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googlesamples avatar

googlesamples/mlkit

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4,248 stele·3,090 fork-uri·Java·Apache-2.0·3 vizualizări

Mlkit

Acest repository este o colecție de aplicații eșantion și proiecte de referință pentru integrarea API-urilor de machine learning on-device în aplicațiile mobile. Oferă exemple de implementare atât pentru Android, cât și pentru iOS, demonstrând cum să încorporați modele de computer vision și procesare a limbajului natural.

Proiectul acoperă implementarea computer vision-ului mobil, inclusiv recunoașterea textului, detectarea feței și scanarea codurilor de bare. Include workflow-uri pentru procesarea imaginilor în timp real și integrarea modelelor pre-antrenate care procesează datele local pe dispozitiv.

Features

  • On-Device Inference - Provides reference implementations for executing machine learning models locally on mobile hardware to eliminate cloud dependency.
  • Cross-Platform ML Deployment - Provides a unified approach to implementing consistent ML behaviors across both iOS and Android platforms.
  • Machine Learning Integrations - Demonstrates the process of embedding pre-trained ML models into mobile applications to enable on-device intelligence.
  • Mobile Vision Implementations - Implements practical mobile computer vision features including text recognition, face detection, and barcode scanning.
  • Mobile Reference Implementations - Ships separate, native codebase paths for Android and iOS to demonstrate platform-specific ML API integration.
  • Android ML Examples - Provides a comprehensive collection of reference projects for implementing ML Kit features on Android.
  • iOS ML Examples - Provides a comprehensive collection of reference projects for implementing ML Kit features on iOS.
  • Mobile ML Sample Applications - Offers a collection of sample apps that demonstrate how to integrate on-device ML APIs on Android and iOS.
  • Real-Time Frame Analysis - Builds workflows that analyze live camera frames in real time for object identification and text reading.
  • Asynchronous Processing Pipelines - Implements background processing pipelines to ensure heavy ML computations do not freeze the mobile user interface.
  • Event-Driven UI Rendering - Triggers real-time UI updates based on the continuous data stream produced by the camera and ML models.

Istoric stele

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Întrebări frecvente

Ce face googlesamples/mlkit?

Acest repository este o colecție de aplicații eșantion și proiecte de referință pentru integrarea API-urilor de machine learning on-device în aplicațiile mobile. Oferă exemple de implementare atât pentru Android, cât și pentru iOS, demonstrând cum să încorporați modele de computer vision și procesare a limbajului natural.

Care sunt principalele funcționalități ale googlesamples/mlkit?

Principalele funcționalități ale googlesamples/mlkit sunt: On-Device Inference, Cross-Platform ML Deployment, Machine Learning Integrations, Mobile Vision Implementations, Mobile Reference Implementations, Android ML Examples, iOS ML Examples, Mobile ML Sample Applications.

Care sunt câteva alternative open-source pentru googlesamples/mlkit?

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