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README.md
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@@ -3,4 +3,100 @@ license: apache-2.0
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base_model:
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- ByteDance-Seed/SeedVR2-3B
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- ByteDance-Seed/SeedVR2-7B
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---
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base_model:
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- ByteDance-Seed/SeedVR2-3B
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- ByteDance-Seed/SeedVR2-7B
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---
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# ComfyUI-SeedVR2_VideoUpscaler
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A Non official custom nodes for ComfyUI that enables Upscale Video generation using [SeedVR2](https://github.com/ByteDance-Seed/SeedVR).
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<video width="700px" controls>
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<source src="https://github.com/user-attachments/assets/8fbd6c1f-4246-4dbe-8819-4e684490c5f2" type="video/mp4">
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Your browser does not support the video tag.
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</video>
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<img src="docs/usage.png" width="700px">
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## Features
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- High-quality Upscaling
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- Suitable for any video length once the right settings are found
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- Model Will Be Download Automatically from [Models](https://huggingface.co/numz/SeedVR2_comfyUI/tree/main)
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## Requirements
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- Last ComfyUI version with python 3.12.9 (may be works with older versions but I haven't test it)
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## Installation
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1. Clone this repository into your ComfyUI custom nodes directory:
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```bash
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cd ComfyUI/custom_nodes
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git clone https://github.com/your-repo/ComfyUI-SeedVR2_VideoUpscaler.git
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```
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2. Install the required dependencies:
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load venv and :
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```bash
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pip install -r ComfyUI-SeedVR2_VideoUpscaler/requirements.txt
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```
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install flash_attn if it ask for it
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```bash
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pip install -r flash_attn
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```
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Or use python_embeded :
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```bash
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python_embeded\python.exe -m pip install -r ComfyUI-SeedVR2_VideoUpscaler/requirements.txt
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```
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```bash
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python_embeded\python.exe -m pip install -r flash_attn
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```
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## Usage
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1. In ComfyUI, locate the **SeedVR2 Video Upscaler** node in the node menu.
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<img src="docs/node.png" width="100%">
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2. Configure the node parameters:
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- `model`: Select your 3B or 7B model
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- `seed`: a seed but it generate another seed from this one
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- `new_width`: New desired Width, will keep ration on height
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- `cfg_scale`:
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- `batch_size`: VERY IMPORTANT!, this model consume a lot of VRAM, All your VRAM, even for the 3B model, so for GPU under 24GB VRAM keep this value Low, good values are [1,5,9,13,...]
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- `vram_mode`: It will try to help with VRAM, but 'auto' is good
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## Performance
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1. **NVIDIA H100 93GB VRAM**
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- 3B Model, 97 images, from 512x768 to 1280x1920, batch_size=50 => Prompt executed in 338.63 seconds
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- 3B Model, 97 images, from 512x768 to 1280x1920, batch_size=10 => Prompt executed in 540.22 seconds
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- 3B Model, 97 images, from 512x768 to 720x1080, batch_size=10 => Prompt executed in 183.64 seconds
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- 7B Model, 50images, 512x768 to 1080x1620, batch_size=50, executed in 166.89 seconds
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2. **NVIDIA RTX4090 24GB VRAM**
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- 3B Model, 20 images, from 512x768 to 1080x1620, batch_size=1, Prompt executed in 1022.26 seconds
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-
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## Limitations
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- Use a lot of VRAM, it will take alllllll!!!!
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- Processing speed depends on GPU capabilities
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## Credits
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- Original [SeedVR2](https://github.com/ByteDance-Seed/SeedVR) implementation
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# 📜 License
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- The code in this repository is released under the MIT license as found in the [LICENSE file](LICENSE).
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