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synced 2025-12-10 05:15:05 +08:00
Fix the nodes to actually work
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d526683f25
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d566c3c35a
29
nodes.py
29
nodes.py
@ -63,14 +63,17 @@ class CreateGradientMask:
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offset_gradient = gradient - time # Offset the gradient values based on time
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image_batch[i] = offset_gradient.reshape(1, -1)
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output = torch.from_numpy(image_batch)
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out.append(output)
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mask = output
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print("gradientmaskshape")
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print(mask.shape)
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out.append(mask)
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if invert:
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return (1.0 - torch.stack(out, dim=0),)
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return (torch.stack(out, dim=0),)
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return (1.0 - torch.cat(out, dim=0),)
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return (torch.cat(out, dim=0),)
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class CreateTextMask:
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RETURN_TYPES = ("MASK",)
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RETURN_TYPES = ("IMAGE", "MASK",)
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FUNCTION = "createtextmask"
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CATEGORY = "KJNodes"
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@ -96,10 +99,10 @@ class CreateTextMask:
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# Define the number of images in the batch
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batch_size = frames
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out = []
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masks = []
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rotation = start_rotation
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if frames > 1:
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rotation_increment = (end_rotation - start_rotation) / (batch_size - 1)
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# Create an empty array to store the image batch
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image_batch = np.zeros((batch_size, height, width), dtype=np.float32)
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if font_path == "fonts\\TTNorms-Black.otf": #I don't know why relative path won't work otherwise...
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font_path = os.path.join(script_dir, font_path)
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# Generate the text
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@ -112,14 +115,15 @@ class CreateTextMask:
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text_center_y = text_y + text_height / 2
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draw.text((text_x, text_y), text, font=font, fill="white")
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image = image.rotate(rotation, center=(text_center_x, text_center_y))
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image = np.array(image).astype(np.float32) / 255.0
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image = torch.from_numpy(image)[None,]
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mask = image[:, :, :, 0]
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masks.append(mask)
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out.append(image)
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rotation += rotation_increment
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image_batch[i] = np.array(image.convert("L"))
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output = torch.from_numpy(image_batch)
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rotation += 10
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out.append(output)
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if invert:
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return (1.0 - torch.stack(out, dim=0),)
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return (torch.stack(out, dim=0),)
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return (1.0 - torch.cat(out, dim=0),)
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return (torch.cat(out, dim=0),torch.cat(masks, dim=0),)
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class GrowMaskWithBlur:
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@classmethod
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@ -173,6 +177,7 @@ class GrowMaskWithBlur:
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else:
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expand += abs(incremental_expandrate) # Use abs(growrate) to ensure positive change
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output = torch.from_numpy(output)
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print(output.shape)
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out.append(output)
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blurred = torch.stack(out, dim=0).reshape((-1, 1, mask.shape[-2], mask.shape[-1])).movedim(1, -1).expand(-1, -1, -1, 3)
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