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README.md

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+# Stable Video Diffusion Temporal Controlnet
+
+## Overview
+Introducing the Stable Video Diffusion Temporal Controlnet! This innovative tool merges the prowess of a controlnet style encoder with the robustness of the svd base. It's designed to enhance your video diffusion projects by providing precise temporal control.
+
+## Setup
+- **Controlnet Model:** First, obtain a svd temporal controlnet model folder from this repo and use it with the github inference code here: https://github.com/CiaraStrawberry/sdv_controlnet
+- **Installation:** run `pip install -r requirements.txt`
+- **Execution:** Run "run_inference.py".
+
+## Demo
+
+![combined_with_square_image_new_gif](https://github.com/CiaraStrawberry/sdv_controlnet/assets/13116982/055c8d3b-074e-4aeb-9ddc-70d12b5504d5)
+
+## 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](https://github.com/pixeli99/SVD_Xtend)