Browse Source

Make Blur node use the image device for processing.

pull/1228/head
comfyanonymous 1 year ago
parent
commit
94fceb8700
  1. 6
      comfy_extras/nodes_post_processing.py

6
comfy_extras/nodes_post_processing.py

@ -59,8 +59,8 @@ class Blend:
def g(self, x): def g(self, x):
return torch.where(x <= 0.25, ((16 * x - 12) * x + 4) * x, torch.sqrt(x)) return torch.where(x <= 0.25, ((16 * x - 12) * x + 4) * x, torch.sqrt(x))
def gaussian_kernel(kernel_size: int, sigma: float): def gaussian_kernel(kernel_size: int, sigma: float, device=None):
x, y = torch.meshgrid(torch.linspace(-1, 1, kernel_size), torch.linspace(-1, 1, kernel_size), indexing="ij") x, y = torch.meshgrid(torch.linspace(-1, 1, kernel_size, device=device), torch.linspace(-1, 1, kernel_size, device=device), indexing="ij")
d = torch.sqrt(x * x + y * y) d = torch.sqrt(x * x + y * y)
g = torch.exp(-(d * d) / (2.0 * sigma * sigma)) g = torch.exp(-(d * d) / (2.0 * sigma * sigma))
return g / g.sum() return g / g.sum()
@ -101,7 +101,7 @@ class Blur:
batch_size, height, width, channels = image.shape batch_size, height, width, channels = image.shape
kernel_size = blur_radius * 2 + 1 kernel_size = blur_radius * 2 + 1
kernel = gaussian_kernel(kernel_size, sigma).repeat(channels, 1, 1).unsqueeze(1) kernel = gaussian_kernel(kernel_size, sigma, device=image.device).repeat(channels, 1, 1).unsqueeze(1)
image = image.permute(0, 3, 1, 2) # Torch wants (B, C, H, W) we use (B, H, W, C) image = image.permute(0, 3, 1, 2) # Torch wants (B, C, H, W) we use (B, H, W, C)
padded_image = F.pad(image, (blur_radius,blur_radius,blur_radius,blur_radius), 'reflect') padded_image = F.pad(image, (blur_radius,blur_radius,blur_radius,blur_radius), 'reflect')

Loading…
Cancel
Save