cuda-nvrtc-10-0* cuda-nvrtc-10-1* cuda-nvrtc-11-0*\n"," cuda-nvrtc-11-1* cuda-nvrtc-dev-10-0* cuda-nvrtc-dev-10-1*\n"," cuda-nvrtc-dev-11-0* cuda-nvrtc-dev-11-1* cuda-nvtx-10-0* cuda-nvtx-10-1*\n"," cuda-nvtx-11-0* cuda-nvtx-11-1* cuda-nvvp-10-0* cuda-nvvp-10-1*\n"," cuda-nvvp-11-0* cuda-nvvp-11-1* cuda-runtime-10-0* cuda-runtime-10-1*\n"," cuda-runtime-11-0* cuda-runtime-11-1* cuda-samples-10-0* cuda-samples-10-1*\n"," cuda-samples-11-0* cuda-samples-11-1* cuda-sanitizer-11-0*\n"," cuda-sanitizer-11-1* cuda-sanitizer-api-10-1* cuda-toolkit-10-0*\n"," cuda-toolkit-10-1* cuda-toolkit-11-0* cuda-toolkit-11-1* cuda-tools-10-0*\n"," cuda-tools-10-1* cuda-tools-11-0* cuda-tools-11-1* cuda-visual-tools-10-0*\n"," cuda-visual-tools-10-1* cuda-visual-tools-11-0* cuda-visual-tools-11-1*\n","The following packages will be upgraded:\n"," libcublas-dev libcublas10\n","2 upgraded, 0 newly installed, 169 to remove and 40 not upgraded.\n","Need to get 85.6 MB of archives.\n","After this operation, 8,209 MB disk space will be freed.\n","Get:1 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 libcublas10 10.2.3.254-1 [43.1 MB]\n","Get:2 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 libcublas-dev 10.2.3.254-1 [42.4 MB]\n","Fetched 85.6 MB in 1s (59.1 MB/s)\n","(Reading database ... 155629 files and directories currently installed.)\n","Removing cuda-10-0 (10.0.130-1) ...\n","Removing cuda-10-1 (10.1.243-1) ...\n","Removing cuda-11-0 (11.0.3-1) 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configuration files for cuda-cusolver-10-0 (10.0.130-1) ...\n","Purging configuration files for cuda-nvjpeg-10-1 (10.1.243-1) ...\n","Purging configuration files for cuda-curand-10-0 (10.0.130-1) ...\n","Purging configuration files for cuda-sanitizer-api-10-1 (10.1.243-1) ...\n","Purging configuration files for cuda-cufft-10-1 (10.1.243-1) ...\n","Purging configuration files for cuda-nvprof-10-1 (10.1.243-1) ...\n","Purging configuration files for cuda-nvrtc-10-1 (10.1.243-1) ...\n","Purging configuration files for cuda-cublas-10-0 (10.0.130-1) ...\n","Purging configuration files for cuda-npp-10-1 (10.1.243-1) ...\n","Purging configuration files for cuda-visual-tools-10-1 (10.1.243-1) ...\n","Purging configuration files for cuda-toolkit-10-0 (10.0.130-1) ...\n","Purging configuration files for cuda-visual-tools-11-1 (11.1.1-1) ...\n","Purging configuration files for cuda-toolkit-11-0 (11.0.3-1) ...\n","Purging configuration files for cuda-cudart-dev-10-0 (10.0.130-1) ...\n","Purging configuration files for cuda-nvcc-10-0 (10.0.130-1) ...\n","Purging configuration files for cuda-nvprof-10-0 (10.0.130-1) ...\n","Purging configuration files for cuda-keyring (1.0-1) ...\n","Purging configuration files for cuda-nvrtc-10-0 (10.0.130-1) ...\n","Purging configuration files for cuda-nvtx-10-0 (10.0.130-1) ...\n","Purging configuration files for cuda-cudart-11-0 (11.0.221-1) ...\n","Purging configuration files for cuda-toolkit-10-1 (10.1.243-1) ...\n","Purging configuration files for cuda-visual-tools-11-0 (11.0.3-1) ...\n"]}],"source":["!apt-get --purge remove 'cuda*'"]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":113247,"status":"ok","timestamp":1653381195515,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"vxVI6Etxxipc","outputId":"c39b77fb-1b12-49fe-e5b1-98313157f1e6"},"outputs":[{"output_type":"stream","name":"stdout","text":["Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Looking in links: https://download.pytorch.org/whl/torch_stable.html\n","Collecting torch==1.10.1+cu102\n"," Downloading https://download.pytorch.org/whl/cu102/torch-1.10.1%2Bcu102-cp37-cp37m-linux_x86_64.whl (881.9 MB)\n","\u001b[K |██████████████████████████████▎ | 834.1 MB 1.2 MB/s eta 0:00:40tcmalloc: large alloc 1147494400 bytes == 0x39626000 @ 0x7f166b16d615 0x592b76 0x4df71e 0x59afff 0x515655 0x549576 0x593fce 0x548ae9 0x51566f 0x549576 0x593fce 0x548ae9 0x5127f1 0x598e3b 0x511f68 0x598e3b 0x511f68 0x598e3b 0x511f68 0x4bc98a 0x532e76 0x594b72 0x515600 0x549576 0x593fce 0x548ae9 0x5127f1 0x549576 0x593fce 0x5118f8 0x593dd7\n","\u001b[K |████████████████████████████████| 881.9 MB 16 kB/s \n","\u001b[?25hCollecting torchvision==0.11.2+cu102\n"," Downloading https://download.pytorch.org/whl/cu102/torchvision-0.11.2%2Bcu102-cp37-cp37m-linux_x86_64.whl (23.2 MB)\n","\u001b[K 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installation: torchvision 0.12.0+cu113\n"," Uninstalling torchvision-0.12.0+cu113:\n"," Successfully uninstalled torchvision-0.12.0+cu113\n"," Attempting uninstall: torchaudio\n"," Found existing installation: torchaudio 0.11.0+cu113\n"," Uninstalling torchaudio-0.11.0+cu113:\n"," Successfully uninstalled torchaudio-0.11.0+cu113\n","\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n","torchtext 0.12.0 requires torch==1.11.0, but you have torch 1.10.1+cu102 which is incompatible.\u001b[0m\n","Successfully installed torch-1.10.1+cu102 torchaudio-0.10.1+rocm4.1 torchvision-0.11.2+cu102\n"]}],"source":["!pip3 install torch==1.10.1+cu102 torchvision==0.11.2+cu102 torchaudio==0.10.1 -f https://download.pytorch.org/whl/torch_stable.html"]},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"elapsed":11479,"status":"ok","timestamp":1653381262095,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"BvvcVLXSVcdo","outputId":"9e372c96-1c17-4b33-f4ca-ed43a730fc60"},"outputs":[{"output_type":"stream","name":"stdout","text":["Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Looking in links: https://dl.fbaipublicfiles.com/detectron2/wheels/cu102/torch1.10/index.html\n","Collecting detectron2\n"," Downloading https://dl.fbaipublicfiles.com/detectron2/wheels/cu102/torch1.10/detectron2-0.6%2Bcu102-cp37-cp37m-linux_x86_64.whl (6.5 MB)\n","\u001b[K |████████████████████████████████| 6.5 MB 5.5 MB/s \n","\u001b[?25hRequirement already satisfied: cloudpickle in /usr/local/lib/python3.7/dist-packages (from detectron2) (1.3.0)\n","Requirement already satisfied: termcolor>=1.1 in /usr/local/lib/python3.7/dist-packages (from detectron2) (1.1.0)\n","Requirement already satisfied: tensorboard in /usr/local/lib/python3.7/dist-packages (from detectron2) (2.8.0)\n","Requirement already satisfied: pycocotools>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from detectron2) (2.0.4)\n","Requirement already satisfied: tabulate in /usr/local/lib/python3.7/dist-packages (from detectron2) (0.8.9)\n","Collecting hydra-core>=1.1\n"," Downloading hydra_core-1.2.0-py3-none-any.whl (151 kB)\n","\u001b[K |████████████████████████████████| 151 kB 8.1 MB/s \n","\u001b[?25hRequirement already satisfied: tqdm>4.29.0 in /usr/local/lib/python3.7/dist-packages (from detectron2) (4.64.0)\n","Collecting iopath<0.1.10,>=0.1.7\n"," Downloading iopath-0.1.9-py3-none-any.whl (27 kB)\n","Collecting fvcore<0.1.6,>=0.1.5\n"," Downloading fvcore-0.1.5.post20220512.tar.gz (50 kB)\n","\u001b[K |████████████████████████████████| 50 kB 7.1 MB/s \n","\u001b[?25hCollecting yacs>=0.1.8\n"," Downloading yacs-0.1.8-py3-none-any.whl (14 kB)\n","Requirement already satisfied: pydot in /usr/local/lib/python3.7/dist-packages (from detectron2) (1.3.0)\n","Requirement already satisfied: Pillow>=7.1 in /usr/local/lib/python3.7/dist-packages (from detectron2) (7.1.2)\n","Requirement already satisfied: future in /usr/local/lib/python3.7/dist-packages (from detectron2) (0.16.0)\n","Collecting black==21.4b2\n"," Downloading black-21.4b2-py3-none-any.whl (130 kB)\n","\u001b[K 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kB)\n","\u001b[K |████████████████████████████████| 117 kB 69.5 MB/s \n","\u001b[?25hRequirement already satisfied: importlib-resources in /usr/local/lib/python3.7/dist-packages (from hydra-core>=1.1->detectron2) (5.7.1)\n","Collecting portalocker\n"," Downloading portalocker-2.4.0-py2.py3-none-any.whl (16 kB)\n","Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib->detectron2) (0.11.0)\n","Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->detectron2) (2.8.2)\n","Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->detectron2) (1.4.2)\n","Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->detectron2) (3.0.9)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from 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google-auth<3,>=1.6.3->tensorboard->detectron2) (4.8)\n","Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.7/dist-packages (from google-auth<3,>=1.6.3->tensorboard->detectron2) (0.2.8)\n","Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from google-auth<3,>=1.6.3->tensorboard->detectron2) (4.2.4)\n","Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.7/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard->detectron2) (1.3.1)\n","Requirement already satisfied: importlib-metadata>=4.4 in /usr/local/lib/python3.7/dist-packages (from markdown>=2.6.8->tensorboard->detectron2) (4.11.3)\n","Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.7/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard->detectron2) (0.4.8)\n","Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard->detectron2) (2.10)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard->detectron2) (2022.5.18.1)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard->detectron2) (3.0.4)\n","Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard->detectron2) (1.24.3)\n","Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard->detectron2) (3.2.0)\n","Building wheels for collected packages: fvcore, antlr4-python3-runtime\n"," Building wheel for fvcore (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Created wheel for fvcore: filename=fvcore-0.1.5.post20220512-py3-none-any.whl size=61288 sha256=34d1da0489e2e122bfba96ed79bb8bffe8fc39ee136fcc21c04a057a12006032\n"," Stored in directory: /root/.cache/pip/wheels/68/20/f9/a11a0dd63f4c13678b2a5ec488e48078756505c7777b75b29e\n"," Building wheel for antlr4-python3-runtime (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Created wheel for antlr4-python3-runtime: filename=antlr4_python3_runtime-4.9.3-py3-none-any.whl size=144575 sha256=665cbc7d8e977e11876cf6ce9c6b654d9b7db3da4b6a8cb46cf7bb41ac3ea9a0\n"," Stored in directory: /root/.cache/pip/wheels/8b/8d/53/2af8772d9aec614e3fc65e53d4a993ad73c61daa8bbd85a873\n","Successfully built fvcore antlr4-python3-runtime\n","Installing collected packages: portalocker, antlr4-python3-runtime, yacs, typed-ast, toml, regex, pathspec, omegaconf, mypy-extensions, iopath, hydra-core, fvcore, black, detectron2\n"," Attempting uninstall: regex\n"," Found existing installation: regex 2019.12.20\n"," Uninstalling regex-2019.12.20:\n"," Successfully uninstalled regex-2019.12.20\n","Successfully installed antlr4-python3-runtime-4.9.3 black-21.4b2 detectron2-0.6+cu102 fvcore-0.1.5.post20220512 hydra-core-1.2.0 iopath-0.1.9 mypy-extensions-0.4.3 omegaconf-2.2.1 pathspec-0.9.0 portalocker-2.4.0 regex-2022.4.24 toml-0.10.2 typed-ast-1.5.4 yacs-0.1.8\n"]},{"output_type":"display_data","data":{"application/vnd.colab-display-data+json":{"pip_warning":{"packages":["pydevd_plugins"]}}},"metadata":{}}],"source":["!pip3 install detectron2 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cu102/torch1.10/index.html"]},{"cell_type":"code","execution_count":5,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1576,"status":"ok","timestamp":1653381310805,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"fsNZSLCcVw3n","outputId":"bdb05308-5812-4420-8439-02611d251eae"},"outputs":[{"output_type":"stream","name":"stdout","text":["1.10.1+cu102 True\n"]}],"source":["import torch, torchvision\n","torch.cuda.empty_cache()\n","\n","print(torch.__version__, torch.cuda.is_available())\n","# assert torch.__version__.startswith(\"1.10\") # please manually install torch 1.9 if Colab changes its default version"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"d0crc13-V0JY"},"outputs":[],"source":["# !pip3 install torch torchvision torchaudio"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"ra22BIMlWh4q"},"outputs":[],"source":["# Some basic setup:\n","# Setup detectron2 logger\n","import detectron2\n","from detectron2.utils.logger import setup_logger\n","setup_logger()\n","\n","# import some common libraries\n","import numpy as np\n","import os, json, cv2, random\n","from google.colab.patches import cv2_imshow\n","\n","# import some common detectron2 utilities\n","from detectron2 import model_zoo\n","from detectron2.engine import DefaultPredictor\n","from detectron2.config import get_cfg\n","from detectron2.utils.visualizer import Visualizer\n","from detectron2.data import MetadataCatalog, DatasetCatalog"]},{"cell_type":"markdown","metadata":{"id":"FRGrf6zxvmWu"},"source":["### Load Data"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":24952,"status":"ok","timestamp":1653375965138,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"cyHOq5yMvpyD","outputId":"59e2044c-d2c8-4ea5-bd7e-5116f8b932e2"},"outputs":[{"name":"stdout","output_type":"stream","text":["Mounted at /content/drive\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":8,"status":"ok","timestamp":1649641334138,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"rFXpSCht5rGK","outputId":"257b747b-e4a1-45dc-d89d-471af3e727c0"},"outputs":[{"name":"stdout","output_type":"stream","text":["/content\n"]}],"source":["!pwd"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":488,"status":"ok","timestamp":1653375983255,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"GIKvaFIy5w-W","outputId":"1fdc0e26-68fe-4198-f833-3dad9f62e691"},"outputs":[{"name":"stdout","output_type":"stream","text":["/content/drive/MyDrive/Colab Notebooks\n","/content/drive/MyDrive/Colab Notebooks\n"]}],"source":["%cd drive/MyDrive/Colab\\ Notebooks\n","!pwd"]},{"cell_type":"code","execution_count":8,"metadata":{"id":"ZJWaLekQ8TMA","executionInfo":{"status":"ok","timestamp":1653381487613,"user_tz":-540,"elapsed":289,"user":{"displayName":"조한별","userId":"01444879122726041884"}}},"outputs":[],"source":["import glob\n","import os\n","import cv2"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"iYBBrQXLvssK"},"outputs":[],"source":["# if your dataset is in COCO format, this cell can be replaced by the following three lines:\n","# from detectron2.data.datasets import register_coco_instances\n","# register_coco_instances(\"my_dataset_train\", {}, \"json_annotation_train.json\", \"path/to/image/dir\")\n","# register_coco_instances(\"my_dataset_val\", {}, \"json_annotation_val.json\", \"path/to/image/dir\")\n","\n","from detectron2.structures import BoxMode\n","\n","def get_carplate_dicts(img_dir):\n"," json_file = os.path.join(img_dir, \"via_region_data.json\")\n"," \n"," with open(json_file) as f:\n"," imgs_anns = json.load(f)\n"," \n"," dataset_dicts = []\n"," for idx, v in enumerate(imgs_anns.values()):\n"," record = {}\n"," print(v)\n"," filename = os.path.join(img_dir, v[\"filename\"])\n"," print(filename)\n"," height, width = cv2.imread(filename).shape[:2]\n"," \n"," record[\"file_name\"] = filename\n"," record[\"image_id\"] = idx\n"," record[\"height\"] = height\n"," record[\"width\"] = width\n"," \n"," annos = v[\"regions\"]\n"," #print(annos[0].keys())\n"," objs = []\n"," for anno in annos:\n"," #assert not anno[\"region_attributes\"]\n"," #anno = anno[\"shape_attributes\"]\n"," anno = anno[\"shape_attributes\"]\n"," px = anno[\"all_points_x\"]\n"," py = anno[\"all_points_y\"]\n"," poly = [(x + 0.5, y + 0.5) for x, y in zip(px, py)]\n"," poly = [p for x in poly for p in x]\n","\n"," obj = {\n"," \"bbox\": [np.min(px), np.min(py), np.max(px), np.max(py)],\n"," \"bbox_mode\": BoxMode.XYXY_ABS,\n"," \"segmentation\": [poly],\n"," \"category_id\": 0,\n"," }\n"," objs.append(obj)\n"," record[\"annotations\"] = objs\n"," dataset_dicts.append(record)\n"," return dataset_dicts\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"FJnSmNBdC9bd"},"outputs":[],"source":["for d in [\"train\", \"val\"]:\n"," DatasetCatalog.register(\"carplate_\" + d, lambda d=d: get_carplate_dicts(\"./carplate/\" + d))\n"," MetadataCatalog.get(\"carplate_\" + d).set(thing_classes=[\"carplate\"])\n","carplate_metadata = MetadataCatalog.get(\"carplate_train\")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"elapsed":60603,"status":"ok","timestamp":1653376054553,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"U6qHPecgv3IK","outputId":"4e0fa7a3-f3f7-47fd-9e7c-38b7ba56d5e6"},"outputs":[{"name":"stdout","output_type":"stream","text":["{'filename': '21765117_37284799007095384.jpg', 'size': 13487, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [95, 156, 156, 94, 95], 'all_points_y': [168, 168, 181, 181, 168]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21765117_37284799007095384.jpg\n","{'filename': '21774755_37643009578239166.jpg', 'size': 18315, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [85, 85, 150, 150, 85], 'all_points_y': [191, 205, 209, 194, 192]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21774755_37643009578239166.jpg\n","{'filename': '21793134_37998533217713863.jpg', 'size': 13898, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [47, 48, 75, 75, 47], 'all_points_y': [197, 216, 220, 201, 198]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21793134_37998533217713863.jpg\n","{'filename': '21821157_38599393863300203.jpg', 'size': 11964, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [138, 138, 99, 99, 138], 'all_points_y': [173, 193, 193, 173, 173]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21821157_38599393863300203.jpg\n","{'filename': '22128663_45771711213987460.jpg', 'size': 