def random_color(tensor, p=.5):
'''
brightness_factor (Union[float, torch.Tensor]) – Brightness adjust factor per element in the batch.
0 does not modify the input image while any other number modify the brightness.
contrast_factor (Union[float, torch.Tensor]) – Contrast adjust factor per element in the batch.
0 generates a compleatly black image,
1 does not modify the input image while any other non-negative number modify the brightness by this factor.
hue_factor (float):0 means no shift. Therefore,
both -PI and PI will give an image with complementary colors while 0 gives the original image.
saturation_factor (float) – How much to adjust the saturation. 0 will give a black
order=0 is brightness, 1 is contrast, 2 is saturation, 4 is hue.
'''
gamma = torch.ones(tensor.shape[1])
gamma = np.random.uniform(0.75, 1.25)
random_number = np.random.uniform()
if random_number < p:
for i in range(tensor.shape[0]):
tensor[i] = kornia.adjust_gamma(tensor[i], gamma)
# hue=torch.ones(tensor.shape[1])
# hue=np.random.uniform(-0.4,0.4)
# random_number=np.random.uniform()
# if random_number<p:
# for i in range(tensor.shape[0]):
# tensor[i]=kornia.adjust_hue(tensor[i],hue)
# contrast=torch.ones(tensor.shape[1])
# contrast=np.random.uniform(0.6,1.4)
# random_number=np.random.uniform()
# if random_number<p:
# for i in range(tensor.shape[0]):
# tensor[i]=kornia.adjust_contrast(tensor[i],contrast)
#
# brightness=torch.ones(tensor.shape[1])
# brightness=np.random.uniform(-0.4,0.4)
# random_number=np.random.uniform()
# if random_number<p:
# for i in range(tensor.shape[0]):
# tensor[i]=kornia.adjust_brightness(tensor[i],brightness)
return tensor
def Gamma(x, alpha, beta):
# alpha (1.0, 3.0), beta (1.0, 3.0)
return kornia.adjust_gamma(x, gamma=alpha, gain=beta)
############################# # Show original imshow(x_rgb) ############################# # Adjust Brightness x_brightness: torch.Tensor = kornia.adjust_brightness(x_rgb, 0.6) imshow(x_brightness) ############################# # Adjust Contrast x_contrast: torch.Tensor = kornia.adjust_contrast(x_rgb, 0.2) imshow(x_contrast) ############################# # Adjust Gamma x_gamma: torch.Tensor = kornia.adjust_gamma(x_rgb, gamma=3., gain=1.5) imshow(x_gamma) ############################# # Adjust Saturation x_saturated: torch.Tensor = kornia.adjust_saturation(x_rgb, 0.2) imshow(x_saturated) ############################# # Adjust Hue x_hue: torch.Tensor = kornia.adjust_hue(x_rgb, 0.5) imshow(x_hue)
def Gamma(x, v):
return kornia.adjust_gamma(x, v)