CharlesShang/TFFRCNN
TensorFlow-based implementation of Faster R-CNN for real-time object detection with region proposal networks.
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This repository provides a TensorFlow implementation of Faster R-CNN, a widely-used deep learning architecture for real-time object detection. It supports multiple backbone networks including VGG16, ResNet, and PVANet, and includes features such as Position Sensitive ROI Pooling, Hard Example Mining, and data augmentation. The project reorganizes the codebase into independent Python modules for easier understanding and modification, based on the original Faster R-CNN paper by Ren et al.
Frequently asked
- What is CharlesShang/TFFRCNN?
- TensorFlow-based implementation of Faster R-CNN for real-time object detection with region proposal networks.
- Is TFFRCNN open source?
- Yes — CharlesShang/TFFRCNN is open source, released under the MIT license.
- What language is TFFRCNN written in?
- CharlesShang/TFFRCNN is primarily written in Python.
- How popular is TFFRCNN?
- CharlesShang/TFFRCNN has 871 stars on GitHub.
- Where can I find TFFRCNN?
- CharlesShang/TFFRCNN is on GitHub at https://github.com/CharlesShang/TFFRCNN.