'''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 np.size(hr) == 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