Pixano-Inference is an inference library for Pixano.

Under active development, subject to API change

Pixano-Inference

An inference server for the Pixano annotation tool. It runs models on Ray Serve and exposes them through a REST API and a Python client.

Each model lives in its own Python package. Install the ones you need and the server finds them.

Quickstart

This runs SAM2 and segments an object from a single click. You need Python 3.10 to 3.13.

pip install "pixano-inference[sam]"
pip install "sam-2 @ git+https://github.com/facebookresearch/sam2.git"

Write the server configuration in models.py:

from pixano_inference.configs import DeploymentConfig, ModelConfig
from pixano_inference_sam import Sam2ImageParams

models = [
    ModelConfig(
        name="sam2-image",
        model_class="Sam2ImageModel",
        model_params=Sam2ImageParams(path="facebook/sam2-hiera-base-plus"),
        deployment=DeploymentConfig(num_gpus=1),  # 0 to run on CPU
    ),
]

Start the server. The first start downloads the weights.

pixano-inference --config models.py

When http://localhost:7463/v1/ready answers "ready": true, run this from another terminal:

from pixano_inference.client import SyncPixanoInferenceClient
from pixano_inference.schemas import SegmentationRequest

client = SyncPixanoInferenceClient("http://localhost:7463")
result = client.segmentation(
    SegmentationRequest(
        model="sam2-image",
        image="https://raw.githubusercontent.com/pixano/pixano-inference/main/docs/assets/examples/sam2/truck.jpg",
        points=[[[500, 375]]],  # one click, in pixels
        labels=[[1]],  # 1: the click is on the object
    )
)

scores = result.data.scores.to_numpy().ravel()
best = scores.argmax()
mask = result.data.masks[0][best].to_mask()
print(f"score {scores[best]:.2f}, mask of {mask.sum()} pixels")

Models

Each package has its own README in packages/.

An application that only sends requests to a server needs pip install pixano-inference, which installs the client without the server.

Your own model

A model is a small Python package. The YOLO example shows a detector and a tracker, and the numpy detector a model with no ML framework at all. The custom models guide explains the rest.

Development

git clone https://github.com/pixano/pixano-inference.git
cd pixano-inference
uv sync
uv run pytest -m "not integration" tests/

Each package under packages/ has its own environment and tests, for example:

uv run --project packages/pixano-inference-sam pytest packages/pixano-inference-sam/tests

The documentation covers the API, Docker deployment and autoscaling.

License

Pixano-Inference is released under the terms of the CeCILL-C license.