19040, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [137, 137, 210, 210, 136], 'all_points_y': [170, 184, 185, 171, 170]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22128663_45771711213987460.jpg\n","{'filename': '22131901_45849902630591043.jpg', 'size': 16580, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [279, 278, 316, 318, 278], 'all_points_y': [168, 200, 191, 163, 168]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22131901_45849902630591043.jpg\n","{'filename': '22139001_46120042876094304.jpg', 'size': 15449, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [49, 50, 98, 98, 50], 'all_points_y': [194, 208, 208, 193, 193]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22139001_46120042876094304.jpg\n","{'filename': '22139454_46122703160181634.jpg', 'size': 18187, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [148, 149, 237, 238, 148], 'all_points_y': [204, 220, 220, 203, 204]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22139454_46122703160181634.jpg\n","{'filename': '22150620_46313687868646516.jpg', 'size': 16479, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [40, 40, 85, 86, 40], 'all_points_y': [181, 192, 198, 186, 181]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22150620_46313687868646516.jpg\n","{'filename': '22153916_46379459003134773.jpg', 'size': 16906, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [49, 49, 93, 93, 50], 'all_points_y': [201, 212, 213, 201, 201]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22153916_46379459003134773.jpg\n","{'filename': '22166861_4465623725277324.jpg', 'size': 17144, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [133, 133, 228, 228, 132], 'all_points_y': [190, 209, 209, 191, 190]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22166861_4465623725277324.jpg\n","{'filename': '22307448_49666028439210654.jpg', 'size': 76731, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [134, 134, 86, 87, 134], 'all_points_y': [350, 385, 376, 342, 350]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22307448_49666028439210654.jpg\n","{'filename': '22538885_12578328969726304.jpg', 'size': 18769, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [170, 170, 244, 244, 170], 'all_points_y': [173, 189, 188, 172, 173]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22538885_12578328969726304.jpg\n","{'filename': '22584203_1090603099253838.jpg', 'size': 55168, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [580, 650, 650, 581, 581], 'all_points_y': [393, 377, 398, 417, 393]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22584203_1090603099253838.jpg\n","{'filename': '22762250_4965387232044186.jpg', 'size': 52896, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [505, 541, 540, 502, 505], 'all_points_y': [378, 370, 394, 405, 378]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22762250_4965387232044186.jpg\n","{'filename': '22798772_5437674896359105.jpg', 'size': 54449, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [308, 397, 397, 307, 308], 'all_points_y': [402, 402, 440, 441, 402]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22798772_5437674896359105.jpg\n","{'filename': '22798772_5437675018421986.jpg', 'size': 49738, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [519, 576, 576, 519, 519], 'all_points_y': [384, 374, 408, 418, 384]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22798772_5437675018421986.jpg\n","{'filename': '22798772_5437675118662300.jpg', 'size': 58299, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [120, 121, 176, 176, 121], 'all_points_y': [368, 402, 415, 379, 368]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22798772_5437675118662300.jpg\n","{'filename': '22800904_5921360338950693.jpg', 'size': 16657, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [141, 231, 231, 140, 141], 'all_points_y': [178, 178, 195, 196, 178]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22800904_5921360338950693.jpg\n","{'filename': '22853059_6366680149928242.jpg', 'size': 65984, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [447, 560, 559, 446, 447], 'all_points_y': [415, 412, 435, 438, 415]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22853059_6366680149928242.jpg\n","{'filename': '22854180_6372343488739476.jpg', 'size': 17283, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [41, 97, 96, 40, 41], 'all_points_y': [172, 174, 191, 188, 172]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22854180_6372343488739476.jpg\n","{'filename': '22854467_6379524420692229.jpg', 'size': 22309, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [40, 81, 81, 40, 40], 'all_points_y': [174, 184, 199, 187, 174]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22854467_6379524420692229.jpg\n","{'filename': '22867139_6525486266926368.jpg', 'size': 68962, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [286, 460, 460, 285, 286], 'all_points_y': [388, 389, 419, 418, 388]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867139_6525486266926368.jpg\n","{'filename': '22867139_6525486502369306.jpg', 'size': 71605, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [93, 197, 200, 97, 93], 'all_points_y': [327, 348, 375, 353, 326]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867139_6525486502369306.jpg\n","{'filename': '22867139_6525486734628649.jpg', 'size': 74985, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [551, 638, 633, 547, 551], 'all_points_y': [342, 326, 349, 368, 342]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867139_6525486734628649.jpg\n","{'filename': '22867669_7628125929397472.jpg', 'size': 12605, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [75, 104, 104, 75, 75], 'all_points_y': [168, 169, 183, 182, 169]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867669_7628125929397472.jpg\n","{'filename': '22876906_6882827826287234.jpg', 'size': 32332, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [284, 438, 439, 285, 285], 'all_points_y': [435, 435, 464, 465, 435]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22876906_6882827826287234.jpg\n","{'filename': '22877731_6784822717297546.jpg', 'size': 15748, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [165, 206, 206, 165, 165], 'all_points_y': [208, 208, 225, 226, 208]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22877731_6784822717297546.jpg\n","{'filename': '22878486_6789431365012443.jpg', 'size': 11757, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [102, 159, 159, 102, 102], 'all_points_y': [170, 170, 182, 182, 170]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22878486_6789431365012443.jpg\n","{'filename': '22901882_7128311537589833.jpg', 'size': 18037, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [58, 114, 115, 58, 57], 'all_points_y': [166, 185, 200, 180, 166]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22901882_7128311537589833.jpg\n","{'filename': '22902002_7131472262198416.jpg', 'size': 21071, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [155, 208, 208, 155, 155], 'all_points_y': [218, 218, 240, 240, 218]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22902002_7131472262198416.jpg\n","{'filename': '22902002_7131478147507051.jpg', 'size': 58419, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [74, 135, 143, 82, 74], 'all_points_y': [346, 367, 408, 383, 346]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22902002_7131478147507051.jpg\n","{'filename': '22903549_7139175246594729.jpg', 'size': 16090, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [40, 95, 95, 42, 41], 'all_points_y': [167, 172, 187, 181, 168]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22903549_7139175246594729.jpg\n","{'filename': '22903702_7140169948956332.jpg', 'size': 18618, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [61, 129, 129, 63, 62], 'all_points_y': [174, 180, 202, 195, 174]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22903702_7140169948956332.jpg\n","{'filename': '22909003_8872666968866685.jpg', 'size': 64138, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [298, 453, 453, 298, 299], 'all_points_y': [371, 372, 402, 401, 372]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22909003_8872666968866685.jpg\n","{'filename': '22909003_8872667142075785.jpg', 'size': 73661, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [109, 157, 157, 110, 109], 'all_points_y': [312, 335, 352, 329, 312]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22909003_8872667142075785.jpg\n","{'filename': '22911289_7381775810933651.jpg', 'size': 16443, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [296, 320, 320, 296, 296], 'all_points_y': [172, 166, 175, 180, 172]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22911289_7381775810933651.jpg\n","{'filename': '22918213_7479987932228958.jpg', 'size': 41701, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [513, 580, 580, 512, 513], 'all_points_y': [371, 345, 369, 396, 371]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22918213_7479987932228958.jpg\n","{'filename': '22918213_7479988077801989.jpg', 'size': 41527, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [251, 437, 436, 252, 251], 'all_points_y': [410, 410, 440, 441, 409]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22918213_7479988077801989.jpg\n","{'filename': '22928047_7644052088040167.jpg', 'size': 16182, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [145, 211, 210, 145, 145], 'all_points_y': [197, 198, 224, 223, 197]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22928047_7644052088040167.jpg\n","{'filename': '22929564_7660514277551917.jpg', 'size': 19290, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [302, 344, 342, 301, 302], 'all_points_y': [168, 147, 165, 187, 169]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22929564_7660514277551917.jpg\n","{'filename': '22929600_10059914292650849.jpg', 'size': 16701, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [146, 203, 203, 146, 146], 'all_points_y': [217, 216, 240, 241, 217]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22929600_10059914292650849.jpg\n","{'filename': '22934023_7741546994767615.jpg', 'size': 53940, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [140, 256, 256, 140, 140], 'all_points_y': [309, 309, 335, 335, 309]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': 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\n","text/plain":["<PIL.Image.Image image mode=RGB size=360x270 at 0x7F77C428FCD0>"]},"metadata":{},"output_type":"display_data"}],"source":["dataset_dicts = get_carplate_dicts('./carplate/train')\n","for d in random.sample(dataset_dicts, 1):\n"," img = cv2.imread(d[\"file_name\"])\n"," visualizer = Visualizer(img[:, :, ::-1], metadata=carplate_metadata, scale=1.0)\n"," out = visualizer.draw_dataset_dict(d)\n"," cv2_imshow(out.get_image()[:, :, ::-1])"]},{"cell_type":"markdown","metadata":{"id":"fopvgnnpv83i"},"source":["### Train"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"5J1syItXJkNE"},"outputs":[],"source":["import copy\n","from detectron2.utils.logger import setup_logger\n","from detectron2.utils.visualizer import Visualizer\n","from detectron2.data import detection_utils as utils\n","import detectron2.data.transforms as T\n","from detectron2.engine import DefaultTrainer\n","import numpy\n","\n","def custom_mapper(dataset_dict):\n","\n"," # Implement a mapper, similar to the default DatasetMapper, but with your own customizations\n"," dataset_dict = copy.deepcopy(dataset_dict) # it will be modified by code below\n"," image = utils.read_image(dataset_dict[\"file_name\"], format=\"RGB\")\n","\n"," #transform_list = [T.Resize(x) for x in resize_list]\n"," transform_list = [T.RandomBrightness(0.3, 1.5),\n"," #T.Resize((800, 800))\n"," ]\n"," #print(transform_list)\n"," \n"," image, transforms = T.apply_transform_gens(transform_list, image)\n"," dataset_dict[\"image\"] = torch.as_tensor(image.transpose(2, 0, 1).astype(\"float32\"))\n","\n"," annos = [\n"," utils.transform_instance_annotations(obj, transforms, image.shape[:2])\n"," for obj in dataset_dict.pop(\"annotations\")\n"," if obj.get(\"iscrowd\", 0) == 0\n"," ]\n"," instances = utils.annotations_to_instances(annos, image.shape[:2])\n"," dataset_dict[\"instances\"] = utils.filter_empty_instances(instances)\n"," return dataset_dict\n","\n","class WheatTrainer(DefaultTrainer):\n"," \n"," @classmethod\n"," def build_train_loader(cls, cfg):\n"," return build_detection_train_loader(cfg, mapper=custom_mapper)\n","\n","DATA_DIR = '/content/drive/MyDrive/Colab Notebooks/carplate/train'\n","\n","def register_dataset(df, dataset_label='wheat_train', image_dir = DATA_DIR):\n"," \n"," # Register dataset - if dataset is already registered, give it a new name \n"," try:\n"," DatasetCatalog.register(dataset_label, lambda d=df: custom_dataset(df, image_dir))\n"," MetadataCatalog.get(dataset_label).set(thing_classes = ['wheat'])\n"," except:\n"," # Add random int to dataset name to not run into 'Already registered' error\n"," n = random.randint(1, 1000)\n"," dataset_label = dataset_label + str(n)\n"," DatasetCatalog.register(dataset_label, lambda d=df: custom_dataset(df, image_dir))\n"," MetadataCatalog.get(dataset_label).set(thing_classes = ['wheat'])\n","\n"," return MetadataCatalog.get(dataset_label), dataset_label\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1073,"status":"ok","timestamp":1653377893744,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"5sAq42rXwIqF","outputId":"480db37e-397c-4366-97fa-7dcf8b088172"},"outputs":[{"name":"stdout","output_type":"stream","text":["\u001b[32m[05/24 07:38:12 d2.engine.defaults]: \u001b[0mModel:\n","GeneralizedRCNN(\n"," (backbone): FPN(\n"," (fpn_lateral2): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n"," (fpn_output2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n"," (fpn_lateral3): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n"," (fpn_output3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n"," (fpn_lateral4): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1))\n"," (fpn_output4): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n"," (fpn_lateral5): Conv2d(2048, 256, kernel_size=(1, 1), stride=(1, 1))\n"," (fpn_output5): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n"," (top_block): LastLevelMaxPool()\n"," (bottom_up): ResNet(\n"," (stem): BasicStem(\n"," (conv1): Conv2d(\n"," 3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n"," )\n"," )\n"," (res2): Sequential(\n"," (0): BottleneckBlock(\n"," (shortcut): Conv2d(\n"," 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv1): Conv2d(\n"," 64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," )\n"," (1): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," )\n"," (2): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," )\n"," )\n"," (res3): Sequential(\n"," (0): BottleneckBlock(\n"," (shortcut): Conv2d(\n"," 256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," (conv1): Conv2d(\n"," 256, 128, kernel_size=(1, 1), stride=(2, 2), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," )\n"," (1): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," )\n"," (2): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," )\n"," (3): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," )\n"," )\n"," (res4): Sequential(\n"," (0): BottleneckBlock(\n"," (shortcut): Conv2d(\n"," 512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n"," )\n"," (conv1): Conv2d(\n"," 512, 256, kernel_size=(1, 1), stride=(2, 2), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n"," )\n"," )\n"," (1): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n"," )\n"," )\n"," (2): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n"," )\n"," )\n"," (3): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n"," )\n"," )\n"," (4): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n"," )\n"," )\n"," (5): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05)\n"," )\n"," )\n"," )\n"," (res5): Sequential(\n"," (0): BottleneckBlock(\n"," (shortcut): Conv2d(\n"," 1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05)\n"," )\n"," (conv1): Conv2d(\n"," 1024, 512, kernel_size=(1, 1), stride=(2, 2), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05)\n"," )\n"," )\n"," (1): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05)\n"," )\n"," )\n"," (2): BottleneckBlock(\n"," (conv1): Conv2d(\n"," 2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," (conv2): Conv2d(\n"," 512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05)\n"," )\n"," (conv3): Conv2d(\n"," 512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False\n"," (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05)\n"," )\n"," )\n"," )\n"," )\n"," )\n"," (proposal_generator): RPN(\n"," (rpn_head): StandardRPNHead(\n"," (conv): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)\n"," (activation): ReLU()\n"," )\n"," (objectness_logits): Conv2d(256, 3, kernel_size=(1, 1), stride=(1, 1))\n"," (anchor_deltas): Conv2d(256, 12, kernel_size=(1, 1), stride=(1, 1))\n"," )\n"," (anchor_generator): DefaultAnchorGenerator(\n"," (cell_anchors): BufferList()\n"," )\n"," )\n"," (roi_heads): StandardROIHeads(\n"," (box_pooler): ROIPooler(\n"," (level_poolers): ModuleList(\n"," (0): ROIAlign(output_size=(7, 7), spatial_scale=0.25, sampling_ratio=0, aligned=True)\n"," (1): ROIAlign(output_size=(7, 7), spatial_scale=0.125, sampling_ratio=0, aligned=True)\n"," (2): ROIAlign(output_size=(7, 7), spatial_scale=0.0625, sampling_ratio=0, aligned=True)\n"," (3): ROIAlign(output_size=(7, 