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- '''metrics'''
- # Copyright 2021 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
- import math
- import numpy as np
-
-
- def quantize(img, rgb_range):
- '''metrics'''
- pixel_range = 255 / rgb_range
- img = np.multiply(img, pixel_range)
- img = np.clip(img, 0, 255)
- img = np.round(img) / pixel_range
- return img
-
-
- def calc_psnr(sr, hr, scale, rgb_range, y_only=False, dataset=None):
- '''metrics'''
- hr = np.float32(hr)
- sr = np.float32(sr)
- diff = (sr - hr) / rgb_range
- gray_coeffs = np.array([65.738, 129.057, 25.064]
- ).reshape((1, 3, 1, 1)) / 256
- diff = np.multiply(diff, gray_coeffs).sum(1)
- if hr.size == 1:
- return 0
- if scale != 1:
- shave = scale
- else:
- shave = scale + 6
- if scale == 1:
- valid = diff
- else:
- valid = diff[..., shave:-shave, shave:-shave]
- mse = np.mean(pow(valid, 2))
- return -10 * math.log10(mse)
-
-
- def rgb2ycbcr(img, y_only=True):
- '''metrics'''
- img.astype(np.float32)
- if y_only:
- rlt = np.dot(img, [65.481, 128.553, 24.966]) / 255.0 + 16.0
- return rlt
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