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https://git.datalinker.icu/comfyanonymous/ComfyUI
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test
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@ -1077,8 +1077,8 @@ class WAN21(BaseModel):
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image = torch.zeros(shape_image, dtype=noise.dtype, layout=noise.layout, device=noise.device)
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image = torch.zeros(shape_image, dtype=noise.dtype, layout=noise.layout, device=noise.device)
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else:
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else:
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image = utils.common_upscale(image.to(device), noise.shape[-1], noise.shape[-2], "bilinear", "center")
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image = utils.common_upscale(image.to(device), noise.shape[-1], noise.shape[-2], "bilinear", "center")
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for i in range(0, image.shape[1], 16):
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for i in range(0, image.shape[1], 36):
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image[:, i: i + 16] = self.process_latent_in(image[:, i: i + 16])
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image[:, i: i + 36] = self.process_latent_in(image[:, i: i + 36])
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image = utils.resize_to_batch_size(image, noise.shape[0])
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image = utils.resize_to_batch_size(image, noise.shape[0])
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print(f"image shape: {image.shape}")
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print(f"image shape: {image.shape}")
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@ -671,12 +671,13 @@ class WanTrackToVideo:
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motion_patched = patch_motion(processed_tracks, y, temperature, (4, 16), topk)[None]
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motion_patched = patch_motion(processed_tracks, y, temperature, (4, 16), topk)[None]
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mask, video = motion_patched[:, 0:4], motion_patched[:, 4:]
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mask, video = motion_patched[:, 0:4], motion_patched[:, 4:]
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# Add motion features to conditioning
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# Add motion features to conditioning
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concat_latent_image = vae.encode(image[:, :, :, :3])
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positive = node_helpers.conditioning_set_values(positive,
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positive = node_helpers.conditioning_set_values(positive,
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{"concat_mask": motion_patched,
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{"concat_mask": motion_patched,
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"concat_latent_image": image})
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"concat_latent_image": concat_latent_image})
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negative = node_helpers.conditioning_set_values(negative,
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negative = node_helpers.conditioning_set_values(negative,
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{"concat_mask": motion_patched,
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{"concat_mask": motion_patched,
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"concat_latent_image": image})
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"concat_latent_image": concat_latent_image})
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# Handle clip vision output if provided
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# Handle clip vision output if provided
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