7), spatial_scale=0.03125, sampling_ratio=0, aligned=True)\n"," )\n"," )\n"," (box_head): FastRCNNConvFCHead(\n"," (flatten): Flatten(start_dim=1, end_dim=-1)\n"," (fc1): Linear(in_features=12544, out_features=1024, bias=True)\n"," (fc_relu1): ReLU()\n"," (fc2): Linear(in_features=1024, out_features=1024, bias=True)\n"," (fc_relu2): ReLU()\n"," )\n"," (box_predictor): FastRCNNOutputLayers(\n"," (cls_score): Linear(in_features=1024, out_features=2, bias=True)\n"," (bbox_pred): Linear(in_features=1024, out_features=4, bias=True)\n"," )\n"," (mask_pooler): ROIPooler(\n"," (level_poolers): ModuleList(\n"," (0): ROIAlign(output_size=(14, 14), spatial_scale=0.25, sampling_ratio=0, aligned=True)\n"," (1): ROIAlign(output_size=(14, 14), spatial_scale=0.125, sampling_ratio=0, aligned=True)\n"," (2): ROIAlign(output_size=(14, 14), spatial_scale=0.0625, sampling_ratio=0, aligned=True)\n"," (3): ROIAlign(output_size=(14, 14), spatial_scale=0.03125, sampling_ratio=0, aligned=True)\n"," )\n"," )\n"," (mask_head): MaskRCNNConvUpsampleHead(\n"," (mask_fcn1): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)\n"," (activation): ReLU()\n"," )\n"," (mask_fcn2): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)\n"," (activation): ReLU()\n"," )\n"," (mask_fcn3): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)\n"," (activation): ReLU()\n"," )\n"," (mask_fcn4): Conv2d(\n"," 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)\n"," (activation): ReLU()\n"," )\n"," (deconv): ConvTranspose2d(256, 256, kernel_size=(2, 2), stride=(2, 2))\n"," (deconv_relu): ReLU()\n"," (predictor): Conv2d(256, 1, kernel_size=(1, 1), stride=(1, 1))\n"," )\n"," )\n",")\n","{'filename': '21765117_37284799007095384.jpg', 'size': 13487, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [95, 156, 156, 94, 95], 'all_points_y': [168, 168, 181, 181, 168]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21765117_37284799007095384.jpg\n","{'filename': '21774755_37643009578239166.jpg', 'size': 18315, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [85, 85, 150, 150, 85], 'all_points_y': [191, 205, 209, 194, 192]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21774755_37643009578239166.jpg\n","{'filename': '21793134_37998533217713863.jpg', 'size': 13898, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [47, 48, 75, 75, 47], 'all_points_y': [197, 216, 220, 201, 198]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21793134_37998533217713863.jpg\n","{'filename': '21821157_38599393863300203.jpg', 'size': 11964, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [138, 138, 99, 99, 138], 'all_points_y': [173, 193, 193, 173, 173]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21821157_38599393863300203.jpg\n","{'filename': '22128663_45771711213987460.jpg', 'size': 19040, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [137, 137, 210, 210, 136], 'all_points_y': [170, 184, 185, 171, 170]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22128663_45771711213987460.jpg\n","{'filename': '22131901_45849902630591043.jpg', 'size': 16580, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [279, 278, 316, 318, 278], 'all_points_y': [168, 200, 191, 163, 168]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22131901_45849902630591043.jpg\n","{'filename': '22139001_46120042876094304.jpg', 'size': 15449, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [49, 50, 98, 98, 50], 'all_points_y': [194, 208, 208, 193, 193]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22139001_46120042876094304.jpg\n","{'filename': '22139454_46122703160181634.jpg', 'size': 18187, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [148, 149, 237, 238, 148], 'all_points_y': [204, 220, 220, 203, 204]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22139454_46122703160181634.jpg\n","{'filename': '22150620_46313687868646516.jpg', 'size': 16479, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [40, 40, 85, 86, 40], 'all_points_y': [181, 192, 198, 186, 181]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22150620_46313687868646516.jpg\n","{'filename': '22153916_46379459003134773.jpg', 'size': 16906, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [49, 49, 93, 93, 50], 'all_points_y': [201, 212, 213, 201, 201]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22153916_46379459003134773.jpg\n","{'filename': '22166861_4465623725277324.jpg', 'size': 17144, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [133, 133, 228, 228, 132], 'all_points_y': [190, 209, 209, 191, 190]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22166861_4465623725277324.jpg\n","{'filename': '22307448_49666028439210654.jpg', 'size': 76731, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [134, 134, 86, 87, 134], 'all_points_y': [350, 385, 376, 342, 350]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22307448_49666028439210654.jpg\n","{'filename': '22538885_12578328969726304.jpg', 'size': 18769, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [170, 170, 244, 244, 170], 'all_points_y': [173, 189, 188, 172, 173]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22538885_12578328969726304.jpg\n","{'filename': '22584203_1090603099253838.jpg', 'size': 55168, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [580, 650, 650, 581, 581], 'all_points_y': [393, 377, 398, 417, 393]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22584203_1090603099253838.jpg\n","{'filename': '22762250_4965387232044186.jpg', 'size': 52896, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [505, 541, 540, 502, 505], 'all_points_y': [378, 370, 394, 405, 378]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22762250_4965387232044186.jpg\n","{'filename': '22798772_5437674896359105.jpg', 'size': 54449, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [308, 397, 397, 307, 308], 'all_points_y': [402, 402, 440, 441, 402]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22798772_5437674896359105.jpg\n","{'filename': '22798772_5437675018421986.jpg', 'size': 49738, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [519, 576, 576, 519, 519], 'all_points_y': [384, 374, 408, 418, 384]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22798772_5437675018421986.jpg\n","{'filename': '22798772_5437675118662300.jpg', 'size': 58299, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [120, 121, 176, 176, 121], 'all_points_y': [368, 402, 415, 379, 368]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22798772_5437675118662300.jpg\n","{'filename': '22800904_5921360338950693.jpg', 'size': 16657, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [141, 231, 231, 140, 141], 'all_points_y': [178, 178, 195, 196, 178]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22800904_5921360338950693.jpg\n","{'filename': '22853059_6366680149928242.jpg', 'size': 65984, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [447, 560, 559, 446, 447], 'all_points_y': [415, 412, 435, 438, 415]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22853059_6366680149928242.jpg\n","{'filename': '22854180_6372343488739476.jpg', 'size': 17283, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [41, 97, 96, 40, 41], 'all_points_y': [172, 174, 191, 188, 172]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22854180_6372343488739476.jpg\n","{'filename': '22854467_6379524420692229.jpg', 'size': 22309, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [40, 81, 81, 40, 40], 'all_points_y': [174, 184, 199, 187, 174]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22854467_6379524420692229.jpg\n","{'filename': '22867139_6525486266926368.jpg', 'size': 68962, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [286, 460, 460, 285, 286], 'all_points_y': [388, 389, 419, 418, 388]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867139_6525486266926368.jpg\n","{'filename': '22867139_6525486502369306.jpg', 'size': 71605, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [93, 197, 200, 97, 93], 'all_points_y': [327, 348, 375, 353, 326]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867139_6525486502369306.jpg\n","{'filename': '22867139_6525486734628649.jpg', 'size': 74985, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [551, 638, 633, 547, 551], 'all_points_y': [342, 326, 349, 368, 342]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867139_6525486734628649.jpg\n","{'filename': '22867669_7628125929397472.jpg', 'size': 12605, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [75, 104, 104, 75, 75], 'all_points_y': [168, 169, 183, 182, 169]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867669_7628125929397472.jpg\n","{'filename': '22876906_6882827826287234.jpg', 'size': 32332, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [284, 438, 439, 285, 285], 'all_points_y': [435, 435, 464, 465, 435]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22876906_6882827826287234.jpg\n","{'filename': '22877731_6784822717297546.jpg', 'size': 15748, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [165, 206, 206, 165, 165], 'all_points_y': [208, 208, 225, 226, 208]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': 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{}}\n","./carplate/train/23060267_10437382504566251.jpg\n","{'filename': '23060267_10437382631616988.jpg', 'size': 64930, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [129, 190, 191, 129, 130], 'all_points_y': [369, 375, 414, 405, 369]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/23060267_10437382631616988.jpg\n","{'filename': '23061761_10491895240536167.jpg', 'size': 22429, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [41, 78, 78, 41, 40], 'all_points_y': [163, 176, 190, 176, 163]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/23061761_10491895240536167.jpg\n","{'filename': '23061775_10440786360016363.jpg', 'size': 17078, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [178, 279, 275, 176, 179], 'all_points_y': [220, 205, 224, 239, 220]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/23061775_10440786360016363.jpg\n","{'filename': '23061795_10434700387044993.jpg', 'size': 21586, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [128, 227, 226, 128, 128], 'all_points_y': [167, 168, 184, 183, 168]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/23061795_10434700387044993.jpg\n","{'filename': '22181398_46894209157041945.jpg', 'size': 22625, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [309, 325, 323, 308, 309], 'all_points_y': [190, 184, 200, 207, 190]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22181398_46894209157041945.jpg\n","{'filename': '22237981_5834811804322674.jpg', 'size': 20727, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [41, 79, 79, 40, 41], 'all_points_y': [182, 184, 195, 192, 182]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22237981_5834811804322674.jpg\n","\u001b[32m[05/24 07:38:13 d2.data.build]: \u001b[0mRemoved 0 images with no usable annotations. 100 images left.\n","\u001b[32m[05/24 07:38:13 d2.data.build]: \u001b[0mUsing training sampler TrainingSampler\n","\u001b[32m[05/24 07:38:13 d2.data.common]: \u001b[0mSerializing 100 elements to byte tensors and concatenating them all ...\n","\u001b[32m[05/24 07:38:13 d2.data.common]: \u001b[0mSerialized dataset takes 0.05 MiB\n"]}],"source":["from detectron2.data import DatasetCatalog, MetadataCatalog, build_detection_test_loader, build_detection_train_loader\n","import torch,gc\n","\n","gc.collect()\n","torch.cuda.empty_cache()\n","\n","cfg = get_cfg()\n","cfg.merge_from_file(model_zoo.get_config_file(\"COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml\"))\n","#cfg.merge_from_list(['MODEL.DEVICE','cpu']) # CPU 변경\n"," # path to the model we just trained\n","cfg.DATASETS.TRAIN = (\"carplate_train\",)\n","cfg.DATASETS.TEST = ()\n","cfg.DATALOADER.NUM_WORKERS = 2\n","#cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, \"chery_chung_model_220110_backup.pth\")\n","# cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, \"chery_chung_makgok_model_2.pth\")\n","cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url(\"COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml\") # Let training initialize from model zoo\n","cfg.SOLVER.IMS_PER_BATCH = 2\n","cfg.SOLVER.BASE_LR = 0.00025 # pick a good LR\n","cfg.SOLVER.MAX_ITER = 300 # 300 iterations seems good enough for this toy dataset; you will need to train longer for a practical dataset\n","cfg.SOLVER.STEPS = [] # do not decay learning rate\n","cfg.MODEL.ROI_HEADS.BATCH_SIZE_PER_IMAGE = 128 # faster, and good enough for this toy dataset (default: 512)\n","cfg.MODEL.ROI_HEADS.NUM_CLASSES = 1 # only has one class (ballon). (see https://detectron2.readthedocs.io/tutorials/datasets.html#update-the-config-for-new-datasets)\n","# cfg.MODEL\n","# NOTE: this config means the number of classes, but a few popular unofficial tutorials incorrect uses num_classes+1 here.\n","\n","os.makedirs(cfg.OUTPUT_DIR, exist_ok=True)\n","#trainer = DefaultTrainer(cfg)\n","trainer = WheatTrainer(cfg)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"elapsed":50546,"status":"ok","timestamp":1653377955574,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"AbNBqM7nJubj","outputId":"f98385c3-e45a-4b72-b768-24547ccbe581"},"outputs":[{"name":"stdout","output_type":"stream","text":["{'filename': '21765117_37284799007095384.jpg', 'size': 13487, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [95, 156, 156, 94, 95], 'all_points_y': [168, 168, 181, 181, 168]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21765117_37284799007095384.jpg\n","{'filename': '21774755_37643009578239166.jpg', 'size': 18315, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [85, 85, 150, 150, 85], 'all_points_y': [191, 205, 209, 194, 192]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21774755_37643009578239166.jpg\n","{'filename': '21793134_37998533217713863.jpg', 'size': 13898, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [47, 48, 75, 75, 47], 'all_points_y': [197, 216, 220, 201, 198]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21793134_37998533217713863.jpg\n","{'filename': '21821157_38599393863300203.jpg', 'size': 11964, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [138, 138, 99, 99, 138], 'all_points_y': [173, 193, 193, 173, 173]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/21821157_38599393863300203.jpg\n","{'filename': '22128663_45771711213987460.jpg', 'size': 19040, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [137, 137, 210, 210, 136], 'all_points_y': [170, 184, 185, 171, 170]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22128663_45771711213987460.jpg\n","{'filename': '22131901_45849902630591043.jpg', 'size': 16580, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [279, 278, 316, 318, 278], 'all_points_y': [168, 200, 191, 163, 168]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22131901_45849902630591043.jpg\n","{'filename': '22139001_46120042876094304.jpg', 'size': 15449, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [49, 50, 98, 98, 50], 'all_points_y': [194, 208, 208, 193, 193]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22139001_46120042876094304.jpg\n","{'filename': '22139454_46122703160181634.jpg', 'size': 18187, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [148, 149, 237, 238, 148], 'all_points_y': [204, 220, 220, 203, 204]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22139454_46122703160181634.jpg\n","{'filename': '22150620_46313687868646516.jpg', 'size': 16479, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [40, 40, 85, 86, 40], 'all_points_y': [181, 192, 198, 186, 181]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22150620_46313687868646516.jpg\n","{'filename': '22153916_46379459003134773.jpg', 'size': 16906, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [49, 49, 93, 93, 50], 'all_points_y': [201, 212, 213, 201, 201]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22153916_46379459003134773.jpg\n","{'filename': '22166861_4465623725277324.jpg', 'size': 17144, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [133, 133, 228, 228, 132], 'all_points_y': [190, 209, 209, 191, 190]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22166861_4465623725277324.jpg\n","{'filename': '22307448_49666028439210654.jpg', 'size': 76731, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [134, 134, 86, 87, 134], 'all_points_y': [350, 385, 376, 342, 350]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22307448_49666028439210654.jpg\n","{'filename': '22538885_12578328969726304.jpg', 'size': 18769, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [170, 170, 244, 244, 170], 'all_points_y': [173, 189, 188, 172, 173]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22538885_12578328969726304.jpg\n","{'filename': '22584203_1090603099253838.jpg', 'size': 55168, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [580, 650, 650, 581, 581], 'all_points_y': [393, 377, 398, 417, 393]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22584203_1090603099253838.jpg\n","{'filename': '22762250_4965387232044186.jpg', 'size': 52896, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [505, 541, 540, 502, 505], 'all_points_y': [378, 370, 394, 405, 378]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22762250_4965387232044186.jpg\n","{'filename': '22798772_5437674896359105.jpg', 'size': 54449, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [308, 397, 397, 307, 308], 'all_points_y': [402, 402, 440, 441, 