Data-centric AI building blocks for computer vision applications
Under active development, subject to API change
Pixano is an open-source tool by CEA List for exploring and annotating your dataset using AI features:
- Fast dataset navigation using the the modern storage format Lance
- Multi-view datasets support for text, images and videos, and soon for 3D point clouds
- Import and export support for dataset formats like COCO
- Semantic search using models like CLIP
- Smart segmentation using models like SAM
Installing Pixano
Production
We recommend installing the published Pixano package in a dedicated Python virtual environment (Python >= 3.10, < 3.14).
For example, with conda:
conda create -n pixano_env python=3.10
conda activate pixano_env
Then, install Pixano with pip:
pip install pixano
Create a data directory and start the Pixano server, then open http://127.0.0.1:7492:
pixano init ./my_data
pixano server run ./my_data
Pixano is also available on the Docker Hub for official releases:
docker pull pixano/pixano:stable
docker run -d --name pixano -e DATA_DIR=/library -p 7492:7492 -v "$(pwd)/my_data:/library" pixano/pixano:stable
my_data is a folder on your machine where Pixano keeps your datasets; the container creates it on first start.
Development (from source)
To run the latest version of Pixano from source, you need uv. Install it if you haven't already:
curl -LsSf https://astral.sh/uv/install.sh | sh
Then, clone the repository and install all dependencies:
git clone https://github.com/pixano/pixano.git
cd pixano
uv sync
This installs the project in editable mode with all dependencies pinned via uv.lock. Your local changes are taken into account each time you run your environment.
Build the frontend UI assets:
pnpm -C ui install
pnpm -C ui/apps/pixano run build
Create a data directory and start the Pixano server:
uv run pixano init ./my_data
uv run pixano server run ./my_data
For more details on running Pixano locally (frontend setup, testing, formatting), see CONTRIBUTING.md.
Using Pixano
Please refer to our Getting started guide for information on how to launch and use the Pixano app, and how to create and use Pixano datasets.
Contributing
Please refer to our CONTRIBUTING.md for information on running Pixano locally and guidelines on how to publish your contributions.
License
Pixano is licensed under the CeCILL-C license.
1 maintainer
Metadata
1 maintainer
Release files for pixano 0.8.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| pixano-0.8.0.tar.gz | 24.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pixano-0.8.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.6 MB
Release files / pixano-0.8.0.tar.gz
| Download URL | pixano-0.8.0.tar.gz |
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| Size | 24.2 MB |
| Tags | Source |
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| Size | 1.4 MB |
| Tags | Python 3 |
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