69 lines
2.6 KiB
Markdown
69 lines
2.6 KiB
Markdown
---
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tags:
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- Checkpoint
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- CheckpointLoader
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- Loader
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- ModelIO
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- ModelLoader
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---
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# Image Only Checkpoint Loader (img2vid model)
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## Documentation
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- Class name: `ImageOnlyCheckpointLoader`
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- Category: `loaders/video_models`
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- Output node: `False`
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This node specializes in loading checkpoints specifically for image-based models within video generation workflows. It efficiently retrieves and configures the necessary components from a given checkpoint, focusing on image-related aspects of the model.
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## Input types
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### Required
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- **`ckpt_name`**
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- Specifies the name of the checkpoint to load. This parameter is crucial for identifying and retrieving the correct checkpoint file from a predefined list of available checkpoints.
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- Comfy dtype: `COMBO[STRING]`
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- Python dtype: `str`
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## Output types
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- **`model`**
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- Comfy dtype: `MODEL`
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- Returns the main model loaded from the checkpoint, configured for image processing within video generation contexts.
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- Python dtype: `torch.nn.Module`
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- **`clip_vision`**
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- Comfy dtype: `CLIP_VISION`
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- Provides the CLIP vision component extracted from the checkpoint, tailored for image understanding and feature extraction.
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- Python dtype: `torch.nn.Module`
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- **`vae`**
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- Comfy dtype: `VAE`
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- Delivers the Variational Autoencoder (VAE) component, essential for image manipulation and generation tasks.
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- Python dtype: `torch.nn.Module`
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## Usage tips
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- Infra type: `GPU`
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- Common nodes:
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- [SVD_img2vid_Conditioning](../../Comfy/Nodes/SVD_img2vid_Conditioning.md)
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- [VAEDecode](../../Comfy/Nodes/VAEDecode.md)
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- [VideoLinearCFGGuidance](../../Comfy/Nodes/VideoLinearCFGGuidance.md)
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- Reroute
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- [StableZero123_Conditioning](../../Comfy/Nodes/StableZero123_Conditioning.md)
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- [LoraLoader](../../Comfy/Nodes/LoraLoader.md)
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- [Anything Everywhere](../../cg-use-everywhere/Nodes/Anything Everywhere.md)
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- [KSampler](../../Comfy/Nodes/KSampler.md)
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- workflow/front
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## Source code
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```python
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class ImageOnlyCheckpointLoader:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "ckpt_name": (folder_paths.get_filename_list("checkpoints"), ),
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}}
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RETURN_TYPES = ("MODEL", "CLIP_VISION", "VAE")
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FUNCTION = "load_checkpoint"
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CATEGORY = "loaders/video_models"
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def load_checkpoint(self, ckpt_name, output_vae=True, output_clip=True):
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ckpt_path = folder_paths.get_full_path("checkpoints", ckpt_name)
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out = comfy.sd.load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=False, output_clipvision=True, embedding_directory=folder_paths.get_folder_paths("embeddings"))
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return (out[0], out[3], out[2])
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```
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