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//paip/script/lpr/detectron2_LPR/lpr_test.py

import subprocess
import time
import os, sys, glob
import detectron2_lpd_inference
import recog_demo
import detectron2_lpr_inference
import flask
from flask import request, jsonify
from flask_cors import CORS
from dateutil.parser import parse
from collections import deque, Counter
import pandas as pd
import uuid
import matplotlib.pyplot as plt
from datetime import datetime
import cv2
from PIL import ImageFont, ImageDraw, Image
import numpy as np
import shutil
import cnn_lpr_inference

# set sys path to import PyDBconnector
#HOME_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), os.pardir)
HOME_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)))
MODULE_DIR = 'util'
sys.path.append(os.path.join(HOME_PATH, MODULE_DIR))
from PyDBconnector import PyDBconnector

def lpr_detecting():
    df = pd.DataFrame(columns=['IMAGE_NAME', 'DATE', 'LPR_RESULT', 'TYPE'])
    # 이미지 경로 설정
    data_dir = "/gate/data/test_dataset"
    FileList = glob.glob(data_dir + '/*.jpg', recursive=True)
    img_namess = FileList
    print(f'파일 갯수 : {len(img_namess)}')

for idx, d in enumerate(img_namess):
        # if idx >=40 :
        #     break
        print(f"<<<<<<<<<<<<<<<<<<<<<<<< {idx} >>>>>>>>>>>>>>>>>>>>>>>>>>")
        # print("numnber = ", idx)
        start_time = time.time()
        # image_name = d.split("/")[-1]
        # image_dir = d.split("/")[:]
        image_dir, image_name = os.path.split(d)

if image_dir[-1] != "/":
            image_dir = image_dir + "/"

image_time = parse(image_name.split("_")[2][:-3])

print('날짜 및 시간 : ', image_time)
        print('이미지 경로 :', image_dir)
        print('이미지 이름 :', image_name)

# detection = detectron2_lpd_inference.LicensePlate_Detector.getInstance()
        # recognition = detectron2_lpr_inference.LicensePlate_Recognition.getInstance()
        # recog = recog_demo.Recognition.getInstance()

try:
            # Detection
            start = time.time()
            lpd_result, out_img, license_plate_type = detection.Predict_LPD(image_dir, image_name)
            end = time.time()
            print("번호 Detection 시간 : " + f"{end - start:.5f} sec")

# Recognition
            start1 = time.time()
            lpr_result = recognition.Predict_LPR(lpd_result)
            lpr_result = lpr_result[0]
            # recog.recog(lpd_result)
            end1 = time.time()
            print("번호 Recog 시간 : " + f"{end1 - start1:.5f} sec   번호 결과 : {lpr_result}     번호판 종류 : {license_plate_type}")

df.loc[idx] = [image_name, image_time, lpr_result, license_plate_type]

###########################
            # 예측한 결과 이미지 저장
            out_img_copy = out_img.get_image()[:, :, ::-1].copy()
            # img = np.full(shape=(512, 512, 3), fill_value=255, dtype=np.uint8)
            img = Image.fromarray(out_img_copy)
            draw = ImageDraw.Draw(img)
            font = ImageFont.truetype("/usr/share/fonts/NanumFont/NanumMyeongjoExtraBold.ttf", 40, encoding="UTF-8")
            #font = ImageFont.truetype("~/usr/share/fonts/nhn-nanum/NanumGothicExtraBold.ttf", 40, encoding="UTF-8")
            org = (50, 100)
            draw.text(org, lpr_result, font=font, fill=(0, 0, 0))
            out_img_put_text = np.array(img)

# numpy_img = np.array(out_img_put_text).copy()
            # cv_img = cv2.cvtColor(numpy_img, cv2.COLOR_RGB2BGR)

# out_img_puttext = cv2.putText(img, lpr_result, (350, 40), cv2.FONT_HERSHEY_PLAIN, 2, (0, 0, 0), 1, cv2.LINE_4)
            size, BaseLine = cv2.getTextSize(lpr_result, cv2.FONT_HERSHEY_SIMPLEX, 2, 4)
            cv2.rectangle(out_img_put_text, org, (org[0] + size[0], org[1] + size[1]), (0, 0, 0))
            cv2.circle(out_img_put_text, org, 3, (255, 0, 255), 2)

jpg_index = image_name.rfind('.jpg')
            plt_image = image_name[0:jpg_index] + "_lprDetectionResult.jpg"
            plt_dir = image_dir + 'result'

try:
                os.makedirs(plt_dir)
            except OSError:
                if not os.path.isdir(plt_dir):
                    raise

save_dir = plt_dir + '/' + plt_image

# 원본 이미지 복사
            shutil.copyfile(image_dir+image_name, plt_dir+"/"+image_name)

# result 이미지 저장
            plt.imsave(save_dir, out_img_put_text)

except Exception as e:
            print(e)
        end_time = time.time()

print(f"<<<< detect_result finish {end_time - start_time:.5f} sec >>>>")
    print(df)
    df.to_csv('lpr_result.csv', index=False, columns=['IMAGE_NAME', 'DATE', 'LPR_RESULT', 'TYPE'], encoding='utf-8-sig')

if __name__ == '__main__':
    print('-------------------- LPR model loading ---------------------')
    detection = detectron2_lpd_inference.LicensePlate_Detector.getInstance()
    #recognition = detectron2_lpr_inference.LicensePlate_Recognition.getInstance()
    recognition = cnn_lpr_inference.LicensePlate_Recognition.getInstance()
    #dbConn = PyDBconnector()

lpr_detecting()