Spaces:
Runtime error
Runtime error
add ScharrOperator
Browse files
server/pipelines/utils/canny_gpu.py
CHANGED
@@ -57,3 +57,61 @@ class SobelOperator(nn.Module):
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return edge
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elif output_type == "pil,tensor":
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return ToPILImage()(edge.squeeze(0).cpu()), edge
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return edge
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elif output_type == "pil,tensor":
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return ToPILImage()(edge.squeeze(0).cpu()), edge
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+
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+
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class ScharrOperator(nn.Module):
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SCHARR_KERNEL_X = torch.tensor(
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[[-3.0, 0.0, 3.0], [-10.0, 0.0, 10.0], [-3.0, 0.0, 3.0]]
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)
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SCHARR_KERNEL_Y = torch.tensor(
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[[-3.0, -10.0, -3.0], [0.0, 0.0, 0.0], [3.0, 10.0, 3.0]]
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)
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def __init__(self, device="cuda"):
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super(ScharrOperator, self).__init__()
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self.device = device
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self.edge_conv_x = nn.Conv2d(1, 1, kernel_size=3, padding=1, bias=False).to(
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self.device
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)
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self.edge_conv_y = nn.Conv2d(1, 1, kernel_size=3, padding=1, bias=False).to(
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self.device
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)
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self.edge_conv_x.weight = nn.Parameter(
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self.SCHARR_KERNEL_X.view((1, 1, 3, 3)).to(self.device)
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)
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self.edge_conv_y.weight = nn.Parameter(
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self.SCHARR_KERNEL_Y.view((1, 1, 3, 3)).to(self.device)
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)
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@torch.no_grad()
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def forward(
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self,
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image: Image.Image,
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low_threshold: float,
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high_threshold: float,
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output_type="pil",
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invert: bool = False,
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) -> Image.Image | torch.Tensor | tuple[Image.Image, torch.Tensor]:
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# Convert PIL image to PyTorch tensor
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image_gray = image.convert("L")
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image_tensor = ToTensor()(image_gray).unsqueeze(0).to(self.device)
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# Compute gradients
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edge_x = self.edge_conv_x(image_tensor)
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edge_y = self.edge_conv_y(image_tensor)
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edge = torch.abs(edge_x) + torch.abs(edge_y)
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# Apply thresholding
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edge.div_(edge.max()) # Normalize to 0-1 (in-place operation)
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edge[edge >= high_threshold] = 1.0
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edge[edge <= low_threshold] = 0.0
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if invert:
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edge = 1 - edge
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# Convert the result back to a PIL image
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if output_type == "pil":
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return ToPILImage()(edge.squeeze(0).cpu())
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elif output_type == "tensor":
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return edge
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elif output_type == "pil,tensor":
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return ToPILImage()(edge.squeeze(0).cpu()), edge
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