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Welcome to the Model Garden for TensorFlow

The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development.

Directory Description
official • A collection of example implementations for SOTA models using the latest TensorFlow 2's high-level APIs
• Officially maintained, supported, and kept up to date with the latest TensorFlow 2 APIs by TensorFlow
• Reasonably optimized for fast performance while still being easy to read
research • A collection of research model implementations in TensorFlow 1 or 2 by researchers
• Maintained and supported by researchers
community • A curated list of the GitHub repositories with machine learning models and implementations powered by TensorFlow 2
orbit • A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. It seamlessly integrates with tf.distribute and supports running on different device types (CPU, GPU, and TPU).
Date News
July 10, 2020 TensorFlow 2 meets the Object Detection API (Blog)
June 30, 2020 SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization released (Tweet)
June 17, 2020 Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection released (Tweet)
May 21, 2020 Unifying Deep Local and Global Features for Image Search (DELG) code released
May 19, 2020 MobileDets: Searching for Object Detection Architectures for Mobile Accelerators released
May 7, 2020 MnasFPN with MobileNet-V2 backbone released for object detection
May 1, 2020 DELF: DEep Local Features updated to support TensorFlow 2.1
March 31, 2020 Introducing the Model Garden for TensorFlow 2 (Tweet)

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help wanted:paper implementation

If you want to contribute, please review the contribution guidelines.

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Apache License 2.0

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Models and examples built with TensorFlow

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