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