predict_frames.py 文件源码

def read_video(self):

        vid = cv2.VideoCapture(self.video_path)

        if vid.isOpened():

            frame_count = int(vid.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))
            self.predictions = np.zeros((frame_count,100,100,3))#need to know frame size
            for count in xrange(frame_count):
                ret,frame = vid.read() #probably don't want to get every frame
                processed_frame = self.process_frame(frame)
                self.predictions[count] = processed_frame
            vid.release()
        else:
            print 'unable to open file: {}'.format(file_str)


    #maybe should separate this algo, or somehow automatically detect what the model accepts
    #should probably convert to float32, divide by 255.