Spaces:
Runtime error
Runtime error
File size: 1,398 Bytes
06f26d7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 |
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# Power by Zongsheng Yue 2022-08-19 10:00:39
import cv2
import numpy as np
from basicsr.data import degradations as degradations
from utils import util_common
def face_degradation(im, sf, sig_x, sig_y, theta, nf, qf):
'''
Face degradation on testing data
Input:
im: numpy array, h x w x c, [0, 1], bgr
sf: scale factor for super-resolution
sig_x, sig_y, theta: parameters for generating gaussian kernel
nf: noise level
qf: quality factor for jpeg compression
Output:
im_lq: numpy array, h x w x c, [0, 1], bgr
'''
h, w = im.shape[:2]
# blur
kernel = degradations.bivariate_Gaussian(
kernel_size=41,
sig_x=sig_x,
sig_y=sig_y,
theta=theta,
isotropic=False,
)
im_lq = cv2.filter2D(im, -1, kernel)
# downsample
im_lq = cv2.resize(im_lq, (int(w // sf), int(h // sf)), interpolation=cv2.INTER_LINEAR)
# noise
im_lq = degradations.add_gaussian_noise(im_lq, sigma=nf, clip=True, rounds=False)
# jpeg compression
im_lq = degradations.add_jpg_compression(im_lq, quality=qf)
# resize to original size
im_lq = cv2.resize(im_lq, (w, h), interpolation=cv2.INTER_LINEAR)
# round and clip
im_lq = np.clip((im_lq * 255.0).round(), 0, 255) / 255.
return im_lq
|