cnn_predict.py 文件源码

def readImg(FileList, data_shape):
    mat = []
    tmp = 0
    ret = len(FileList)/(NUM_SAMPLES+1)
    for i in range(ret):
        for j in range(NUM_SAMPLES):
        index = i * (NUM_SAMPLES+1) + j    
            img_1 = cv2.imread(FileList[index], 0)
            img_11 = cv2.resize(img_1, (data_shape[2], data_shape[1]))
            img_111 = np.multiply(img_11, 1/255.0)
            img_2 = cv2.imread(FileList[index+1], 0)
            img_22 = cv2.resize(img_2, (data_shape[2], data_shape[1]))
            img_222 = np.multiply(img_22, 1/255.0)
        flow = cv2.calcOpticalFlowFarneback(img_111, img_222, 0.5, 3, 15, 3, 5, 1.2, 0)
        flow = np.array(flow)
            flow_1 = flow.transpose((2,1,0))
        flow_1 = flow_1.tolist()
        mat.append(flow_1)
    return mat