# 将图片编码成rle格式
from torchvision.transforms import transforms
def rle_encode(img, min_max_threshold=1e-3, max_mean_threshold=None):
    if np.max(img) < min_max_threshold:
        return ''  
    if max_mean_threshold and np.mean(img) > max_mean_threshold:
        return ''  
    pixels = img.T.flatten()
    pixels = np.concatenate([[0], pixels, [0]])
    runs = np.where(pixels[1:] != pixels[:-1])[0] + 1
    runs[1::2] -= runs[::2]
    return ' '.join(str(x) for x in runs)


# 将rle格式进行解码为图片
def rle_decode(mask_rle, shape=(512, 512)):
    s = mask_rle.split()
    starts, lengths = [np.asarray(x, dtype=int) for x in (s[0:][::2], s[1:][::2])]
    starts -= 1
    ends = starts + lengths
    img = np.zeros(shape[0] * shape[1], dtype=np.uint8)
    for lo, hi in zip(starts, ends):
        img[lo:hi] = 1
    return img.reshape(shape, order='F')