faster_rcnn_pytorch

Why we included this project

This is an honest, from-scratch PyTorch port of Faster R-CNN, written by someone learning the framework rather than shipping production code. The author rebuilt the region proposal network and RoI pooling by hand instead of calling into a high-level library, so the code shows the real wiring of a two-stage detector: anchor generation, proposal scoring, and the custom CUDA and Cython layers for NMS and pooling. For anyone trying to understand object detection internals or write their own implementation, it works well as a study reference. The README is also candid that it does not match the original Caffe version's accuracy and predates modern PyTorch APIs, and it points to newer, maintained forks if your real goal is to train Faster R-CNN on your own data. Treat this as a way to learn the architecture, not something to drop into production.