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Use GPU for otherwise very slow "Image Film Grain" node (if available) #462

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Use GPU for otherwise very slow "Image Film Grain" node (if available) #462

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ClownsharkBatwing Aug 15, 2024
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ClownsharkBatwing Aug 15, 2024
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ClownsharkBatwing Aug 15, 2024
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28 changes: 15 additions & 13 deletions WAS_Node_Suite.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6252,24 +6252,27 @@ def film_grain(self, image, density, intensity, highlights, supersample_factor):
return (pil2tensor(self.apply_film_grain(tensor2pil(image), density, intensity, highlights, supersample_factor)), )

def apply_film_grain(self, img, density=0.1, intensity=1.0, highlights=1.0, supersample_factor=4):
"""
Apply grayscale noise with specified density, intensity, and highlights to a PIL image.
"""

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

#Apply grayscale noise with specified density, intensity, and highlights to a PIL image.
img_gray = img.convert('L')
original_size = img.size
img_gray = img_gray.resize(
((img.size[0] * supersample_factor), (img.size[1] * supersample_factor)), Image.Resampling(2))
num_pixels = int(density * img_gray.size[0] * img_gray.size[1])

noise_pixels = []
for i in range(num_pixels):
x = random.randint(0, img_gray.size[0]-1)
y = random.randint(0, img_gray.size[1]-1)
noise_pixels.append((x, y))

for x, y in noise_pixels:
value = random.randint(0, 255)
img_gray.putpixel((x, y), value)
img_gray_tensor = torch.from_numpy(np.array(img_gray).astype(np.float32) / 255.0).to(device)
img_gray_flat = img_gray_tensor.view(-1)
num_pixels = int(density * img_gray_flat.numel())
indices = torch.randint(0, img_gray_flat.numel(), (num_pixels,), device=img_gray_flat.device)
values = torch.randint(0, 256, (num_pixels,), device=img_gray_flat.device, dtype=torch.float32) / 255.0

img_gray_flat[indices] = values
img_gray = img_gray_flat.view(img_gray_tensor.shape)

img_gray_np = (img_gray.cpu().numpy() * 255).astype(np.uint8)
img_gray = Image.fromarray(img_gray_np)

img_noise = img_gray.convert('RGB')
img_noise = img_noise.filter(ImageFilter.GaussianBlur(radius=0.125))
Expand All @@ -6279,7 +6282,6 @@ def apply_film_grain(self, img, density=0.1, intensity=1.0, highlights=1.0, supe
enhancer = ImageEnhance.Brightness(img_final)
img_highlights = enhancer.enhance(highlights)

# Return the final image
return img_highlights


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