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Running
on
Zero
File size: 2,854 Bytes
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import cv2
import numpy as np
def saturate_weaken_HSV(img, severity=1):
"""
Saturate Weaken by scaling S channel in HSV.
severity=[1, 2, 3, 4, 5] corresponding to scale=[0.7, 0.55, 0.4, 0.2, 0.0].
severity mainly refer to KADID-10K.
@param img: Input image, H x W x 3, value range [0, 255]
@param severity: Severity of distortion, [1, 5]
@return: Degraded image, H x W x 3, value range [0, 255]
"""
c = [0.7, 0.55, 0.4, 0.2, 0.0][severity - 1]
hsv = np.array(cv2.cvtColor(img, cv2.COLOR_RGB2HSV), dtype=np.float32)
hsv[:, :, 1] = c * hsv[:, :, 1]
hsv = np.uint8(np.clip(hsv, 0, 255))
img = cv2.cvtColor(hsv, cv2.COLOR_HSV2RGB)
return img
def saturate_weaken_YCrCb(img, severity=1):
"""
Saturate Weaken by scaling S channel in YCrCb.
severity=[1, 2, 3, 4, 5] corresponding to scale=[0.6, 0.4, 0.2, 0.1, 0.0].
severity mainly refer to PieAPP.
@param img: Input image, H x W x 3, value range [0, 255]
@param severity: Severity of distortion, [1, 5]
@return: Degraded image, H x W x 3, value range [0, 255]
"""
c = [0.6, 0.4, 0.2, 0.1, 0.0][severity - 1]
ycrcb = np.array(cv2.cvtColor(img, cv2.COLOR_RGB2YCR_CB), dtype=np.float32)
ycrcb[:, :, 1] = 128 + (ycrcb[:, :, 1] - 128) * c
ycrcb[:, :, 2] = 128 + (ycrcb[:, :, 2] - 128) * c
ycrcb = np.uint8(np.clip(ycrcb, 0, 255))
img = cv2.cvtColor(ycrcb, cv2.COLOR_YCR_CB2RGB)
return img
def saturate_strengthen_HSV(img, severity=1):
"""
Saturate Strengthen by scaling S channel in HSV.
severity=[1, 2, 3, 4, 5] corresponding to scale=[3.0, 6.0, 12.0, 20.0, 64.0].
@param img: Input image, H x W x 3, value range [0, 255]
@param severity: Severity of distortion, [1, 5]
@return: Degraded image, H x W x 3, value range [0, 255]
"""
c = [3.0, 6.0, 12.0, 20.0, 64.0][severity - 1]
hsv = np.array(cv2.cvtColor(img, cv2.COLOR_RGB2HSV), dtype=np.float32)
hsv[:, :, 1] = c * hsv[:, :, 1]
hsv = np.uint8(np.clip(hsv, 0, 255))
img = cv2.cvtColor(hsv, cv2.COLOR_HSV2RGB)
return img
def saturate_strengthen_YCrCb(img, severity=1):
"""
Saturate Strengthen by scaling S channel in YCrCb.
severity=[1, 2, 3, 4, 5] corresponding to scale=[2.0, 3.0, 5.0, 8.0, 16.0].
severity mainly refer to PieAPP.
@param img: Input image, H x W x 3, value range [0, 255]
@param severity: Severity of distortion, [1, 5]
@return: Degraded image, H x W x 3, value range [0, 255]
"""
c = [2.0, 3.0, 5.0, 8.0, 16.0][severity - 1]
ycrcb = np.array(cv2.cvtColor(img, cv2.COLOR_RGB2YCR_CB), dtype=np.float32)
ycrcb[:, :, 1] = 128 + (ycrcb[:, :, 1] - 128) * c
ycrcb[:, :, 2] = 128 + (ycrcb[:, :, 2] - 128) * c
ycrcb = np.uint8(np.clip(ycrcb, 0, 255))
img = cv2.cvtColor(ycrcb, cv2.COLOR_YCR_CB2RGB)
return img
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