Simple Faster R-CNN PyTorch

Simple Faster R-CNN PyTorch is an open-source implementation of the Faster R-CNN object detection architecture designed for clarity, reproducibility, and educational use. It simplifies the original model into approximately 2,000 lines of documented Python code. The software uses PyTorch and torchvision to implement region proposal generation, feature extraction, object classification, and bounding box regression. Its architecture includes a VGG16 backbone and standard Faster R-CNN training components. The project provides training scripts, evaluation utilities, and visualization tools for monitoring model performance. It includes examples using the PASCAL VOC object detection dataset. