Développement
Transformers
The model-definition framework behind modern AI — thousands of pretrained transformers for text, vision, and audio.
★ 166,9 k étoilesApache-2.0
Voir le guide →mediapipe est un projet de développement open source, créé par google-ai-edge (google-ai-edge/mediapipe sur GitHub). Il compte 37 191 étoiles sur GitHub et 6 183 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.
Google's cross-platform framework for on-device ML perception: vision, text and audio pipelines
Decide what you want to achieve with mediapipe and check the README on GitHub for requirements before installing.
Clone the repository from GitHub (or take the packaged install route in step 3 if the README offers one).
Follow the project's documented install commands — the Run section below lists the exact ones — and add any required API keys or models.
Work through the README's quickstart example end to end, then adapt it to your own project or data.
Ready-to-use solutions for vision, text and audio tasks such as object detection, image classification, text classification and audio classification.
Processing is built from reusable graph nodes called calculators, so complex perception pipelines stay modular and efficient.
One framework spans Android, iOS, web, desktop and Raspberry Pi-class devices.
Models run locally on the device, keeping latency low and media private — no server round-trip.
The repo also carries the legacy MediaPipe solutions (hands, face mesh, pose and more) alongside the newer Tasks APIs.
Developed by Google with extensive guides, publications and videos linked from the repository.
Get the MediaPipe framework source.
git clone https://github.com/google-ai-edge/mediapipe.git
cd mediapipeFor Python development, install MediaPipe from PyPI as covered in the official setup guides.
pip install mediapipeFollow the developer guide for your task (vision, text or audio) and platform to run a ready-made model.
# see the task guides at https://ai.google.dev/edge/mediapipe for the exact example codemediapipe is maintained by the google-ai-edge organization/account on GitHub, together with open-source contributors, in the public repository google-ai-edge/mediapipe.
Yes — the code is open source under the Apache-2.0 license. You can use, modify and redistribute it under that license's terms.
No API key or paid service is needed — MediaPipe and its downloadable task models run locally on your device or machine.
Cloud APIs are easier to start with but charge per call and need connectivity; MediaPipe runs on-device for free with low latency, at the cost of integrating the framework yourself.
Clone the repository from GitHub, follow the install commands in the Run section (taken from the project's README), and complete the documented quickstart example before adapting it to your own use case.
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