def DataIOStream(raw_src: Flow):
return (raw_src.Filter(
lambda x: x.endswith('.jpg')) # select jpg files/选取jpg格式文件
.Map(lambda x: os.path.join(train_dir, x)) # 拿到ground truth数据
.Map(data.imread).Map(lambda im: [
im, mixed_noise(im),
gaussian_noise(im),
poisson_noise(im)
] | infix / Map @ img_as_float).Map(to_batch))
def DataIOStream(raw_src: Flow):
return (raw_src.Filter(
lambda x: x.endswith('.jpg')) # select jpg files/选取jpg格式文件
.Map(lambda x: [os.path.join(train_dir, x)] + [
os.path.join(test_dir, x[:-4] + "_" + str(i) + '.jpg')
for i in range(1, 3)
]) # 将噪声数据和真实数据进行合并
.Map(lambda img_file_names: list(
map(
and_then(
data.imread, # 读取图像
img_as_float), # 浮点数张量 [0, 255]->[0, 1]
img_file_names))).Map(to_batch))