GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection, semantic segmentation and pose estimation, to instance segmentation and video action recognition. The model zoo is the one-stop shopping center for many models you are expecting. GluonCV embraces a flexible development pattern while is super easy to optimize and deploy without retaining a heavyweight deep learning framework.

Features

  • Train scripts to reproduce SOTA results reported in research papers
  • Supports both PyTorch and MXNet
  • A large number of pre-trained models
  • Carefully designed APIs that greatly reduce the implementation complexity
  • Community support
  • It is designed for engineers, researchers, and students to fast prototype products

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License

Apache License V2.0

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Additional Project Details

Programming Language

Python

Related Categories

Python Frameworks, Python Machine Learning Software, Python Computer Vision Libraries, Python Object Detection Models, Python Deep Learning Frameworks

Registered

2021-11-01