Metadata-Version: 2.1
Name: simian3d
Version: 0.0.9
Summary: A synthetic data generator for video caption pairs.
Home-page: https://github.com/RaccoonResearch/Simian
Author: Raccoon Research
Author-email: shawmakesmagic@gmail.com
License: MIT
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Description-Content-Type: text/markdown
Requires-Dist: omegaconf
Requires-Dist: requests
Requires-Dist: argparse
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: distributaur
Requires-Dist: bpy
Requires-Dist: rr-infinigen

# Simian
A synthetic data generator for video caption pairs.


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Simian creates synthetic data that is usable for generative video and video captioning tasks. The data consists of videos and captions. The videos are generated using Blender, a 3D modeling software.

## 🖥️ Setup

> **_NOTE:_** Simian requires Python 3.11.

1. Install dependences:
```bash
pip install -r requirements.txt
```

2. Download the datasets:
```bash
./scripts/get_data.sh
```

3. [OPTIONAL] If you're on a headless Linux server, install Xorg and start it:

```bash
sudo apt-get install xserver-xorg -y && \
sudo python3 scripts/start_x_server.py start
```

## 📸 Usage

### Generating Combinations

```bash
python3 -m simian.combiner --count 1000 --seed 42
```

### Generating Videos or Images

Configure the flags as needed:
- `--width` and `--height` are the resolution of the video.
- `--combination_index` is the index of the combination to render.
- `--output_dir` is the directory to save the rendered video.
- `--hdri_path` is the directory containing the background images.
- `--start_frame` and `--end_frame` are the start and end frames of the video.
- `--animation_length` is the total number of frames, this as a result controls the how fast the animation will appear.
- `--images` adding this will output images instead of video at random frames. Creates multiple images per combination of varying sizes

Or generate all or part of the combination set using the `batch.py` script:


### Generating Videos or Images

To generate a video(s): 
```bash
python3 -m simian.batch --start_index 0 --end_index 1000 --width 1024 --height 576 --start_frame 1 --end_frame 65 --animation_length 120
```

To generate an image(s):
```bash
python3 -m simian.batch --start_index 0 --end_index 1000 --width 1024 --height 576 --start_frame 1 --end_frame 65 --animation_length 120 --images
```

You can also generate individually:
```bash
# MacOS
python -m simian.render

# Linux
python -m simian.render

## Kitchen sink
python -m simian.render -- --width 1920 --height 1080 --combination_index 0 --output_dir ./renders --hdri_path ./backgrounds --start_frame 1 --end_frame 65
```


### Clean up Captions

Make captions more prompt friendly.

> **_NOTE:_** Create a .env file and add your OpenAI API key
```bash
python3 scripts/rewrite_captions.py
```

### Distributed rendering
Rendering can be distributed across multiple machines using the "simian.py" and "worker.py" scripts.

You will need to set up Redis and obtain Huggingface API key to use this feature.

#### Set Up Redis
You can make a free Redis account [here](https://redis.io/try-free/).

For local testing and multiple local workers, you can use the following script to set up a local instance of Redis:
```bash
scripts/setup_redis.sh
```

#### Huggingface API Key

You can get a Huggingface API key [here](https://huggingface.co/settings/tokens).

Now, start your workers
```bash
export REDIS_HOST=<myhost>.com
export REDIS_PORT=1337
export REDIS_USER=default
export REDIS_PASSWORD=<somepassword>
export HF_TOKEN=<token>
export HF_REPO_ID=<repo_id>
celery -A simian.worker worker --loglevel=info
```

You can also build and run the worker with Docker
```bash
# build the container
docker build -t simian-worker .

# run the container with .env
docker run --env-file .env simian-worker

# run the container with environment variables
docker run -e REDIS_HOST={myhost} -e REDIS_PORT={port} -e REDIS_USER=default -e REDIS_PASSWORD={some password} -e HF_TOKEN={token} -e HF_REPO_ID={repo_id} simian-worker
```

Finally, issue work to your task queue

```bash
python3 -m simian.cli --start_index 0 --end_index 10 --width 1024 --height 576
```

If you want to use a custom or hosted Redis instance (recommended), you can add the redis details like this:
```bash
export REDIS_HOST=<myhost>.com
export REDIS_PORT=1337
export REDIS_USER=default
export REDIS_PASSWORD=<somepassword>
```

To run all tests

```
python3 -m simian.tests.__run__
```

To run tests look into the test folder and run whichever test file you want

```bash
python3 -m simian.tests.object_test
```

## 📁 Datasets

We are currently using the following datasets:
[Objaverse](https://huggingface.co/datasets/allenai/objaverse)

Backgrounds are loaded from:
[Poly Haven](https://polyhaven.com)

## 🦝 Contributing

We welcome contributions! We're especially interested in help adding and refining datasets, improving generation quality, adding new features and dynamics and allowing the project to meet more use cases.

### How to contribute

1. Check out the issues <a href="https://github.com/RaccoonResearch/simian/issues">here</a>. 
2. Join our Discord <a href="https://discord.gg/JMfbmHdPNB">here</a>.
3. Get in touch with us so we can coordinate on development.
4. Or, you know, just YOLO a pull request. We're pretty chill.

## 📜 License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

If you use it, please cite us:

```bibtex
@misc{Simian,
  author = {Raccoon Research},
  title = {Simian: A Synthetic Data Generator for Video Caption Pairs},
  year = {2024},
  publisher = {GitHub},
  howpublished = {\url{https://github.com/RaccoonResearch/simian}}
}
```

## Contributors ✨

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[![All Contributors](https://img.shields.io/badge/all_contributors-2-orange.svg?style=flat-square)](#contributors-)
<!-- ALL-CONTRIBUTORS-BADGE:END -->

This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!

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## Sponsors

<p style="text-align: center; margin-left: auto; margin-right: auto; max-width:800px;">
<center>Raccoon Research is sponsored by the following organizations:</center>
</p>
<p style="text-align: center; margin-left: auto; margin-right: auto; max-width:800px;">
</p>
<p style="text-align: center; margin-left: auto; margin-right: auto; max-width:800px;">
<center>Interested in working with us? Join our <a href="https://discord.gg/JMfbmHdPNB">Discord</a> or post an <a href="https://github.com/RaccoonResearch/Simian/issues/new">issue</a> to get in touch.</center>
</p>
