#-------------------------------------#
#   调用摄像头或者视频进行检测
#   调用摄像头直接运行即可
#   调用视频可以将cv2.VideoCapture()指定路径
#   视频的保存并不难，可以百度一下看看
#-------------------------------------#
import time

import cv2
import numpy as np
from keras.layers import Input
from PIL import Image

from yolo import YOLO

yolo = YOLO()
#-------------------------------------#
#   调用摄像头
#   capture=cv2.VideoCapture("1.mp4")
#-------------------------------------#
capture=cv2.VideoCapture(0)

fps = 0.0
while(True):
    t1 = time.time()
    # 读取某一帧
    ref,frame=capture.read()
    # 格式转变，BGRtoRGB
    frame = cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
    # 转变成Image
    frame = Image.fromarray(np.uint8(frame))
    # 进行检测
    frame = np.array(yolo.detect_image(frame))
    # RGBtoBGR满足opencv显示格式
    frame = cv2.cvtColor(frame,cv2.COLOR_RGB2BGR)
    
    fps  = ( fps + (1./(time.time()-t1)) ) / 2
    print("fps= %.2f"%(fps))
    frame = cv2.putText(frame, "fps= %.2f"%(fps), (0, 40), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
    
    cv2.imshow("video",frame)
    c= cv2.waitKey(1) & 0xff 
    if c==27:
        capture.release()
        break

yolo.close_session()