402]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22798772_5437674896359105.jpg\n","{'filename': '22798772_5437675018421986.jpg', 'size': 49738, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [519, 576, 576, 519, 519], 'all_points_y': [384, 374, 408, 418, 384]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22798772_5437675018421986.jpg\n","{'filename': '22798772_5437675118662300.jpg', 'size': 58299, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [120, 121, 176, 176, 121], 'all_points_y': [368, 402, 415, 379, 368]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22798772_5437675118662300.jpg\n","{'filename': '22800904_5921360338950693.jpg', 'size': 16657, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [141, 231, 231, 140, 141], 'all_points_y': [178, 178, 195, 196, 178]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22800904_5921360338950693.jpg\n","{'filename': '22853059_6366680149928242.jpg', 'size': 65984, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [447, 560, 559, 446, 447], 'all_points_y': [415, 412, 435, 438, 415]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22853059_6366680149928242.jpg\n","{'filename': '22854180_6372343488739476.jpg', 'size': 17283, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [41, 97, 96, 40, 41], 'all_points_y': [172, 174, 191, 188, 172]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22854180_6372343488739476.jpg\n","{'filename': '22854467_6379524420692229.jpg', 'size': 22309, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [40, 81, 81, 40, 40], 'all_points_y': [174, 184, 199, 187, 174]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22854467_6379524420692229.jpg\n","{'filename': '22867139_6525486266926368.jpg', 'size': 68962, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [286, 460, 460, 285, 286], 'all_points_y': [388, 389, 419, 418, 388]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867139_6525486266926368.jpg\n","{'filename': '22867139_6525486502369306.jpg', 'size': 71605, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [93, 197, 200, 97, 93], 'all_points_y': [327, 348, 375, 353, 326]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867139_6525486502369306.jpg\n","{'filename': '22867139_6525486734628649.jpg', 'size': 74985, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [551, 638, 633, 547, 551], 'all_points_y': [342, 326, 349, 368, 342]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867139_6525486734628649.jpg\n","{'filename': '22867669_7628125929397472.jpg', 'size': 12605, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [75, 104, 104, 75, 75], 'all_points_y': [168, 169, 183, 182, 169]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22867669_7628125929397472.jpg\n","{'filename': '22876906_6882827826287234.jpg', 'size': 32332, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [284, 438, 439, 285, 285], 'all_points_y': [435, 435, 464, 465, 435]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22876906_6882827826287234.jpg\n","{'filename': '22877731_6784822717297546.jpg', 'size': 15748, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [165, 206, 206, 165, 165], 'all_points_y': [208, 208, 225, 226, 208]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22877731_6784822717297546.jpg\n","{'filename': '22878486_6789431365012443.jpg', 'size': 11757, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [102, 159, 159, 102, 102], 'all_points_y': [170, 170, 182, 182, 170]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22878486_6789431365012443.jpg\n","{'filename': '22901882_7128311537589833.jpg', 'size': 18037, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [58, 114, 115, 58, 57], 'all_points_y': [166, 185, 200, 180, 166]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22901882_7128311537589833.jpg\n","{'filename': '22902002_7131472262198416.jpg', 'size': 21071, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [155, 208, 208, 155, 155], 'all_points_y': [218, 218, 240, 240, 218]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22902002_7131472262198416.jpg\n","{'filename': '22902002_7131478147507051.jpg', 'size': 58419, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [74, 135, 143, 82, 74], 'all_points_y': [346, 367, 408, 383, 346]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22902002_7131478147507051.jpg\n","{'filename': '22903549_7139175246594729.jpg', 'size': 16090, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [40, 95, 95, 42, 41], 'all_points_y': [167, 172, 187, 181, 168]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22903549_7139175246594729.jpg\n","{'filename': '22903702_7140169948956332.jpg', 'size': 18618, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [61, 129, 129, 63, 62], 'all_points_y': [174, 180, 202, 195, 174]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22903702_7140169948956332.jpg\n","{'filename': '22909003_8872666968866685.jpg', 'size': 64138, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [298, 453, 453, 298, 299], 'all_points_y': [371, 372, 402, 401, 372]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22909003_8872666968866685.jpg\n","{'filename': '22909003_8872667142075785.jpg', 'size': 73661, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [109, 157, 157, 110, 109], 'all_points_y': [312, 335, 352, 329, 312]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22909003_8872667142075785.jpg\n","{'filename': '22911289_7381775810933651.jpg', 'size': 16443, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [296, 320, 320, 296, 296], 'all_points_y': [172, 166, 175, 180, 172]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22911289_7381775810933651.jpg\n","{'filename': '22918213_7479987932228958.jpg', 'size': 41701, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [513, 580, 580, 512, 513], 'all_points_y': [371, 345, 369, 396, 371]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22918213_7479987932228958.jpg\n","{'filename': '22918213_7479988077801989.jpg', 'size': 41527, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [251, 437, 436, 252, 251], 'all_points_y': [410, 410, 440, 441, 409]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22918213_7479988077801989.jpg\n","{'filename': '22928047_7644052088040167.jpg', 'size': 16182, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [145, 211, 210, 145, 145], 'all_points_y': [197, 198, 224, 223, 197]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22928047_7644052088040167.jpg\n","{'filename': '22929564_7660514277551917.jpg', 'size': 19290, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [302, 344, 342, 301, 302], 'all_points_y': [168, 147, 165, 187, 169]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22929564_7660514277551917.jpg\n","{'filename': '22929600_10059914292650849.jpg', 'size': 16701, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [146, 203, 203, 146, 146], 'all_points_y': [217, 216, 240, 241, 217]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': {}}\n","./carplate/train/22929600_10059914292650849.jpg\n","{'filename': '22934023_7741546994767615.jpg', 'size': 53940, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [140, 256, 256, 140, 140], 'all_points_y': [309, 309, 335, 335, 309]}, 'region_attributes': {'carplate': ''}}], 'file_attributes': 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{}}\n","./carplate/train/22237981_5834811804322674.jpg\n","\u001b[32m[05/24 07:38:25 d2.data.build]: \u001b[0mRemoved 0 images with no usable annotations. 100 images left.\n","\u001b[32m[05/24 07:38:25 d2.data.build]: \u001b[0mUsing training sampler TrainingSampler\n","\u001b[32m[05/24 07:38:25 d2.data.common]: \u001b[0mSerializing 100 elements to byte tensors and concatenating them all ...\n","\u001b[32m[05/24 07:38:25 d2.data.common]: \u001b[0mSerialized dataset takes 0.05 MiB\n"]},{"name":"stderr","output_type":"stream","text":["Skip loading parameter 'roi_heads.box_predictor.cls_score.weight' to the model due to incompatible shapes: (81, 1024) in the checkpoint but (2, 1024) in the model! You might want to double check if this is expected.\n","Skip loading parameter 'roi_heads.box_predictor.cls_score.bias' to the model due to incompatible shapes: (81,) in the checkpoint but (2,) in the model! You might want to double check if this is expected.\n","Skip loading parameter 'roi_heads.box_predictor.bbox_pred.weight' to the model due to incompatible shapes: (320, 1024) in the checkpoint but (4, 1024) in the model! You might want to double check if this is expected.\n","Skip loading parameter 'roi_heads.box_predictor.bbox_pred.bias' to the model due to incompatible shapes: (320,) in the checkpoint but (4,) in the model! You might want to double check if this is expected.\n","Skip loading parameter 'roi_heads.mask_head.predictor.weight' to the model due to incompatible shapes: (80, 256, 1, 1) in the checkpoint but (1, 256, 1, 1) in the model! You might want to double check if this is expected.\n","Skip loading parameter 'roi_heads.mask_head.predictor.bias' to the model due to incompatible shapes: (80,) in the checkpoint but (1,) in the model! You might want to double check if this is expected.\n","Some model parameters or buffers are not found in the checkpoint:\n","\u001b[34mroi_heads.box_predictor.bbox_pred.{bias, weight}\u001b[0m\n","\u001b[34mroi_heads.box_predictor.cls_score.{bias, weight}\u001b[0m\n","\u001b[34mroi_heads.mask_head.predictor.{bias, weight}\u001b[0m\n"]},{"name":"stdout","output_type":"stream","text":["\u001b[32m[05/24 07:38:26 d2.engine.train_loop]: \u001b[0mStarting training from iteration 0\n","\u001b[32m[05/24 07:38:29 d2.utils.events]: \u001b[0m eta: 0:00:44 iter: 19 total_loss: 1.477 loss_cls: 0.5807 loss_box_reg: 0.006199 loss_mask: 0.6898 loss_rpn_cls: 0.1692 loss_rpn_loc: 0.01011 time: 0.1397 data_time: 0.0128 lr: 1.6068e-05 max_mem: 1706M\n","\u001b[32m[05/24 07:38:32 d2.utils.events]: \u001b[0m eta: 0:00:42 iter: 39 total_loss: 1.272 loss_cls: 0.3941 loss_box_reg: 0.0005946 loss_mask: 0.6269 loss_rpn_cls: 0.2065 loss_rpn_loc: 0.01415 time: 0.1442 data_time: 0.0074 lr: 3.2718e-05 max_mem: 1706M\n","\u001b[32m[05/24 07:38:35 d2.utils.events]: \u001b[0m eta: 0:00:39 iter: 59 total_loss: 0.9398 loss_cls: 0.2212 loss_box_reg: 0.04074 loss_mask: 0.5513 loss_rpn_cls: 0.14 loss_rpn_loc: 0.01128 time: 0.1483 data_time: 0.0079 lr: 4.9367e-05 max_mem: 1707M\n","\u001b[32m[05/24 07:38:38 d2.utils.events]: \u001b[0m eta: 0:00:35 iter: 79 total_loss: 0.8582 loss_cls: 0.1815 loss_box_reg: 0.1284 loss_mask: 0.4427 loss_rpn_cls: 0.06258 loss_rpn_loc: 0.01087 time: 0.1463 data_time: 0.0080 lr: 6.6017e-05 max_mem: 1707M\n","\u001b[32m[05/24 07:38:41 d2.utils.events]: \u001b[0m eta: 0:00:32 iter: 99 total_loss: 0.9195 loss_cls: 0.1832 loss_box_reg: 0.1678 loss_mask: 0.3956 loss_rpn_cls: 0.03613 loss_rpn_loc: 0.008456 time: 0.1470 data_time: 0.0074 lr: 8.2668e-05 max_mem: 1707M\n","\u001b[32m[05/24 07:38:43 d2.utils.events]: \u001b[0m eta: 0:00:29 iter: 119 total_loss: 0.843 loss_cls: 0.1831 loss_box_reg: 0.2502 loss_mask: 0.3829 loss_rpn_cls: 0.02131 loss_rpn_loc: 0.008127 time: 0.1460 data_time: 0.0077 lr: 9.9318e-05 max_mem: 1707M\n","\u001b[32m[05/24 07:38:47 d2.utils.events]: \u001b[0m eta: 0:00:26 iter: 139 total_loss: 0.834 loss_cls: 0.166 loss_box_reg: 0.2825 loss_mask: 0.3462 loss_rpn_cls: 0.02732 loss_rpn_loc: 0.006115 time: 0.1473 data_time: 0.0081 lr: 0.00011597 max_mem: 1707M\n","\u001b[32m[05/24 07:38:50 d2.utils.events]: \u001b[0m eta: 0:00:23 iter: 159 total_loss: 0.8548 loss_cls: 0.1517 loss_box_reg: 0.3603 loss_mask: 0.2835 loss_rpn_cls: 0.02215 loss_rpn_loc: 0.005866 time: 0.1485 data_time: 0.0079 lr: 0.00013262 max_mem: 1707M\n","\u001b[32m[05/24 07:38:53 d2.utils.events]: \u001b[0m eta: 0:00:19 iter: 179 total_loss: 0.7634 loss_cls: 0.1383 loss_box_reg: 0.3619 loss_mask: 0.2238 loss_rpn_cls: 0.01783 loss_rpn_loc: 0.007453 time: 0.1492 data_time: 0.0069 lr: 0.00014927 max_mem: 1707M\n","\u001b[32m[05/24 07:38:56 d2.utils.events]: \u001b[0m eta: 0:00:16 iter: 199 total_loss: 0.659 loss_cls: 0.09698 loss_box_reg: 0.3198 loss_mask: 0.2085 loss_rpn_cls: 0.01233 loss_rpn_loc: 0.008613 time: 0.1505 data_time: 0.0080 lr: 0.00016592 max_mem: 1707M\n","\u001b[32m[05/24 07:38:59 d2.utils.events]: \u001b[0m eta: 0:00:13 iter: 219 total_loss: 0.6198 loss_cls: 0.0949 loss_box_reg: 0.3136 loss_mask: 0.1733 loss_rpn_cls: 0.01246 loss_rpn_loc: 0.006092 time: 0.1508 data_time: 0.0098 lr: 0.00018257 max_mem: 1707M\n","\u001b[32m[05/24 07:39:02 d2.utils.events]: \u001b[0m eta: 0:00:10 iter: 239 total_loss: 0.5016 loss_cls: 0.06723 loss_box_reg: 0.2627 loss_mask: 0.1359 loss_rpn_cls: 0.005651 loss_rpn_loc: 0.006371 time: 0.1519 data_time: 0.0079 lr: 0.00019922 max_mem: 1707M\n","\u001b[32m[05/24 07:39:06 d2.utils.events]: \u001b[0m eta: 0:00:06 iter: 259 total_loss: 0.3816 loss_cls: 0.06103 loss_box_reg: 0.1911 loss_mask: 0.1314 loss_rpn_cls: 0.005138 loss_rpn_loc: 0.007095 time: 0.1519 data_time: 0.0080 lr: 0.00021587 max_mem: 1707M\n","\u001b[32m[05/24 07:39:09 d2.utils.events]: \u001b[0m eta: 0:00:03 iter: 279 total_loss: 0.3771 loss_cls: 0.05061 loss_box_reg: 0.1706 loss_mask: 0.1349 loss_rpn_cls: 0.007446 loss_rpn_loc: 0.004511 time: 0.1527 data_time: 0.0075 lr: 0.00023252 max_mem: 1707M\n","\u001b[32m[05/24 07:39:13 d2.utils.events]: \u001b[0m eta: 0:00:00 iter: 299 total_loss: 0.3554 loss_cls: 0.05144 loss_box_reg: 0.1766 loss_mask: 0.1056 loss_rpn_cls: 0.005356 loss_rpn_loc: 0.005047 time: 0.1531 data_time: 0.0066 lr: 0.00024917 max_mem: 1707M\n","\u001b[32m[05/24 07:39:13 d2.engine.hooks]: \u001b[0mOverall training speed: 298 iterations in 0:00:45 (0.1531 s / it)\n","\u001b[32m[05/24 07:39:13 d2.engine.hooks]: \u001b[0mTotal training time: 0:00:46 (0:00:00 on hooks)\n"]},{"data":{"image/png":"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\n","text/plain":["<Figure size 1440x1440 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["train_data_loader = trainer.build_train_loader(cfg)\n","data_iter = iter(train_data_loader)\n","batch = next(data_iter)\n","\n","# visualization\n","import matplotlib.pyplot as plt\n","\n","rows, cols = 1, 2\n","plt.figure(figsize=(20,20))\n","\n","for i, per_image in enumerate(batch[:4]):\n"," \n"," plt.subplot(rows, cols, i+1)\n"," \n"," # Pytorch tensor is in (C, H, W) format\n"," img = per_image[\"image\"].permute(1, 2, 0).cpu().detach().numpy()\n"," img = utils.convert_image_to_rgb(img, cfg.INPUT.FORMAT)\n","\n"," #visualizer = Visualizer(img, metadata=chicken_metadata, scale=1.0)\n"," visualizer = Visualizer(img, metadata=carplate_metadata, scale=0.5)\n","\n"," target_fields = per_image[\"instances\"].get_fields()\n"," labels = None\n"," vis = visualizer.overlay_instances(\n"," labels=labels,\n"," boxes=target_fields.get(\"gt_boxes\", None),\n"," masks=target_fields.get(\"gt_masks\", None),\n"," keypoints=target_fields.get(\"gt_keypoints\", None),\n"," )\n"," plt.imshow(vis.get_image()[:, :, ::-1])\n","\n","trainer.resume_or_load(resume=False)\n","trainer.train()\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"JgcU0PIYwRH1"},"outputs":[],"source":["# Look at training curves in tensorboard:\n","# %load_ext tensorboard\n","# %tensorboard --logdir output"]},{"cell_type":"markdown","metadata":{"id":"i4oduarjy07V"},"source":["### Inference & evaluation using the trained model"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"UwVzPQH3wzjj"},"outputs":[],"source":["# Inference should use the config with parameters that are used in training\n","# cfg now already contains everything we've set previously. We changed it a little bit for inference:\n","cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, \"model_final.pth\") # path to the model we just trained\n","#cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, \"chery_chung_model.pth\")\n","#cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, \"chery_chung_makgok_model_2.pth\")\n","cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.7 # set a custom testing threshold\n","predictor = DefaultPredictor(cfg)"]},{"cell_type":"markdown","metadata":{"id":"8Ro5lyTKp8V9"},"source":[""]},{"cell_type":"markdown","metadata":{"id":"0odqVuMQwsDu"},"source":["# 이미지 calib(펴기)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"GJd3d4EFK-kW"},"outputs":[],"source":["import os, sys, subprocess, shlex, glob\n","import matplotlib.pyplot as plt\n","import cv2\n","from IPython.core.interactiveshell import InteractiveShell\n","\n","def calib_image(img_source):\n"," img = img_source.copy() \n"," #img = cv2.imread(os.path.join(image_dir, image_name))\n"," cent_x, cent_y = img.shape[:2]\n"," '''\n"," @ f_val : 1100 \n"," '''\n"," # 1100 , 1200\n","\n"," f_val = 1100.