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temporal-controlnet-depth-svd-v1
CiaraRowles/temporal-controlnet-depth-svd-v1
temporal-controlnet-depth-svd-v1 is a machine learning model from CiaraRowles. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for diffusers. The card lists the license as unknown.
Introducing the Stable Video Diffusion Temporal Controlnet! This tool uses a controlnet style encoder with the svd base. It's designed to enhance your video diffusion projects by providing precise temporal control.
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Updated Dec 23, 2023
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At a glance
- Library
- diffusers
- License
- unknown
- Access
- Public
- Created
- Dec 23, 2023
- Updated
- Dec 23, 2023
- SHA
- 0737ee01
Model card
From the Hugging Face model README
Stable Video Diffusion Temporal Controlnet
Overview
Introducing the Stable Video Diffusion Temporal Controlnet! This tool uses a controlnet style encoder with the svd base. It's designed to enhance your video diffusion projects by providing precise temporal control.
Setup
- Controlnet Model: download the inference repo from here: https://github.com/CiaraStrawberry/sdv_controlnet
- Installation: run
pip install -r requirements.txt - Execution: Run "run_inference.py".
Demo
Notes
- Focus on Central Object: The system tends to extract motion features primarily from a central object and, occasionally, from the background. It's best to avoid overly complex motion or obscure objects.
- Simplicity in Motion: Stick to motions that svd can handle well without the controlnet. This ensures it will be able to apply the motion.
Acknowledgements
- Diffusers Team: For the svd implementation.
- Pixeli99: For providing a practical svd training script: SVD_Xtend
- Library
- diffusers
- License
- unknown
- Created
- Dec 23, 2023
- Updated
- Dec 23, 2023