An open API service indexing awesome lists of open source software.

https://github.com/outofai/gen3c-modal

GRADIO GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control
https://github.com/outofai/gen3c-modal

camera-control gen3c gradio modal video-diffusion-model

Last synced: 4 months ago
JSON representation

GRADIO GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control

Awesome Lists containing this project

README

          

# GRADIO GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control

This the Gradio variation of https://github.com/nv-tlabs/GEN3C to run on https://modal.com/. Currently Running on a Single A100-80GB GPU
with inference time for each clip around ~15 mins. Modal offers 30 dollars for free for GPU computing which is more than enough to run this
model for couple of inferences!

Make sure you have Modal module installed
You have to always make sure that you have requested access to https://huggingface.co/nvidia/Cosmos-Tokenize1-CV8x8x8-720p repo as it's a gated repo
```
python3 -m pip install Modal
```

and also set up correctly

```
python3 -m modal setup
```

you would also need a huggingface Token set a Secret with the name HF_TOKEN on modal dashboard then simply deploy the model

```
python3 -m modal deploy modal_cli.py
```

The first time runnning the Gradio interface, you would need to dowload the models on Modal's storage by clicking Download Checkpoints
before running inference, it's 70+ GB of data and then after you wouldn't need to download it anymore as it gets stored on the given volume

## Examples

![image](https://github.com/user-attachments/assets/598f3e26-418d-48cd-b5d7-1cb25c39224b)

https://github.com/user-attachments/assets/ce04b86a-40ec-4571-ab94-936979fd5908

https://github.com/user-attachments/assets/98590b46-f0cb-49fe-bf93-6bb0f2359935