\n"," K = np.array([[f_val, 0.0, cent_y / 2], [0.0, f_val, cent_x / 2 ], [0., 0., 1.0]])\n"," D = np.array([0.04004325, 0.00112638, 0.01004722, -0.00593285])\n","\n"," map1, map2 = cv2.fisheye.initUndistortRectifyMap(K, D, np.eye(3), K, (cent_y, cent_x), cv2.CV_16SC2)\n"," newImg = cv2.remap(img, map1, map2, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)\n","\n"," return newImg"]},{"cell_type":"markdown","metadata":{"id":"AwtSY4Ts8ADg"},"source":["### 테스트"]},{"cell_type":"code","execution_count":10,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":312,"status":"ok","timestamp":1653381521767,"user":{"displayName":"조한별","userId":"01444879122726041884"},"user_tz":-540},"id":"iFOqe6yyaqeG","outputId":"d83f0e51-afca-478d-e3ae-2ebe2a9a2568"},"outputs":[{"output_type":"stream","name":"stdout","text":["파일 갯수 : 0\n"]}],"source":["from detectron2.utils.visualizer import ColorMode\n","import numpy as np\n","import detectron2.structures.instances as inss\n","import detectron2.structures.boxes as bbox\n","import pandas as pd\n","import math\n","import cv2\n","import heapq\n","import matplotlib.pyplot as plt\n","import warnings\n","warnings.filterwarnings('ignore')\n","\n","data_dir = './carplate/test/**'\n","FileList = glob.glob(data_dir + '/*.jpg', recursive=True)\n","img_namess = FileList\n","print(f'파일 갯수 : {len(img_namess)}')\n","\n","\n","cctv_pixel = []\n","for idx, d in enumerate(img_namess):\n"," try :\n"," print(idx, d)\n"," image_name = d.split('/')[-1]\n"," #print(idx, image_name)\n"," # if idx > 3:\n"," # break\n"," im = cv2.imread(d)\n"," if im is None : raise Exception('image not found')\n","\n","\n"," im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)\n"," #im = cv2.cvtColor(im, cv2.COLOR_RGB2BGR)\n"," \n"," outputs = predictor(im) # format is documented at https://detectron2.readthedocs.io/tutorials/models.html#model-output-format\n"," v = Visualizer(im[:, :, ::-1],\n"," metadata=carplate_metadata,\n"," scale=1.0,\n"," #instance_mode=ColorMode.IMAGE_BW # remove the colors of unsegmented pixels. This option is only available for segmentation models\n"," instance_mode=ColorMode.IMAGE\n"," )\n","\n"," output_cpu = outputs['instances'].to(\"cpu\")\n"," boxes = output_cpu.pred_boxes\n"," scores = output_cpu.scores\n"," pred_classes = output_cpu.pred_classes\n"," pred_masks = output_cpu.pred_masks\n","\n"," print(pred_masks)\n"," \n"," bound_xy = torch.tensor([0,0,pred_masks.shape[2],pred_masks.shape[1]])\n"," masks = torch.tensor([1,1,-1,-1])\n","\n"," \n"," out = v.draw_instance_predictions(output_cpu)\n","\n"," cv2_imshow(out.get_image()[:, :, ::-1])\n","\n"," #output_img = out.get_image()[:, :, ::-1].copy()\n","\n"," # plt_dir = out_dir + d[index2 : ]\n","\n"," # if not os.path.exists(plt_dir):\n"," # #print(\"-------------------------------------이미지를 저장합니다.--------------------------------------------\")\n"," # plt.imsave(plt_dir, output_img)\n"," # else:\n"," # print(\"-------------------------------기존에 이미지가 존재하여 덮어 씌우기로 저장합니다.-----------------------------\")\n"," # plt.imsave(plt_dir, output_img)\n","\n","\n"," except Exception as e :\n"," #df.loc[idx] = [date, d[index2 : ], 0, 0, 0]\n"," print(e)\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":102067,"status":"ok","timestamp":1644559218026,"user":{"displayName":"조한별","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"01444879122726041884"},"user_tz":-540},"id":"1REBrzO5qOAn","outputId":"2a75c993-2bc9-4a22-8731-937521d7e506"},"outputs":[{"name":"stdout","output_type":"stream","text":["0 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209000232_farm_image_real_6ed5808849da.jpg\n","x_mean or x_std is None \n","1 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209001731_farm_image_real_9f6742d94f7a.jpg\n","x_mean or x_std is None \n","2 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209000334_farm_image_real_2460f8fc4de3.jpg\n","pixel_list : [14534, 16011, 16555, 13921, 14631, 14173, 13893, 14671, 15212]\n","pixel_mean : 14845.0, pixel_count : 9\n","3 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209001836_farm_image_real_4021ce5f4816.jpg\n","pixel_list : [12844, 14628, 13955, 11587, 14740, 12230, 14340, 11873, 14081]\n","pixel_mean : 13364.0, pixel_count : 9\n","4 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209001940_farm_image_real_c6caa1ee4d9e.jpg\n","x_mean or x_std is None \n","5 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209000438_farm_image_real_36331b174b3e.jpg\n","pixel_list : [3423]\n","pixel_mean : 3423.0, pixel_count : 1\n","6 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209004732_farm_image_real_03e269634813.jpg\n","x_mean or x_std is None \n","7 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209004849_farm_image_real_8cc8b10047d8.jpg\n","pixel_list : [11771, 13041, 12892, 13765, 13595, 15215, 13911, 13067, 15560, 12461, 14782, 13320, 14100, 14657, 14616, 14809]\n","pixel_mean : 13848.0, pixel_count : 16\n","8 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209003231_farm_image_real_dc64b87a48e3.jpg\n","x_mean or x_std is None \n","9 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209003444_farm_image_real_815f90044e51.jpg\n","x_mean or x_std is None \n","10 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209003333_farm_image_real_4decd63543b2.jpg\n","pixel_list : [13979, 13739, 13087, 13862, 12792, 14314, 12480, 11977, 12853, 12127, 13136, 11866, 14792, 12615, 12240, 14337]\n","pixel_mean : 13137.0, pixel_count : 16\n","11 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209010338_farm_image_real_e2da71974bf1.jpg\n","pixel_list : [13182, 13595, 15047, 13546, 14028, 14058, 12839, 14223, 15340, 12543, 14979, 14958, 13370, 14670, 13790, 14228, 14717]\n","pixel_mean : 14065.0, pixel_count : 17\n","12 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209005005_farm_image_real_1d3c620041f8.jpg\n","x_mean or x_std is None \n","13 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209010451_farm_image_real_432767ff449e.jpg\n","x_mean or x_std is None \n","14 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209011851_farm_image_real_039fe9a44240.jpg\n","pixel_list : [13214, 13991, 12067, 15111, 13001, 13469, 12937, 13360]\n","pixel_mean : 13394.0, pixel_count : 8\n","15 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209010232_farm_image_real_8e1e97a04582.jpg\n","x_mean or x_std is None \n","16 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209011748_farm_image_real_c5e7cdf54ca9.jpg\n","x_mean or x_std is None \n","17 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209013231_farm_image_real_d9a6a9324037.jpg\n","x_mean or x_std is None \n","18 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209013333_farm_image_real_b35629ac4480.jpg\n","pixel_list : [15109, 14736, 14125, 13317, 13465, 13986, 12574, 12760, 14138]\n","pixel_mean : 13801.0, pixel_count : 9\n","19 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209014837_farm_image_real_69d2ea534296.jpg\n","pixel_list : [14688, 15167, 15020, 14152, 14711, 16186, 13641, 14357, 14383, 13853, 16119, 11644, 14311]\n","pixel_mean : 14479.0, pixel_count : 13\n","20 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209011953_farm_image_real_363441de4d30.jpg\n","x_mean or x_std is None \n","21 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209013438_farm_image_real_781090854a2a.jpg\n","x_mean or x_std is None \n","22 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209014735_farm_image_real_193c3d6d41d1.jpg\n","x_mean or x_std is None \n","23 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209020442_farm_image_real_d7fd36f44976.jpg\n","x_mean or x_std is None \n","24 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209020339_farm_image_real_1df7d4974add.jpg\n","pixel_list : [15388, 12929, 14073, 12749, 12439, 12998, 13334, 14005, 12552, 11816, 13091, 12324, 13806, 13244, 12308]\n","pixel_mean : 13137.0, pixel_count : 15\n","25 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209020237_farm_image_real_667b6b444e79.jpg\n","x_mean or x_std is None \n","26 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209021736_farm_image_real_bed0774d44b9.jpg\n","pixel_list : [3698]\n","pixel_mean : 3698.0, pixel_count : 1\n","27 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209014957_farm_image_real_a8d0bf684240.jpg\n","x_mean or x_std is None \n","28 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209024732_farm_image_real_612e53cb47df.jpg\n","pixel_list : [2636]\n","pixel_mean : 2636.0, pixel_count : 1\n","29 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209023452_farm_image_real_0245094d43c3.jpg\n","x_mean or x_std is None \n","30 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209023338_farm_image_real_3b2b061e4832.jpg\n","pixel_list : [14983, 15232, 13201, 13657, 15091, 15040, 14343, 12663, 13900, 11756]\n","pixel_mean : 13987.0, pixel_count : 10\n","31 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209023234_farm_image_real_d79f82b94d8e.jpg\n","pixel_list : [4424, 3740]\n","pixel_mean : 4082.0, pixel_count : 2\n","32 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209021844_farm_image_real_61b3a54d4b16.jpg\n","pixel_list : [14025, 13555, 13489, 14976, 14876, 13750, 14118, 11829, 12683, 12871, 13128]\n","pixel_mean : 13573.0, pixel_count : 11\n","33 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209031741_farm_image_real_04146e9f461e.jpg\n","x_mean or x_std is None \n","34 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209024939_farm_image_real_9dd200f24d2e.jpg\n","x_mean or x_std is None \n","35 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209030451_farm_image_real_1f3ecb5b4179.jpg\n","x_mean or x_std is None \n","36 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209024835_farm_image_real_fa5067e649bf.jpg\n","pixel_list : [15070, 12558, 14563, 13181, 13497, 13607, 13725, 13787, 13413]\n","pixel_mean : 13711.0, pixel_count : 9\n","37 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209030346_farm_image_real_595643f64eb6.jpg\n","pixel_list : [13633, 12635, 14950, 14440, 13889, 13205, 14155, 15690, 13603, 15643, 14330, 12986, 13723, 14444]\n","pixel_mean : 14095.0, pixel_count : 14\n","38 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209030243_farm_image_real_d3575c464568.jpg\n","x_mean or x_std is None \n","39 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209031847_farm_image_real_2c8649594c92.jpg\n","pixel_list : [12928, 12876, 12644, 14025, 15206, 15035, 14073, 16395, 14964, 13798, 13472, 14043, 14893, 13193, 13291]\n","pixel_mean : 14056.0, pixel_count : 15\n","40 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209033238_farm_image_real_2c2c037941f9.jpg\n","x_mean or x_std is None \n","41 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209032002_farm_image_real_6cff3a2b4122.jpg\n","x_mean or x_std is None \n","42 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209033452_farm_image_real_1cedccf34093.jpg\n","x_mean or x_std is None \n","43 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209033339_farm_image_real_e47aa0a14251.jpg\n","pixel_list : [14599, 14791, 14061, 13762, 15770, 12354, 13080, 12661, 14005, 12698, 13674, 11947, 13583, 13537, 13003, 15998, 13090, 13271, 12457, 13464, 14060, 14184, 14508, 14561, 12347]\n","pixel_mean : 13659.0, pixel_count : 25\n","44 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209040231_farm_image_real_fd2348b54db7.jpg\n","x_mean or x_std is None \n","45 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209034836_farm_image_real_75a30efa48f7.jpg\n","pixel_list : [14532, 15851, 12491, 15035, 14552, 13497, 16043, 14022, 15571, 14626, 15581]\n","pixel_mean : 14709.0, pixel_count : 11\n","46 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209034735_farm_image_real_8b693b1341c3.jpg\n","x_mean or x_std is None \n","47 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209034938_farm_image_real_1f23455c4648.jpg\n","x_mean or x_std is None \n","48 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209041959_farm_image_real_b4f57e984eae.jpg\n","x_mean or x_std is None \n","49 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209041853_farm_image_real_d6310c604934.jpg\n","pixel_list : [14996, 14341, 14499, 14375, 17288, 14776, 14805, 13846, 15071, 14666, 14228, 16379, 13054, 15302, 16713, 13979, 15008, 13713, 13785, 14329, 13050]\n","pixel_mean : 14676.0, pixel_count : 21\n","50 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209040332_farm_image_real_6de3a95a48c0.jpg\n","pixel_list : [14403, 14682, 14470, 12457, 14246, 14914, 13261, 14117, 15803, 12135, 13532, 12534, 12794, 14906, 13753, 11722, 13094]\n","pixel_mean : 13695.0, pixel_count : 17\n","51 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209041747_farm_image_real_066f2a6c43ec.jpg\n","pixel_list : [4066]\n","pixel_mean : 4066.0, pixel_count : 1\n","52 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209040435_farm_image_real_24802d534436.jpg\n","pixel_list : [4550]\n","pixel_mean : 4550.0, pixel_count : 1\n","53 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209044952_farm_image_real_ae6abc744926.jpg\n","pixel_list : [3423]\n","pixel_mean : 3423.0, pixel_count : 1\n","54 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209043334_farm_image_real_f86213de4c6c.jpg\n","pixel_list : [14884, 15366, 15569, 13325, 13982, 15946, 16486, 14420, 12292, 14317, 15813, 15310, 14859, 14425, 16678, 15305, 13987, 13563, 14319]\n","pixel_mean : 14781.0, pixel_count : 19\n","55 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209044743_farm_image_real_e4e6cb844ff3.jpg\n","x_mean or x_std is None \n","56 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209043232_farm_image_real_d45c75eb4499.jpg\n","x_mean or x_std is None \n","57 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209044847_farm_image_real_a263ba29481e.jpg\n","pixel_list : [15197, 15904, 15771, 12879, 14359, 13106, 12799, 11968, 14303, 14647, 13822]\n","pixel_mean : 14069.0, pixel_count : 11\n","58 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209043439_farm_image_real_1d0c43844737.jpg\n","x_mean or x_std is None \n","59 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209050231_farm_image_real_4be0a1724153.jpg\n","x_mean or x_std is None \n","60 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209050333_farm_image_real_ee850016400b.jpg\n","pixel_list : [14994, 12364, 12809, 14061, 15108, 12893, 13073, 14415, 13855, 14004, 12142, 12472, 12769]\n","pixel_mean : 13458.0, pixel_count : 13\n","61 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209051943_farm_image_real_6e9a755b4547.jpg\n","x_mean or x_std is None \n","62 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209050436_farm_image_real_b95d9bfa4f8c.jpg\n","x_mean or x_std is None \n","63 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209051739_farm_image_real_5168624a4dc4.jpg\n","x_mean or x_std is None \n","64 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209051841_farm_image_real_2431305a45ca.jpg\n","pixel_list : [13542, 13269, 13606, 13913, 13147, 14885, 14269, 14985, 14537, 13738, 13996, 14856, 12589]\n","pixel_mean : 13949.0, pixel_count : 13\n","65 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209054738_farm_image_real_5ea496f94850.jpg\n","x_mean or x_std is None \n","66 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209053446_farm_image_real_dbd549544619.jpg\n","x_mean or x_std is None \n","67 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209053241_farm_image_real_1cae9f974be9.jpg\n","pixel_list : [4596]\n","pixel_mean : 4596.0, pixel_count : 1\n","68 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209054955_farm_image_real_43827b18499f.jpg\n","x_mean or x_std is None \n","69 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209053343_farm_image_real_d5c31b2d4403.jpg\n","pixel_list : [12531, 13314, 15313, 13856, 14296, 12584, 12458, 13405, 13617, 12996, 14424, 12837, 14634, 14495, 13155, 15277, 14162, 13816]\n","pixel_mean : 13732.0, pixel_count : 18\n","70 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209054851_farm_image_real_364ee3414734.jpg\n","x_mean or x_std is None \n","71 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209060336_farm_image_real_9abe982c4b1e.jpg\n","pixel_list : [14987, 14766, 13517, 14260, 14338, 14370, 14632, 15708, 12708, 14485, 14627]\n","pixel_mean : 14400.0, pixel_count : 11\n","72 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209060233_farm_image_real_6f3b9af24e93.jpg\n","pixel_list : [4499]\n","pixel_mean : 4499.0, pixel_count : 1\n","73 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209061841_farm_image_real_3a2b50be430e.jpg\n","pixel_list : [12431, 13864, 13065, 12253, 14758, 13227, 14323, 11666, 13684, 12594, 12406, 13875, 13475, 13489, 14111, 13030]\n","pixel_mean : 13266.0, pixel_count : 16\n","74 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209060439_farm_image_real_ef56b6bc4220.jpg\n","pixel_list : [3671, 3164]\n","pixel_mean : 3418.0, pixel_count : 2\n","75 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209061943_farm_image_real_96f0ff71417f.jpg\n","x_mean or x_std is None \n","76 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209061738_farm_image_real_037894e145e3.jpg\n","x_mean or x_std is None \n","77 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209064940_farm_image_real_2049d82f438f.jpg\n","x_mean or x_std is None \n","78 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209063339_farm_image_real_1f2076c84f80.jpg\n","pixel_list : [12214, 13501, 15577, 12518, 13172, 14130, 14043, 15649, 11662, 13645, 14004, 12583, 11929, 12505, 13756, 12520, 13370]\n","pixel_mean : 13340.0, pixel_count : 17\n","79 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209063456_farm_image_real_68c7d13340a6.jpg\n","x_mean or x_std is None \n","80 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209063234_farm_image_real_308f7e0c4ba1.jpg\n","x_mean or x_std is None \n","81 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209064835_farm_image_real_b0c1f944450f.jpg\n","pixel_list : [16110, 14040, 14675, 14872, 13018, 15321, 12913, 14138, 13987, 14169, 12887, 13837, 13615, 16165, 13977, 14699, 16040]\n","pixel_mean : 14380.0, pixel_count : 17\n","82 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209064732_farm_image_real_c014235c4f85.jpg\n","pixel_list : [4051]\n","pixel_mean : 4051.0, pixel_count : 1\n","83 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209071953_farm_image_real_ba6281bc47d4.jpg\n","x_mean or x_std is None \n","84 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209070231_farm_image_real_0a52fd7546d0.jpg\n","pixel_list : [3959, 4470]\n","pixel_mean : 4214.0, pixel_count : 2\n","85 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209070437_farm_image_real_5f88472f4bf8.jpg\n","x_mean or x_std is None \n","86 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209071747_farm_image_real_35125cfb4c0a.jpg\n","x_mean or x_std is None \n","87 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209070333_farm_image_real_dc4e142a46ce.jpg\n","pixel_list : [15901, 14609, 13673, 13738, 14516, 13862, 13155, 15515, 13989, 15286, 13883, 14840, 15513, 15287, 12484, 15174, 13970, 13970]\n","pixel_mean : 14409.0, pixel_count : 18\n","88 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209071849_farm_image_real_7e82bb574cd5.jpg\n","pixel_list : [16092, 13741, 14020, 14158, 13823, 14253, 13116, 14144, 14315]\n","pixel_mean : 14185.0, pixel_count : 9\n","89 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209073456_farm_image_real_ac54b0fc4e84.jpg\n","x_mean or x_std is None \n","90 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209073246_farm_image_real_894edd324a1b.jpg\n","pixel_list : [2233, 2731]\n","pixel_mean : 2482.0, pixel_count : 2\n","91 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209073348_farm_image_real_eb64afcb498e.jpg\n","pixel_list : [12679, 12768, 12105, 11507, 11884, 15245, 12245, 12291, 12058, 13671, 11391, 11430]\n","pixel_mean : 12440.0, pixel_count : 12\n","92 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209074846_farm_image_real_4b3cdb9e460b.jpg\n","pixel_list : [15873, 13432, 14581, 12802, 15865, 15096, 12966, 15450, 12561, 16297, 12651, 14278, 12818, 14120, 13948, 15536]\n","pixel_mean : 14267.0, pixel_count : 16\n","93 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209074742_farm_image_real_b58be1ed461c.jpg\n","pixel_list : [4033, 3216]\n","pixel_mean : 3624.0, pixel_count : 2\n","94 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209080247_farm_image_real_332f2a5f46a1.jpg\n","x_mean or x_std is None \n","95 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209080452_farm_image_real_ead28f4b4141.jpg\n","x_mean or x_std is None \n","96 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209080350_farm_image_real_7dc4cf0e4a51.jpg\n","pixel_list : [16589, 13807, 14475, 14267, 13259, 12513, 13010, 15066, 15289, 14355, 14210, 14772, 16276, 13458, 12552, 13033, 11573]\n","pixel_mean : 14030.0, pixel_count : 17\n","97 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209081845_farm_image_real_98b7b0d54e35.jpg\n","pixel_list : [12609, 13315, 12866, 12096, 13196, 14780, 14131, 12773, 11816, 15114, 13724, 16574, 12935, 13118, 12770, 11407]\n","pixel_mean : 13326.0, pixel_count : 16\n","98 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209081741_farm_image_real_01b9b9564cb5.jpg\n","x_mean or x_std is None \n","99 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209074953_farm_image_real_c4d98374469b.jpg\n","pixel_list : [4274, 3442]\n","pixel_mean : 3858.0, pixel_count : 2\n","100 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209081948_farm_image_real_9f564ca84a25.jpg\n","x_mean or x_std is None \n","101 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209083232_farm_image_real_3f2c8e4a4b31.jpg\n","x_mean or x_std is None \n","102 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209083446_farm_image_real_706fd52e4e40.jpg\n","x_mean or x_std is None \n","103 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209083335_farm_image_real_327ca5bb4b57.jpg\n","pixel_list : [13050, 17434, 13727, 16287, 15661, 15793, 13146, 15250, 14698, 12543, 15766, 13441, 15434, 12875, 13057, 13250, 12289, 12925, 15001]\n","pixel_mean : 14296.0, pixel_count : 19\n","104 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209084741_farm_image_real_8b9de1554059.jpg\n","x_mean or x_std is None \n","105 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209091731_farm_image_real_e7e5407c43e3.jpg\n","x_mean or x_std is None \n","106 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209084843_farm_image_real_8f6157a24773.jpg\n","pixel_list : [16571, 15433, 13785, 14346, 14188, 16350, 13796, 13698, 14273, 14023, 12462]\n","pixel_mean : 14448.0, pixel_count : 11\n","107 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209084949_farm_image_real_bce439af4e50.jpg\n","x_mean or x_std is None \n","108 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209090237_farm_image_real_58501cb74395.jpg\n","x_mean or x_std is None \n","109 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209090340_farm_image_real_b86383034df3.jpg\n","pixel_list : [13176, 14010, 14223, 15030, 14247, 14963]\n","pixel_mean : 14275.0, pixel_count : 6\n","110 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209090443_farm_image_real_986b18ee4ae0.jpg\n","pixel_list : [4771]\n","pixel_mean : 4771.0, pixel_count : 1\n","111 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209093338_farm_image_real_182fac6f481e.jpg\n","pixel_list : [15141, 14830, 14211, 15351, 15335, 12720, 15955, 14118, 12826, 14121, 13651]\n","pixel_mean : 14387.0, pixel_count : 11\n","112 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209091939_farm_image_real_2f4499d84a18.jpg\n","x_mean or x_std is None \n","113 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209093233_farm_image_real_31c81bcb4154.jpg\n","x_mean or x_std is None \n","114 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209093442_farm_image_real_e6e40a0e43f8.jpg\n","x_mean or x_std is None \n","115 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209091836_farm_image_real_c8009bcc41b2.jpg\n","pixel_list : [12538, 14567, 13670, 14696, 12606, 13629, 13138, 12860, 13951, 13733, 12686, 13836, 13541, 13618, 14661, 11848, 14567, 12609]\n","pixel_mean : 13486.0, pixel_count : 18\n","116 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209100437_farm_image_real_2f3f7ccb4df3.jpg\n","x_mean or x_std is None \n","117 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209100233_farm_image_real_f1cc27994376.jpg\n","x_mean or x_std is None \n","118 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209094940_farm_image_real_b09eea604bab.jpg\n","x_mean or x_std is None \n","119 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209094838_farm_image_real_8d0eb978491a.jpg\n","pixel_list : [14867, 11622, 12388, 13858, 12938, 12489, 14608, 12985, 12965, 12314, 16176, 13404, 13857, 12387]\n","pixel_mean : 13347.0, pixel_count : 14\n","120 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209100335_farm_image_real_d40e9f88440e.jpg\n","pixel_list : [14323, 14665, 14714, 14616, 12965, 15989, 13858, 13138, 12766, 13246, 12561, 13172, 14398]\n","pixel_mean : 13878.0, pixel_count : 13\n","121 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209103345_farm_image_real_123608c045f5.jpg\n","pixel_list : [15398, 14776, 12706, 13956, 12780, 13903, 13606, 13043, 14174, 14542, 13821, 16240]\n","pixel_mean : 14079.0, pixel_count : 12\n","122 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209103450_farm_image_real_f4137ff14ccb.jpg\n","x_mean or x_std is None \n","123 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209101940_farm_image_real_3468255840f8.jpg\n","x_mean or x_std is None \n","124 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209103241_farm_image_real_90af5ae043bd.jpg\n","x_mean or x_std is None \n","125 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209101735_farm_image_real_7f135d444569.jpg\n","x_mean or x_std is None \n","126 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209104735_farm_image_real_97bf67524833.jpg\n","pixel_list : [3263, 3802]\n","pixel_mean : 3532.0, pixel_count : 2\n","127 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209101837_farm_image_real_c27c81ea48fb.jpg\n","pixel_list : [13365, 14798, 14804, 13683, 14356, 13583, 15997, 12328, 13762, 12168, 11439, 16510, 12798, 13384, 13722, 15268, 12254, 13069, 11182]\n","pixel_mean : 13604.0, pixel_count : 19\n","128 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209110454_farm_image_real_ac5710e145d5.jpg\n","x_mean or x_std is None \n","129 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209104839_farm_image_real_b796abcc41eb.jpg\n","pixel_list : [13116, 11003, 12486, 12965, 12898, 14410, 13082, 12909, 11801]\n","pixel_mean : 12741.0, pixel_count : 9\n","130 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209111735_farm_image_real_e93128984bf7.jpg\n","pixel_list : [4046]\n","pixel_mean : 4046.0, pixel_count : 1\n","131 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209110240_farm_image_real_749704e344ae.jpg\n","x_mean or x_std is None \n","132 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209110344_farm_image_real_3f78924e4354.jpg\n","pixel_list : [12984, 15529, 15509, 13810, 12619, 13026, 13370, 12428, 13257, 14008, 12510, 12582, 12903, 10495]\n","pixel_mean : 13216.0, pixel_count : 14\n","133 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209104944_farm_image_real_0832476244bb.jpg\n","x_mean or x_std is None \n","134 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209113233_farm_image_real_f20132f547c2.jpg\n","pixel_list : [4311, 5082]\n","pixel_mean : 4696.0, pixel_count : 2\n","135 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209114743_farm_image_real_beb0bcf94041.jpg\n","x_mean or x_std is None \n","136 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209114845_farm_image_real_836bccc34249.jpg\n","pixel_list : [14513, 13610, 14347, 14412, 14610, 16182, 13149, 13283, 14353, 14200, 14097, 12793, 13067]\n","pixel_mean : 14047.0, pixel_count : 13\n","137 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209111842_farm_image_real_7f409a5240d4.jpg\n","pixel_list : [13851, 13773, 12998, 13787, 13549, 14461, 14748, 14095, 13943, 11965, 13968, 12916, 14717, 12928, 13804]\n","pixel_mean : 13700.0, pixel_count : 15\n","138 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209113335_farm_image_real_2376dd754027.jpg\n","pixel_list : [14856, 15291, 14780, 13963, 14014, 14356, 16353, 13972, 14719, 14086, 12320, 16447]\n","pixel_mean : 14596.0, pixel_count : 12\n","139 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209113437_farm_image_real_a56afba9443a.jpg\n","x_mean or x_std is None \n","140 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209111947_farm_image_real_e4bfb8fe4f1a.jpg\n","pixel_list : [3899]\n","pixel_mean : 3899.0, pixel_count : 1\n","141 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209114959_farm_image_real_cf39bcda4487.jpg\n","pixel_list : [3226]\n","pixel_mean : 3226.0, pixel_count : 1\n","142 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209121835_farm_image_real_64d373ca4a02.jpg\n","pixel_list : [14250, 16118, 14335, 13718, 14857, 15112, 13868, 15731, 15520, 16337, 14715, 13865, 14482, 15752, 11874, 13407, 12469, 14719]\n","pixel_mean : 14507.0, pixel_count : 18\n","143 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209120452_farm_image_real_1750e78c4360.jpg\n","pixel_list : [3963]\n","pixel_mean : 3963.0, pixel_count : 1\n","144 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209121732_farm_image_real_c157fb8c4fb3.jpg\n","x_mean or x_std is None \n","145 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209120345_farm_image_real_e7be533549d4.jpg\n","pixel_list : [15418, 13889, 13699, 13869, 16620, 15747, 14412, 15177, 13620, 15943, 15256, 14283, 15020, 15370, 15342, 15787]\n","pixel_mean : 14966.0, pixel_count : 16\n","146 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209121942_farm_image_real_993ea17f4f48.jpg\n","x_mean or x_std is None \n","147 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209123358_farm_image_real_432011ea4ede.jpg\n","pixel_list : [14331, 12912, 13968, 12092, 12618, 13211, 14158, 11707, 14659, 11742]\n","pixel_mean : 13140.0, pixel_count : 10\n","148 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209123256_farm_image_real_4f69e8124aec.jpg\n","x_mean or x_std is None \n","149 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209124742_farm_image_real_1e92d3bc4b11.jpg\n","pixel_list : [4441]\n","pixel_mean : 4441.0, pixel_count : 1\n","150 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209124856_farm_image_real_15de2ae04f73.jpg\n","pixel_list : [12060, 13042, 13191, 13545, 12708, 14572, 14278, 11567, 13174, 13048]\n","pixel_mean : 13118.0, pixel_count : 10\n","151 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209123508_farm_image_real_6cf3d9e34ef1.jpg\n","x_mean or x_std is None \n","152 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209131733_farm_image_real_333b4c5d4fd3.jpg\n","pixel_list : [4117]\n","pixel_mean : 4117.0, pixel_count : 1\n","153 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209131847_farm_image_real_23c686024a81.jpg\n","pixel_list : [13496, 13675, 13032, 13921, 13614, 13535, 14152, 12601, 13957, 14691, 14092, 13997, 14575]\n","pixel_mean : 13795.0, pixel_count : 13\n","154 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209130239_farm_image_real_63ea11f04a59.jpg\n","pixel_list : [3198]\n","pixel_mean : 3198.0, pixel_count : 1\n","155 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209130354_farm_image_real_b729a5a84fa6.jpg\n","pixel_list : [13374, 13262, 12750, 10998, 17003, 13491, 15028, 15348, 15535, 15014, 15588]\n","pixel_mean : 14308.0, pixel_count : 11\n","156 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209130458_farm_image_real_1a96929b43f9.jpg\n","x_mean or x_std is None \n","157 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209125003_farm_image_real_93dce1be4e89.jpg\n","x_mean or x_std is None \n","158 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209133439_farm_image_real_513daf834b09.jpg\n","pixel_list : [3278]\n","pixel_mean : 3278.0, pixel_count : 1\n","159 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209134734_farm_image_real_fbd519b54076.jpg\n","x_mean or x_std is None \n","160 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209133231_farm_image_real_e1c16ffe43f3.jpg\n","x_mean or x_std is None \n","161 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209134847_farm_image_real_525546da4a76.jpg\n","pixel_list : [13792, 14155, 13713, 15339, 13294, 14150, 14715, 14052, 15607, 14402, 14027, 15220, 13616, 13411, 14212]\n","pixel_mean : 14247.0, pixel_count : 15\n","162 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209133333_farm_image_real_4860057d459d.jpg\n","pixel_list : [14685, 14131, 13043, 12827, 13815, 15655, 14900, 13887, 14839]\n","pixel_mean : 14198.0, pixel_count : 9\n","163 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209131951_farm_image_real_42c9cbb14eae.jpg\n","x_mean or x_std is None \n","164 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209140339_farm_image_real_0e68357747ea.jpg\n","pixel_list : [16076, 14127, 15194, 14463, 12255, 12510, 15287]\n","pixel_mean : 14273.0, pixel_count : 7\n","165 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209141837_farm_image_real_c815794b42fa.jpg\n","pixel_list : [12221, 15180, 14219, 14727, 13229, 13606]\n","pixel_mean : 13864.0, pixel_count : 6\n","166 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209141732_farm_image_real_03c793624f05.jpg\n","x_mean or x_std is None \n","167 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209134954_farm_image_real_6aa99065486f.jpg\n","x_mean or x_std is None \n","168 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209140232_farm_image_real_b5e13a5044cd.jpg\n","x_mean or x_std is None \n","169 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209140454_farm_image_real_029e4cb649fa.jpg\n","x_mean or x_std is None \n","170 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209143234_farm_image_real_5cf4276246fd.jpg\n","pixel_list : [3947]\n","pixel_mean : 3947.0, pixel_count : 1\n","171 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209143337_farm_image_real_be9f741a44ba.jpg\n","pixel_list : [12065, 14668, 13809, 15881, 14627, 13180, 14438, 10207, 15110, 12062, 12921]\n","pixel_mean : 13543.0, pixel_count : 11\n","172 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209144734_farm_image_real_32eeab334d44.jpg\n","pixel_list : [4632, 3333]\n","pixel_mean : 3982.0, pixel_count : 2\n","173 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209141945_farm_image_real_a7af78854113.jpg\n","x_mean or x_std is None \n","174 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209143446_farm_image_real_bd30fb034d29.jpg\n","pixel_list : [3793]\n","pixel_mean : 3793.0, pixel_count : 1\n","175 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209144838_farm_image_real_c300a1554333.jpg\n","pixel_list : [16217, 14183, 12844, 14558, 14263, 15055, 13552, 15141, 13364, 14299, 15267]\n","pixel_mean : 14431.0, pixel_count : 11\n","176 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209150342_farm_image_real_5c84e58d4042.jpg\n","pixel_list : [16428, 14240, 14934, 13657]\n","pixel_mean : 14815.0, pixel_count : 4\n","177 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209150238_farm_image_real_551ee929439e.jpg\n","x_mean or x_std is None \n","178 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209150446_farm_image_real_5e6059b5431d.jpg\n","pixel_list : [3880]\n","pixel_mean : 3880.0, pixel_count : 1\n","179 