def forward(self, x):
if self.filter_type == 'Median_Filter':
x_denoised = kornia.median_blur(x, (self.ksize, self.ksize))
elif self.filter_type == 'Mean_Filter':
x_denoised = kornia.box_blur(x, (self.ksize, self.ksize))
elif self.filter_type == 'Gaussian_Filter':
x_denoised = kornia.gaussian_blur2d(
x, (self.ksize, self.ksize),
(0.3 * ((x.shape[3] - 1) * 0.5 - 1) + 0.8, 0.3 *
((x.shape[2] - 1) * 0.5 - 1) + 0.8))
new_x = x + self.conv(x_denoised)
return new_x
def forward(self, x):
if self.filter_type == 'Median_Filter':
x_denoised = kornia.median_blur(x, (self.ksize, self.ksize))
elif self.filter_type == 'Mean_Filter':
x_denoised = kornia.box_blur(x, (self.ksize, self.ksize))
elif self.filter_type == 'Gaussian_Filter':
x_denoised = kornia.gaussian_blur2d(
x, (self.ksize, self.ksize),
(0.3 * ((x.shape[3] - 1) * 0.5 - 1) + 0.8, 0.3 *
((x.shape[2] - 1) * 0.5 - 1) + 0.8))
elif self.filter_type == "NonLocal_Filter":
x_denoised = self.non_local_op(x, self.embed, self.softmax)
new_x = x + self.conv_1x1(x_denoised)
return new_x
def main():
try:
img_bgr: np.ndarray = cv2.imread('model8.png', cv2.IMREAD_COLOR)
x_bgr: torch.Tensor = kornia.image_to_tensor(img_bgr)
x_rgb: torch.Tensor = kornia.bgr_to_rgb(x_bgr)
x_rgb = x_rgb.expand(2, -1, -1, -1)
x_rgb = x_rgb.float() / 255.
imshow(x_rgb)
# Box Blur
x_blur: torch.Tensor = kornia.box_blur(x_rgb, (9, 9))
imshow(x_blur)
# Median Blur
x_blur: torch.Tensor = kornia.median_blur(x_rgb, (5, 5))
imshow(x_blur)
# Gaussian Blur
x_blur: torch.Tensor = kornia.gaussian_blur2d(x_rgb, (11, 11), (11., 11.))
imshow(x_blur)
except:
print("Error found")
# Create batch and normalize
x_rgb = x_rgb.expand(2, -1, -1, -1) # 4xCxHxW
x_rgb = x_rgb.float() / 255.
def imshow(input: torch.Tensor):
out: torch.Tensor = torchvision.utils.make_grid(input, nrow=2, padding=1)
out_np: np.array = kornia.tensor_to_image(out)
plt.imshow(out_np)
plt.axis('off')
#############################
# Show original
imshow(x_rgb)
#############################
# Box Blur
x_blur: torch.Tensor = kornia.box_blur(x_rgb, (9, 9))
imshow(x_blur)
#############################
# Media Blur
x_blur: torch.Tensor = kornia.median_blur(x_rgb, (5, 5))
imshow(x_blur)
#############################
# Gaussian Blur
x_blur: torch.Tensor = kornia.gaussian_blur2d(x_rgb, (11, 11), (11., 11.))
imshow(x_blur)