ComfyUI Extension: ComfyUI-SeedVR2_VideoUpscaler

Authored by numz

Created

Updated

27 stars

Upscale your videos with this SeedVR2

Custom Nodes (0)

    README

    ComfyUI-SeedVR2_VideoUpscaler

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    A Non official custom nodes for ComfyUI that enables Upscale Video generation using SeedVR2.

    <video width="700px" controls> <source src="https://github.com/user-attachments/assets/8fbd6c1f-4246-4dbe-8819-4e684490c5f2" type="video/mp4"> Your browser does not support the video tag. </video> <img src="docs/usage.png" width="700px">

    Features

    • High-quality Upscaling
    • Suitable for any video length once the right settings are found
    • Model Will Be Download Automatically from Models

    Requirements

    • Last ComfyUI version with python 3.12.9 (may be works with older versions but I haven't test it)

    Installation

    1. Clone this repository into your ComfyUI custom nodes directory:
    cd ComfyUI/custom_nodes
    git clone https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler.git
    
    1. Install the required dependencies:

    load venv and :

    pip install -r ComfyUI-SeedVR2_VideoUpscaler/requirements.txt
    

    install flash_attn if it ask for it

    pip install -r flash_attn
    

    Or use python_embeded :

    python_embeded\python.exe -m pip install -r ComfyUI-SeedVR2_VideoUpscaler/requirements.txt
    
    python_embeded\python.exe -m pip install -r flash_attn
    
    1. Models

      Will be automtically download into : models/SEEDVR2

      or can be found here (MODELS)

    Usage

    1. In ComfyUI, locate the SeedVR2 Video Upscaler node in the node menu.
    <img src="docs/node.png" width="100%">
    1. Configure the node parameters:

      • model: Select your 3B or 7B model
      • seed: a seed but it generate another seed from this one
      • new_width: New desired Width, will keep ration on height
      • cfg_scale:
      • 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,...]
      • vram_mode: It will try to help with VRAM, but 'auto' is good

    Performance

    1. NVIDIA H100 93GB VRAM

    3B or 7B spike to 90+GB VRAM!! but fast!!

    • 3B Model, 97 images, from 512x768 to 1280x1920, batch_size=50 => Prompt executed in 338.63 seconds
    • 3B Model, 97 images, from 512x768 to 1280x1920, batch_size=10 => Prompt executed in 540.22 seconds
    • 3B Model, 97 images, from 512x768 to 720x1080, batch_size=10 => Prompt executed in 183.64 seconds
    • 7B Model, 50 images, 512x768 to 1080x1620, batch_size=50, Prompt executed in 166.89 seconds
    • 7B Model, 97 images, 512x768 to 1080x1620, batch_size=97, Prompt executed in 146.72 seconds
    • 7B Model, 200 images, 512x768 to 1080x1620, batch_size=200, Prompt executed in 266.14 seconds
    1. NVIDIA RTX4090 24GB VRAM
    • 3B Model, 20 images, from 512x768 to 1080x1620, batch_size=1, Prompt executed in 435.13 seconds

    Limitations

    • Use a lot of VRAM, it will take alllllll!!!!
    • Processing speed depends on GPU capabilities

    Credits

    📜 License

    • The code in this repository is released under the MIT license as found in the LICENSE file.