rl-network-train.py 文件源码

def preprocess_images(images):
    if images.shape[0] < 4:
        # single image
        x_t = images[0]
        x_t = imresize(x_t, (80, 80))
        x_t = x_t.astype("float")
        x_t /= 255.0
        s_t = np.stack((x_t, x_t, x_t, x_t), axis=2)
    else:
        # 4 images
        xt_list = []
        for i in range(images.shape[0]):
            x_t = imresize(images[i], (80, 80))
            x_t = x_t.astype("float")
            x_t /= 255.0
            xt_list.append(x_t)
        s_t = np.stack((xt_list[0], xt_list[1], xt_list[2], xt_list[3]), 
                       axis=2)
    s_t = np.expand_dims(s_t, axis=0)
    return s_t