Instructions to use TheDenk/cogvideox-5b-controlnet-canny-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TheDenk/cogvideox-5b-controlnet-canny-v1 with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("TheDenk/cogvideox-5b-controlnet-canny-v1") pipe = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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language:
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- en
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tags:
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- cogvideox
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- video-generation
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- video-to-video
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- controlnet
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- diffusers
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---
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# CogvideoX-5b Controlnet Extention
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###
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```
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--
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--
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--
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<p>Issues should be raised directly in the repository. For professional support and recommendations please <a>welcomedenk@gmail.com</a>.</p>
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---
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license: apache-2.0
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language:
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- en
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tags:
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- cogvideox
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- video-generation
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- video-to-video
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- controlnet
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- diffusers
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---
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# CogvideoX-5b Controlnet Extention
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63fde49f6315a264aba6a7ed/pdqauAcmf3d-v1mmu4UeR.mp4"></video>
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### (Warning) This is raw version of controlnet. Better version will be published soon.
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### How to
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Clone repo
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```bash
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git clone https://github.com/TheDenk/cogvideox-controlnet.git
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cd cogvideox-controlnet
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```
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Create venv
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```bash
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python -m venv venv
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source venv/bin/activate
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```
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Install requirements
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```bash
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pip install -r requirements.txt
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```
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### Inference examples
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#### Inference with cli
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```bash
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python -m inference.cli_demo \
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--video_path "resources/car.mp4" \
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--prompt "The camera follows behind red car. Car is surrounded by a panoramic view of the vast, azure ocean. Seagulls soar overhead, and in the distance, a lighthouse stands sentinel, its beam cutting through the twilight. The scene captures a perfect blend of adventure and serenity, with the car symbolizing freedom on the open sea." \
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--controlnet_type "canny" \
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--base_model_path THUDM/CogVideoX-5b \
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--controlnet_model_path TheDenk/cogvideox-5b-controlnet-canny-v1
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```
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#### Inference with Gradio
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```bash
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python -m inference.gradio_web_demo \
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--controlnet_type "canny" \
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--base_model_path THUDM/CogVideoX-5b \
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--controlnet_model_path TheDenk/cogvideox-5b-controlnet-canny-v1
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```
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## Acknowledgements
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Original code and models [CogVideoX](https://github.com/THUDM/CogVideo/tree/main).
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## Contacts
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<p>Issues should be raised directly in the repository. For professional support and recommendations please <a>welcomedenk@gmail.com</a>.</p>
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