Awesome-CoreML-Models and awesome-CoreML-models

These tools are competitors because both are collections of Core ML models, and a user would likely choose one as their primary resource for finding models.

Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 19/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 17/25
Stars: 6,968
Forks: 507
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 586
Forks: 61
Downloads:
Commits (30d): 0
Language:
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About Awesome-CoreML-Models

likedan/Awesome-CoreML-Models

Largest list of models for Core ML (for iOS 11+)

This project offers a comprehensive collection of pre-trained machine learning models that can be directly integrated into Apple applications (iOS, macOS, tvOS, watchOS). It allows app developers to easily add features like image recognition, text detection, and pose estimation. Developers can take these models and build intelligent features into their apps, from identifying objects in photos to recognizing emotions from faces.

iOS development app features image analysis machine learning integration mobile development

About awesome-CoreML-models

SwiftBrain/awesome-CoreML-models

Collection of models for Core ML

This collection provides ready-to-use machine learning models that run directly on Apple devices. It helps iOS developers integrate advanced capabilities like object detection, image classification (e.g., food, flowers), sentiment analysis, and facial attribute recognition (age, gender, emotion) into their apps. You get a Core ML model file and an example Xcode project, which lets you see the model in action and quickly incorporate it into your own application.

iOS development mobile app features image recognition natural language processing facial analysis

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