import time

import cv2
import torch

import detect_with_API

cap = cv2.VideoCapture(r'D:\Downloads\Video\1080p.mp4')  # 0
DETECT_API = detect_with_API.detectapi(weights='models/yolov7.pt')
init_data = {
    'debug': False
}

def run_time(fun):
    def wrapper(*args, **kwargs):
        t1 = time.time()
        ret_val = fun(*args, **kwargs)
        t2 = time.time()
        print('Time elapsed was: {}'.format(t2 - t1))
        return ret_val

    return wrapper


def detect_video(video_file):
    # 视频检测
    cap = cv2.VideoCapture(video_file)
    rec, img = cap.read()
    result, names = a.detect([img])
    img = result[0][0]  # 每一帧图片的处理结果图片
    # 每一帧图像的识别结果（可包含多个物体）
    for cls, (x1, y1, x2, y2), conf in result[0][1]:
        print(names[cls], x1, y1, x2, y2, conf)  # 识别物体种类、左上角x坐标、左上角y轴坐标、右下角x轴坐标、右下角y轴坐标，置信度
        '''
        cv2.rectangle(img,(x1,y1),(x2,y2),(0,255,0))
        cv2.putText(img,names[cls],(x1,y1-20),cv2.FONT_HERSHEY_DUPLEX,1.5,(255,0,0))'''
    print()  # 将每一帧的结果输出分开
    cv2.imshow("vedio", img)

    if cv2.waitKey(1) == ord('q'):
        break


def detect_img(ImgPath):
    images = cv2.imread(ImgPath + '\\' + img_name)
    images, result = DETECT_API.detect(images)


def debug_detect():
    pass


if __name__ == '__main__':
    with torch.no_grad():
        while True:
            rec, img = cap.read()
            result, names = a.detect([img])
            img = result[0][0]  # 每一帧图片的处理结果图片
            # 每一帧图像的识别结果（可包含多个物体）
            for cls, (x1, y1, x2, y2), conf in result[0][1]:
                print(names[cls], x1, y1, x2, y2, conf)  # 识别物体种类、左上角x坐标、左上角y轴坐标、右下角x轴坐标、右下角y轴坐标，置信度
                '''
                cv2.rectangle(img,(x1,y1),(x2,y2),(0,255,0))
                cv2.putText(img,names[cls],(x1,y1-20),cv2.FONT_HERSHEY_DUPLEX,1.5,(255,0,0))'''
            print()  # 将每一帧的结果输出分开
            cv2.imshow("vedio", img)

            if cv2.waitKey(1) == ord('q'):
                break