matrice

What it is and what it does

Matrice is a Python SDK that wraps the Matrice.ai platform's backend services, letting you programmatically manage the full lifecycle of machine learning projects—from creation through model training, export, and deployment. It provides high-level abstractions that handle session management, RPC calls, and response parsing via matrice_common, plus utilities for local testing, metrics calculation, and streaming automation.

The package is designed for developers building ML workflows: you can create projects, import data from local or cloud sources, submit training jobs with custom configurations, export trained models in multiple formats, deploy to FastAPI or Triton, create inference pipelines, and monitor drift. It also includes helpers for Docker environment setup, local test harnesses, and performance benchmarking. Optional dependencies extend functionality for data processing and streaming, but core project and model management work with just matrice_common.

Use it for:

• Create and manage ML projects end-to-end, from data import through model training and deployment on Matrice.ai.
• Automate annotation workflows by creating tasks, assigning labelers and reviewers, and tracking completion.
• Export trained models in multiple formats and deploy them to FastAPI or Triton inference servers.
• Build and manage inference pipelines that combine multiple applications and handle real-time camera streams.
• Monitor model drift in production deployments and track inference metrics over time.
• Run local tests and benchmarks on models before cloud deployment using provided test utilities.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Python SDK for building machine learning projects, datasets, models, and inference pipelines on the Matrice.ai platform, with support for training, deployment, and monitoring workflows.

Yes, if you are working within the Matrice.ai ecosystem. The SDK is actively maintained, has no known vulnerabilities, carries a permissive MIT license, and installs with minimal friction. It is the standard way to programmatically manage projects and workflows on the platform. If you are not already using Matrice.ai, it will not be useful—it is a platform-specific client library, not a general ML framework.

Install

matrice on PyPI

pip install matrice

uv add matrice

poetry add matrice

Installing matrice

Before you install

Low installation friction; pure Python wheel with a single runtime dependency (matrice_common). Actively maintained with a release 16 days old. Supports Python 3.8 through 3.12.

License in practice

MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute this package freely provided you include the license notice.

Quickstart

pip install matrice

from matrice import Projects
from matrice_common import Session

session = Session(api_key="your_api_key", base_url="https://api.matrice.ai")
project = Projects(session, project_name="my_project")

Requires valid Matrice.ai credentials (API key and base URL) and an active account; the SDK is a client for the Matrice.ai platform and cannot function standalone.

Verify before relying

• Whether optional dependencies (matrice_data_processing, matrice_streaming, requests, Pillow) are required for specific workflows or fully optional.
• API stability and backward-compatibility guarantees across versions.
• Performance characteristics when handling large datasets or high-volume inference pipelines.
• Whether the package can be used outside the Matrice.ai ecosystem or requires active platform credentials.

Package facts

Evidence: matrice-1.1.9-py3-none-any.whl

Keywords: matrice, common, utilities, mypyc, compiled

Tags

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