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209144942_farm_image_real_53aa04684183.jpg\n","x_mean or x_std is None \n","180 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209151837_farm_image_real_a5fb283e4539.jpg\n","pixel_list : [14108, 13330, 14299, 13686, 12834, 13838]\n","pixel_mean : 13682.0, pixel_count : 6\n","181 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209151734_farm_image_real_0a27b3124b89.jpg\n","x_mean or x_std is None \n","182 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209153337_farm_image_real_7bfd76d343fd.jpg\n","pixel_list : [15399, 12725, 14416, 14670, 16326, 12525, 14814, 16015, 14252, 11930]\n","pixel_mean : 14307.0, pixel_count : 10\n","183 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209154738_farm_image_real_81e14bb24c12.jpg\n","pixel_list : [3867, 4329]\n","pixel_mean : 4098.0, pixel_count : 2\n","184 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209153234_farm_image_real_23aec62c4bce.jpg\n","x_mean or x_std is None \n","185 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209151943_farm_image_real_f824abd5476f.jpg\n","pixel_list : [3453]\n","pixel_mean : 3453.0, pixel_count : 1\n","186 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209153451_farm_image_real_50b941734480.jpg\n","x_mean or x_std is None \n","187 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209160438_farm_image_real_a2845c13458f.jpg\n","x_mean or x_std is None \n","188 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209155000_farm_image_real_f5bb06c744c4.jpg\n","x_mean or x_std is None \n","189 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209160334_farm_image_real_d985f95e40b7.jpg\n","pixel_list : [14418, 14731, 12333, 13738, 12829, 13518, 15957, 15688, 16310, 14360, 12817, 15757, 13500, 14110, 12144]\n","pixel_mean : 14147.0, pixel_count : 15\n","190 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209154844_farm_image_real_cf04ea174a7b.jpg\n","pixel_list : [14329, 16635, 14909, 14572, 15326, 14408, 14438, 13762, 13907, 13901, 13119]\n","pixel_mean : 14482.0, pixel_count : 11\n","191 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209161743_farm_image_real_2d1ba1ca4749.jpg\n","x_mean or x_std is None \n","192 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209160232_farm_image_real_7680225e412a.jpg\n","pixel_list : [4436]\n","pixel_mean : 4436.0, pixel_count : 1\n","193 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209164743_farm_image_real_b629f8914bb5.jpg\n","x_mean or x_std is None \n","194 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209161950_farm_image_real_c6fd0d8f4bf3.jpg\n","pixel_list : [4568]\n","pixel_mean : 4568.0, pixel_count : 1\n","195 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209164844_farm_image_real_050b48b54a5a.jpg\n","pixel_list : [15075, 12857, 14607, 14382]\n","pixel_mean : 14230.0, pixel_count : 4\n","196 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209163339_farm_image_real_5055f69146ae.jpg\n","pixel_list : [13984, 13917, 13711, 15895, 15284, 13967, 15126, 12745]\n","pixel_mean : 14329.0, pixel_count : 8\n","197 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209163459_farm_image_real_9d628db144d5.jpg\n","x_mean or x_std is None \n","198 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209161845_farm_image_real_644172324ef2.jpg\n","pixel_list : [13161, 12117, 14467, 12695, 14461, 13073]\n","pixel_mean : 13329.0, pixel_count : 6\n","199 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209170458_farm_image_real_3130e1a74d9b.jpg\n","x_mean or x_std is None \n","200 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209170354_farm_image_real_d2f9d4384020.jpg\n","pixel_list : [13782, 14102, 13335, 11484, 13172]\n","pixel_mean : 13175.0, pixel_count : 5\n","201 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209164947_farm_image_real_20944d7d42e5.jpg\n","pixel_list : [736]\n","pixel_mean : 736.0, pixel_count : 1\n","202 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209170249_farm_image_real_a9262d634551.jpg\n","x_mean or x_std is None \n","203 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209173449_farm_image_real_2d755c354066.jpg\n","x_mean or x_std is None \n","204 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209173243_farm_image_real_99b1efb84df6.jpg\n","x_mean or x_std is None \n","205 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209171743_farm_image_real_2cad6016489d.jpg\n","pixel_list : [3232]\n","pixel_mean : 3232.0, pixel_count : 1\n","206 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209171955_farm_image_real_baeaac8b4ae4.jpg\n","x_mean or x_std is None \n","207 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209171852_farm_image_real_dbbd573c4966.jpg\n","pixel_list : [15528, 13419, 13178, 15530, 13968]\n","pixel_mean : 14325.0, pixel_count : 5\n","208 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209173346_farm_image_real_4c796d1d4c91.jpg\n","pixel_list : [15022, 15993, 14551, 15097, 14800, 15302, 12334, 13840, 13172, 15472]\n","pixel_mean : 14558.0, pixel_count : 10\n","209 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209175028_farm_image_real_dc62214d49ad.jpg\n","x_mean or x_std is None \n","210 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209180248_farm_image_real_c6389d354739.jpg\n","x_mean or x_std is None \n","211 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209180500_farm_image_real_a029b7f74f63.jpg\n","pixel_list : [4044]\n","pixel_mean : 4044.0, pixel_count : 1\n","212 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209174757_farm_image_real_10dceb124e94.jpg\n","x_mean or x_std is None \n","213 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209174916_farm_image_real_25b6ec4b4844.jpg\n","pixel_list : [16257, 16711, 16091, 13956, 16820, 11746, 15669]\n","pixel_mean : 15321.0, pixel_count : 7\n","214 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209181847_farm_image_real_c148b9b648b4.jpg\n","pixel_list : [16624, 14176, 12325, 12718, 16319, 15511, 14312, 11651, 13569, 17583, 14206, 15349, 12364, 15983, 17274, 14382, 12712]\n","pixel_mean : 14533.0, pixel_count : 17\n","215 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209183442_farm_image_real_016be6534744.jpg\n","x_mean or x_std is None \n","216 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209181953_farm_image_real_bfbbeb124410.jpg\n","x_mean or x_std is None \n","217 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209183237_farm_image_real_e31ffad94a9e.jpg\n","x_mean or x_std is None \n","218 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209183338_farm_image_real_a586f9b74cac.jpg\n","pixel_list : [13784, 14220, 15122, 15616, 14990, 15608, 14801, 14583]\n","pixel_mean : 14840.0, pixel_count : 8\n","219 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209181731_farm_image_real_48699a084384.jpg\n","x_mean or x_std is None \n","220 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209190234_farm_image_real_43627ad543d3.jpg\n","x_mean or x_std is None \n","221 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209190439_farm_image_real_fd4a1649426b.jpg\n","x_mean or x_std is None \n","222 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209184833_farm_image_real_2d6a8ecf45b0.jpg\n","pixel_list : [13690, 15093]\n","pixel_mean : 14392.0, pixel_count : 2\n","223 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209184935_farm_image_real_4b5784864e05.jpg\n","x_mean or x_std is None \n","224 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209190336_farm_image_real_9d5c65c84f18.jpg\n","pixel_list : [15356, 13695, 12073, 14336, 12891, 13929, 13810, 15640, 14662, 12180, 14270, 13071, 15179, 13171]\n","pixel_mean : 13876.0, pixel_count : 14\n","225 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209184731_farm_image_real_492be9874609.jpg\n","pixel_list : [4416]\n","pixel_mean : 4416.0, pixel_count : 1\n","226 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209193354_farm_image_real_a0c6443d4d39.jpg\n","pixel_list : [15497, 11809, 14300, 16458, 12659, 15194, 12838, 12729, 13355, 13386, 15012, 15899, 11859, 16088, 13610, 13450]\n","pixel_mean : 14009.0, pixel_count : 16\n","227 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209191937_farm_image_real_5e6fb4574505.jpg\n","pixel_list : [3854]\n","pixel_mean : 3854.0, pixel_count : 1\n","228 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209191834_farm_image_real_b185f68c4a80.jpg\n","pixel_list : [13680, 16073, 14738, 14844]\n","pixel_mean : 14834.0, pixel_count : 4\n","229 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209193233_farm_image_real_5a429ccf47ee.jpg\n","x_mean or x_std is None \n","230 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209191731_farm_image_real_110a3317472c.jpg\n","x_mean or x_std is None \n","231 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209200242_farm_image_real_f60945d84e94.jpg\n","pixel_list : [4586]\n","pixel_mean : 4586.0, pixel_count : 1\n","232 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209194955_farm_image_real_56f459bf4c67.jpg\n","x_mean or x_std is None \n","233 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209193458_farm_image_real_ddad56c54e08.jpg\n","x_mean or x_std is None \n","234 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209194835_farm_image_real_c881602f4add.jpg\n","pixel_list : [16387, 12691, 15034, 16152, 16922, 15503, 13539, 14611, 15309, 13614, 14093, 12561, 17503, 14938]\n","pixel_mean : 14918.0, pixel_count : 14\n","235 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209194734_farm_image_real_964e91584ec5.jpg\n","pixel_list : [4532, 3817]\n","pixel_mean : 4174.0, pixel_count : 2\n","236 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209200350_farm_image_real_3da59711410c.jpg\n","pixel_list : [15448, 15162, 14851, 13940, 13007, 13940, 15645, 13945, 13593, 15338, 13527, 16492, 12635]\n","pixel_mean : 14425.0, pixel_count : 13\n","237 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209200503_farm_image_real_d68e41f24c50.jpg\n","x_mean or x_std is None \n","238 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209203238_farm_image_real_d9e2d0bd4bb6.jpg\n","x_mean or x_std is None \n","239 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209203341_farm_image_real_d42212884e91.jpg\n","pixel_list : [15381, 16167, 14833, 16456, 15503, 13822, 15457, 14963, 14548]\n","pixel_mean : 15237.0, pixel_count : 9\n","240 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209201738_farm_image_real_36b3f12a4882.jpg\n","x_mean or x_std is None \n","241 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209201844_farm_image_real_c31e47d741aa.jpg\n","pixel_list : [15895, 14587, 14432, 13944, 15056, 14624, 16220, 17065, 14405, 15545, 14787, 16336, 12967, 13160, 14017, 13544, 14837, 14614, 13283, 14339, 14960, 14260, 14049, 15086, 11175, 12863, 13513]\n","pixel_mean : 14428.0, pixel_count : 27\n","242 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209203458_farm_image_real_5287146c4461.jpg\n","pixel_list : [3156]\n","pixel_mean : 3156.0, pixel_count : 1\n","243 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209210236_farm_image_real_40bb6d4c40ae.jpg\n","pixel_list : [4177]\n","pixel_mean : 4177.0, pixel_count : 1\n","244 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209210441_farm_image_real_bfb7183e410d.jpg\n","x_mean or x_std is None \n","245 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209204838_farm_image_real_d82852684dbc.jpg\n","pixel_list : [15598, 14694, 14795, 13261, 15538, 15454, 16143, 14818]\n","pixel_mean : 15038.0, pixel_count : 8\n","246 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209210338_farm_image_real_34a0183d4ece.jpg\n","pixel_list : [13787, 14418, 14386, 15434, 14140, 14657, 12177, 13335, 13108, 14083, 14333, 15768, 14294, 13162]\n","pixel_mean : 14077.0, pixel_count : 14\n","247 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209204736_farm_image_real_a5febfd0427e.jpg\n","x_mean or x_std is None \n","248 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209204951_farm_image_real_78b00b204e20.jpg\n","x_mean or x_std is None \n","249 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209211943_farm_image_real_80bdb3814a57.jpg\n","pixel_list : [3170]\n","pixel_mean : 3170.0, pixel_count : 1\n","250 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209211739_farm_image_real_f237065a4a42.jpg\n","pixel_list : [4463]\n","pixel_mean : 4463.0, pixel_count : 1\n","251 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209211841_farm_image_real_f70cc1b44c4a.jpg\n","pixel_list : [13779, 14794, 14632, 14038, 15103, 13863, 14344, 14705, 14226, 13224, 14199, 14166, 11568, 12423, 13191]\n","pixel_mean : 13884.0, pixel_count : 15\n","252 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209213231_farm_image_real_b4be468b43f1.jpg\n","x_mean or x_std is None \n","253 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209220232_farm_image_real_34bfa4934e78.jpg\n","pixel_list : [4473]\n","pixel_mean : 4473.0, pixel_count : 1\n","254 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209213440_farm_image_real_1c99ef8f46b0.jpg\n","x_mean or x_std is None \n","255 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209213337_farm_image_real_48c7539d49cc.jpg\n","pixel_list : [14619, 15836, 14291, 13459, 13615, 13503, 15401, 13270, 13062, 14946, 13298, 14237, 15166, 13167, 13382, 13800, 12870, 14406, 13935]\n","pixel_mean : 14014.0, pixel_count : 19\n","256 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209214841_farm_image_real_2fc518614fa6.jpg\n","pixel_list : [16112, 16071, 13929, 14214, 15463, 15046, 15342, 14537, 14015, 13103]\n","pixel_mean : 14783.0, pixel_count : 10\n","257 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209214738_farm_image_real_26d397914a62.jpg\n","pixel_list : [4573, 5029]\n","pixel_mean : 4801.0, pixel_count : 2\n","258 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209214953_farm_image_real_b82f50f7423b.jpg\n","x_mean or x_std is None \n","259 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209221839_farm_image_real_9c31eedc47d2.jpg\n","pixel_list : [15655, 15982, 14656, 13890, 17255, 17521, 14260, 14123, 15954, 16307, 15439, 16978, 15375, 14889, 16474, 15836, 13204, 15027, 13225, 16315, 14752, 15645, 13084]\n","pixel_mean : 15298.0, pixel_count : 23\n","260 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209220436_farm_image_real_0f5d5fa54286.jpg\n","pixel_list : [870]\n","pixel_mean : 870.0, pixel_count : 1\n","261 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209220334_farm_image_real_0f5d72184acc.jpg\n","pixel_list : [15460, 14371, 14059, 14370, 16606, 14003, 15449, 13493, 15942, 15172, 13311, 13480]\n","pixel_mean : 14643.0, pixel_count : 12\n","262 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209221941_farm_image_real_5ce863104ce6.jpg\n","x_mean or x_std is None \n","263 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209221735_farm_image_real_86953d034e34.jpg\n","pixel_list : [3944, 4215]\n","pixel_mean : 4080.0, pixel_count : 2\n","264 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209223343_farm_image_real_708c52eb4735.jpg\n","pixel_list : [15317, 14938, 16381, 12871, 15425]\n","pixel_mean : 14986.0, pixel_count : 5\n","265 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209223446_farm_image_real_f6a82868499d.jpg\n","x_mean or x_std is None \n","266 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209224833_farm_image_real_aa19cec84ab0.jpg\n","pixel_list : [14381, 15613, 15682, 13848, 14165, 16371, 14434, 15259, 14303]\n","pixel_mean : 14895.0, pixel_count : 9\n","267 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209223238_farm_image_real_fb56a6ec4fd5.jpg\n","pixel_list : [4554]\n","pixel_mean : 4554.0, pixel_count : 1\n","268 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209224732_farm_image_real_72ccbf6745bb.jpg\n","x_mean or x_std is None \n","269 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209224936_farm_image_real_d11640da4545.jpg\n","pixel_list : [4429]\n","pixel_mean : 4429.0, pixel_count : 1\n","270 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209231937_farm_image_real_3ade46ba4e04.jpg\n","pixel_list : [3907]\n","pixel_mean : 3907.0, pixel_count : 1\n","271 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209231731_farm_image_real_f30725be4f86.jpg\n","x_mean or x_std is None \n","272 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209230438_farm_image_real_3991abe54c14.jpg\n","x_mean or x_std is None \n","273 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209230334_farm_image_real_1614bd274991.jpg\n","pixel_list : [15786, 11927, 12220, 15382, 12941, 12300]\n","pixel_mean : 13426.0, pixel_count : 6\n","274 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209231833_farm_image_real_750293b84418.jpg\n","pixel_list : [15524, 15912, 13657, 13759, 15618, 13793, 14774, 13241, 13559, 14494, 15243]\n","pixel_mean : 14507.0, pixel_count : 11\n","275 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209233231_farm_image_real_4f7aa0c248e8.jpg\n","pixel_list : [4644]\n","pixel_mean : 4644.0, pixel_count : 1\n","276 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209233338_farm_image_real_ce8c20a24718.jpg\n","pixel_list : [14485, 11938, 16273, 14192, 15682, 15136, 13725, 11823, 14240, 12962, 14829, 14136, 13373, 14567, 13094]\n","pixel_mean : 14030.0, pixel_count : 15\n","277 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209233441_farm_image_real_458da2c3474c.jpg\n","x_mean or x_std is None \n","278 ./20210915/test4/FA0007_GW01_H03_CT10,10_20220209234734_farm_image_real_7268cea44e95.jpg\n","pixel_list : [4547, 3410]\n","pixel_mean : 3978.0, pixel_count : 2\n","279 ./20210915/test4/FA0007_GW01_H03_CT10,11_20220209234840_farm_image_real_5f4c810d4da6.jpg\n","pixel_list : [12837, 13528, 14229, 13743, 15838, 15685, 15681, 13281, 16685, 15390, 14248, 14724, 13393, 16033, 13182]\n","pixel_mean : 14565.0, pixel_count : 15\n","280 ./20210915/test4/FA0007_GW01_H03_CT10,12_20220209234943_farm_image_real_3f4f6604402a.jpg\n","pixel_list : [2845]\n","pixel_mean : 2845.0, pixel_count : 1\n","------------------------------------------------\n","2 14845.0\n","3 13364.0\n","5 3423.0\n","7 13848.0\n","10 13137.0\n"," ... \n","275 4644.0\n","276 14030.0\n","278 3978.0\n","279 14565.0\n","280 2845.0\n","Name: pixel_mean, Length: 149, dtype: float64\n"]}],"source":["# Inference should use the config with parameters that are used in training\n","# cfg now already contains everything we've set previously. We changed it a little bit for inference:\n","#cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, \"model_final.pth\") # path to the model we just trained\n","cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, \"model_final.pth\") # path to the model we just trained\n","cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.8 # set a custom testing threshold\n","predictor = DefaultPredictor(cfg)\n","\n","from detectron2.utils.visualizer import ColorMode\n","import numpy as np\n","import detectron2.structures.instances as inss\n","import detectron2.structures.boxes as bbox\n","import pandas as pd\n","import math\n","import cv2\n","import heapq\n","import matplotlib.pyplot as plt\n","import warnings\n","warnings.filterwarnings('ignore')\n","\n","data_dir = './20210915/test1/'\n","#data_dir = './20210915/makgok/20220106 (H01)/'\n","#out_dir = './20210915/makgok/20220114 (H01)/result/'\n","FileList = glob.glob(data_dir + '/*.jpg')\n","img_namess = FileList\n","\n","df = pd.DataFrame(columns=['date', 'image_name','pixel_mean', 'pixel_count', 'pixel_list'])\n","\n","def cv2_resize(img):\n"," height, width, chanel = img.shape\n"," #resize_img = calib_image[int(height/4) : int(3*height/4) , int(width/4) : int(3*width/4)].copy()\n"," resize_img = img[int(1.5* height/8) : int(4*height/8) , int(width/8) : int(4*width/8)].copy()\n"," return resize_img\n","\n","def cv2_crop(img, house_num):\n","\n"," height, width, chanel = img.shape\n"," \n"," if house_num == 'H01' : \n"," crop_img_left = img[int(2.8 * height/8) : int(4.8 * height/8) , int(0.4 * width/8) : int(1.6*width/8)].copy()\n"," crop_img_right = img[int(2.8 * height/8) : int(4.8 * height/8) , int(6.0 * width/8) : int(7.2*width/8)].copy()\n"," elif house_num == 'H02' :\n"," crop_img_left = img[int(2.5 * height/8) : int(4.5*height/8) , int(2.2*width/8) : int(3.4*width/8)].copy()\n"," crop_img_right = img[int(2.5 * height/8) : int(4.5*height/8) , int(5.2*width/8) : int(6.4*width/8)].copy()\n"," elif house_num == 'H03' :\n"," crop_img_left = img[int(4.5 * height/8) : int(6.5 * height/8) , int(0.8 * width/8) : int(2.0 * width/8)].copy()\n"," crop_img_right = img[int(5.9 * height/8) : int(7.9 * height/8) , int(6.4 * width/8) : int(7.6 * width/8)].copy()\n"," elif house_num == 'H04' :\n"," crop_img_left = img[int(4.4 * height/8) : int(6.4 * height/8) , int(0.01 * width/8) : int(1.21 * width/8)].copy()\n"," crop_img_right = img[int(5.8 * height/8) : int(7.8 * height/8) , int(4.9 * width/8) : int(6.1 * width/8)].copy()\n"," else :\n"," print(\"failed -----\")\n"," \n"," # print(crop_img_left.shape)\n"," # print(crop_img_right.shape)\n"," \n"," return crop_img_left, crop_img_right\n"," \n"," #crop_img = img[int(4 * height/8) : int(6.5*height/8) , 0 : int(width/8)].copy()\n"," \n"," #return crop_img_h4_right\n","\n","for idx, d in enumerate(img_namess):\n"," try :\n"," print(idx, d)\n"," if idx > 20:\n"," break\n"," im = cv2.imread(d)\n"," if im is None : raise Exception('image not found')\n"," #jpg_index = d.rfind('FA')\n"," #image_name = d[jpg_index:]\n"," #save = out_dir+image_name\n"," #plt.imsave(save, crop_img)\n"," #house_num = image_name.split('_')[2]\n"," #crop_img_left, crop_img_right = cv2_crop(im, house_num)\n"," \n"," # cv2_imshow(crop_img_left)\n"," # cv2_imshow(crop_img_right)\n"," # continue\n","\n"," # for i in range(0, 2) :\n"," # if i == 0:\n"," # print(\"Left Crop\")\n"," # crop_img = crop_img_left\n"," # else :\n"," # print(\"Right Crop\")\n"," # crop_img = crop_img_right\n"," # try :\n"," im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)\n"," \n"," outputs = predictor(im) # format is documented at https://detectron2.readthedocs.io/tutorials/models.html#model-output-format\n"," v = Visualizer(im[:, :, ::-1],\n"," metadata=chicken_metadata,\n"," scale=0.5,\n"," #instance_mode=ColorMode.IMAGE_BW # remove the colors of unsegmented pixels. This option is only available for segmentation models\n"," instance_mode=ColorMode.IMAGE\n"," )\n","\n"," output_cpu = outputs['instances'].to(\"cpu\")\n"," boxes = output_cpu.pred_boxes\n"," scores = output_cpu.scores\n"," pred_classes = output_cpu.pred_classes\n"," pred_masks = output_cpu.pred_masks\n"," \n"," bound_xy = torch.tensor([0,0,pred_masks.shape[2],pred_masks.shape[1]])\n"," masks = torch.tensor([1,1,-1,-1])\n"," bound_check = lambda x : all((bound_xy - x)*masks < -5) # margin : 5\n","\n"," num_of_interest = 40\n"," x_sum, x_std = [], 0.\n"," toggle_bound = []\n","\n"," for i,x in enumerate(boxes) :\n"," x1,y1,x2,y2 = x\n"," x_area = round(float((x2-x1) * (y2-y1)),1)\n"," x_sum.append(x_area)\n"," toggle_bound.append(bound_check(x))\n"," \n"," x_mean =np.mean(x_sum)\n"," x_std = np.std(x_sum)\n","\n"," if np.isnan(x_mean) or np.isnan(x_std):\n"," raise Exception('x_mean or x_std is None ')\n"," else:\n"," ind_toggle = [(x_mean - x_std <= x <= x_mean + x_std) for x in x_sum]\n"," ind_toggle = np.array(ind_toggle) & np.array(toggle_bound)\n"," ind_toggle = [ind_toggle[i] if sum(ind_toggle[:i]) < num_of_interest else False for i in range(len(ind_toggle))]\n","\n","\n"," # ind_toggle = [x_mean - x_std <= x <= x_mean + x_std for x in x_sum]\n","\n"," # # toggle join image boundary toggle\n"," # ind_toggle = np.array(ind_toggle) & np.array(toggle_bound)\n","\n"," # # num of interest \n"," # ind_toggle = [ind_toggle[i] if sum(ind_toggle[:i]) < num_of_interest else False for i in range(len(ind_toggle))]\n","\n"," total_sum = torch.sum(pred_masks, (1,2))[ind_toggle]\n","\n"," total_mean = torch.round(torch.sum(total_sum) / len(total_sum)).item()\n"," total_count = len(total_sum)\n","\n"," pixel_sum = torch.sum(pred_masks, (1,2))[ind_toggle]\n"," pixel_mean = torch.round(torch.sum(pixel_sum) / len(pixel_sum)).item()\n"," pixel_count = int(sum(ind_toggle))\n"," print(f'pixel_list : {total_sum.tolist()}')\n"," print(f'pixel_mean : {pixel_mean}, pixel_count : {pixel_count}')\n"," # print(pixel_mean)\n"," ####\n"," # choose distortion(dist_toggle) or no_distortion(no_dist_toggle) or all(ind_toggle)\n"," final_toggle = ind_toggle\n"," \n"," # draw circle\n"," output_boxs = output_cpu[final_toggle].pred_boxes\n"," box_centers = output_boxs.get_centers()\n"," \n"," ### counts\n","\n"," #print(f'total detection counts : {len(output_cpu)}')\n"," #print(f'boundary check : {sum(toggle_bound)}')\n"," #print(f'mean,std check : {sum([x_mean - x_std <= x <= x_mean + x_std for x in x_sum])}')\n"," #print(f'finally : {sum(final_toggle)}')\n"," \n"," index1 = d.rfind('2022')\n"," index2 = d.rfind('H')\n"," date = d[index1: index1 +14]\n"," \n"," df.loc[idx] = [date, d[index2 : ], pixel_mean, pixel_count, total_sum.tolist()]\n"," \n"," # print(date)\n"," # print(d[index2 : ])\n"," # print(pixel_mean)\n"," out = v.draw_instance_predictions(output_cpu[final_toggle])\n","\n"," #cv2_imshow(out.get_image()[:, :, ::-1])\n"," #output_img = out.get_image()[:, :, ::-1].copy()\n","\n"," # plt_dir = out_dir + d[index2 : ]\n","\n"," # if not os.path.exists(plt_dir):\n"," # #print(\"-------------------------------------이미지를 저장합니다.--------------------------------------------\")\n"," # plt.imsave(plt_dir, output_img)\n"," # else:\n"," # print(\"-------------------------------기존에 이미지가 존재하여 덮어 씌우기로 저장합니다.-----------------------------\")\n"," # plt.imsave(plt_dir, output_img)\n","\n","\n"," except Exception as e :\n"," #df.loc[idx] = [date, d[index2 : ], 0, 0, 0]\n"," print(e)\n","\n","csv_filename = '산수 2022-02-10(makgok).csv'\n","print('------------------------------------------------')\n","print(df['pixel_mean'])\n","if not os.path.exists(csv_filename):\n"," df.to_csv(csv_filename, index=False, columns=['date', 'image_name','pixel_mean', 'pixel_count', 'pixel_list'],encoding='utf-8')\n","else :\n"," df.to_csv(csv_filename, index=False, columns=['date', 'image_name','pixel_mean', 'pixel_count', 'pixel_list'],encoding='utf-8')\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"dlX0FvJzy9kr"},"outputs":[],"source":["from detectron2.utils.visualizer import ColorMode\n","dataset_dicts = get_chicken_dicts(\"./20211014/val\")\n","for d in random.sample(dataset_dicts, 3): \n"," im = cv2.imread(d[\"file_name\"])\n"," outputs = predictor(im) # format is documented at https://detectron2.readthedocs.io/tutorials/models.html#model-output-format\n"," v = Visualizer(im[:, :, ::-1],\n"," metadata=chicken_metadata, \n"," scale=0.5, \n"," instance_mode=ColorMode.IMAGE_BW # remove the colors of unsegmented pixels. This option is only available for segmentation models\n"," )\n"," out = v.draw_instance_predictions(outputs[\"instances\"].to(\"cpu\"))\n"," cv2_imshow(out.get_image()[:, :, ::-1])"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":93,"status":"ok","timestamp":1631776920398,"user":{"displayName":"전규빈","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"01278177497556326253"},"user_tz":-540},"id":"-3h10vZuzClq","outputId":"fed0294b-c3cb-40ea-d13b-3eaf8414c397"},"outputs":[{"name":"stdout","output_type":"stream","text":["\u001b[32m[09/16 07:21:02 d2.evaluation.coco_evaluation]: \u001b[0m'chicken_val' is not registered by `register_coco_instances`. Therefore trying to convert it to COCO format ...\n","\u001b[5m\u001b[31mWARNING\u001b[0m \u001b[32m[09/16 07:21:02 d2.data.datasets.coco]: \u001b[0mUsing previously cached COCO format annotations at './output/chicken_val_coco_format.json'. You need to clear the cache file if your dataset has been modified.\n","{'filename': 'FA0002_GW01_H01_0002_20210901154447_farm_image_real_4d377d82.jpg', 'size': 3084870, 'regions': [{'shape_attributes': {'name': 'polyline', 'all_points_x': [1470, 1473, 1466, 1473, 1492, 1512, 1513, 1505, 1497, 1492, 1489, 1484, 1474], 'all_points_y': [422, 433, 454, 482, 495, 474, 435, 417, 396, 406, 404, 417, 423]}, 'region_attributes': {'chicken': ''}}, {'shape_attributes': {'name': 'polyline', 'all_points_x': [1611, 1604, 1598, 1586, 1585, 1573, 1573, 1581, 1575, 1581, 1593, 1593, 1601, 1609, 1614], 'all_points_y': [469, 488, 508, 500, 487, 466, 430, 422, 418, 404, 418, 422, 435, 453, 464]}, 'region_attributes': {'chicken': ''}}, {'shape_attributes': {'name': 'polyline', 'all_points_x': [1727, 1716, 1716, 1723, 1718, 1719, 1732, 1739, 1753, 1763, 1763, 1766, 1753, 1749, 1734], 'all_points_y': [839, 856, 874, 884, 889, 895, 895, 882, 879, 855, 835, 818, 814, 830, 837]}, 'region_attributes': 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{'shape_attributes': {'name': 'polyline', 'all_points_x': [1884, 1887, 1893, 1913, 1917, 1919, 1924, 1924, 1931, 1923, 1909, 1904, 1906, 1897, 1891, 1888, 1882, 1885, 1888, 1885], 'all_points_y': [1286, 1295, 1307, 1299, 1302, 1303, 1291, 1285, 1270, 1259, 1248, 1251, 1256, 1252, 1246, 1252, 1250, 1261, 1268, 1277]}, 'region_attributes': {'chicken': ''}}, {'shape_attributes': {'name': 'polyline', 'all_points_x': [1470, 1483, 1483, 1472, 1453, 1442, 1427, 1421, 1414, 1417, 1427, 1436, 1435, 1462, 1468], 'all_points_y': [1373, 1373, 1353, 1339, 1335, 1338, 1340, 1337, 1343, 1355, 1359, 1366, 1374, 1385, 1378]}, 'region_attributes': {'chicken': ''}}, {'shape_attributes': {'name': 'polyline', 'all_points_x': [1220, 1228, 1220, 1230, 1233, 1254, 1257, 1259, 1248, 1234, 1222], 'all_points_y': [156, 170, 187, 212, 217, 209, 189, 176, 169, 160, 154]}, 'region_attributes': {'chicken': ''}}], 'file_attributes': {}}\n","./20210915/val/FA0002_GW01_H01_0002_20210901154447_farm_image_real_4d377d82.jpg\n","dict_keys(['shape_attributes', 'region_attributes'])\n","\u001b[32m[09/16 07:21:04 d2.data.build]: \u001b[0mDistribution of instances among all 1 categories:\n","\u001b[36m| category | #instances |\n","|:----------:|:-------------|\n","| chicken | 89 |\n","| | |\u001b[0m\n","\u001b[32m[09/16 07:21:04 d2.data.dataset_mapper]: \u001b[0m[DatasetMapper] Augmentations used in inference: [ResizeShortestEdge(short_edge_length=(800, 800), max_size=1333, sample_style='choice')]\n","\u001b[32m[09/16 07:21:04 d2.data.common]: \u001b[0mSerializing 1 elements to byte tensors and concatenating them all ...\n","\u001b[32m[09/16 07:21:04 d2.data.common]: \u001b[0mSerialized dataset takes 0.03 MiB\n","\u001b[32m[09/16 07:21:04 d2.evaluation.evaluator]: \u001b[0mStart inference on 1 batches\n","\u001b[32m[09/16 07:21:07 d2.evaluation.evaluator]: \u001b[0mInference done 1/1. Dataloading: 0.0000 s/iter. Inference: 0.7280 s/iter. Eval: 1.8046 s/iter. Total: 2.5326 s/iter. ETA=0:00:00\n","\u001b[32m[09/16 07:21:07 d2.evaluation.evaluator]: \u001b[0mTotal inference time: 0:00:02.613932 (2.613932 s / iter per device, on 1 devices)\n","\u001b[32m[09/16 07:21:07 d2.evaluation.evaluator]: \u001b[0mTotal inference pure compute time: 0:00:00 (0.728006 s / iter per device, on 1 devices)\n","\u001b[32m[09/16 07:21:08 d2.evaluation.coco_evaluation]: \u001b[0mPreparing results for COCO format ...\n","\u001b[32m[09/16 07:21:08 d2.evaluation.coco_evaluation]: \u001b[0mSaving results to ./output/coco_instances_results.json\n","\u001b[32m[09/16 07:21:09 d2.evaluation.coco_evaluation]: \u001b[0mEvaluating predictions with unofficial COCO API...\n","Loading and preparing results...\n","DONE (t=0.00s)\n","creating index...\n","index created!\n","\u001b[32m[09/16 07:21:09 d2.evaluation.fast_eval_api]: \u001b[0mEvaluate annotation type *bbox*\n","\u001b[32m[09/16 07:21:09 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.evaluate() finished in 0.01 seconds.\n","\u001b[32m[09/16 07:21:09 d2.evaluation.fast_eval_api]: \u001b[0mAccumulating evaluation results...\n","\u001b[32m[09/16 07:21:09 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.accumulate() finished in 0.00 seconds.\n"," Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000\n"," Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000\n"," Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000\n"," Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000\n"," Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000\n"," Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000\n","\u001b[32m[09/16 07:21:09 d2.evaluation.coco_evaluation]: \u001b[0mEvaluation results for bbox: \n","| AP | AP50 | AP75 | APs | APm | APl |\n","|:-----:|:------:|:------:|:-----:|:-----:|:-----:|\n","| 0.000 | 0.000 | 0.000 | nan | nan | 0.000 |\n","\u001b[32m[09/16 07:21:09 d2.evaluation.coco_evaluation]: \u001b[0mSome metrics cannot be computed and is shown as NaN.\n","Loading and preparing results...\n","DONE (t=0.00s)\n","creating index...\n","index created!\n","\u001b[32m[09/16 07:21:09 d2.evaluation.fast_eval_api]: \u001b[0mEvaluate annotation type *segm*\n","\u001b[32m[09/16 07:21:09 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.evaluate() finished in 0.02 seconds.\n","\u001b[32m[09/16 07:21:09 d2.evaluation.fast_eval_api]: \u001b[0mAccumulating evaluation results...\n","\u001b[32m[09/16 07:21:09 d2.evaluation.fast_eval_api]: \u001b[0mCOCOeval_opt.accumulate() finished in 0.00 seconds.\n"," Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000\n"," Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000\n"," Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000\n"," Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000\n"," Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000\n"," Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000\n"," Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000\n","\u001b[32m[09/16 07:21:09 d2.evaluation.coco_evaluation]: \u001b[0mEvaluation results for segm: \n","| AP | AP50 | AP75 | APs | APm | APl |\n","|:-----:|:------:|:------:|:-----:|:-----:|:-----:|\n","| 0.000 | 0.000 | 0.000 | nan | nan | 0.000 |\n","\u001b[32m[09/16 07:21:09 d2.evaluation.coco_evaluation]: \u001b[0mSome metrics cannot be computed and is shown as NaN.\n","OrderedDict([('bbox', {'AP': 0.0, 'AP50': 0.0, 'AP75': 0.0, 'APs': nan, 'APm': nan, 'APl': 0.0}), ('segm', {'AP': 0.0, 'AP50': 0.0, 'AP75': 0.0, 'APs': nan, 'APm': nan, 'APl': 0.0})])\n"]}],"source":["from detectron2.evaluation import COCOEvaluator, inference_on_dataset\n","from detectron2.data import build_detection_test_loader\n","evaluator = COCOEvaluator(\"chicken_val\", output_dir=\"./output\")\n","val_loader = build_detection_test_loader(cfg, \"chicken_val\")\n","print(inference_on_dataset(predictor.model, val_loader, evaluator))\n","# another equivalent way to evaluate the model is to use `trainer.test`"]}],"metadata":{"accelerator":"GPU","colab":{"collapsed_sections":[],"name":"detectron2_LPR_detect.ipynb","provenance":[{"file_id":"1wPLZYIxKnhFDeJPjHEMGNy1-gH_EuDwf","timestamp":1631078560271}]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}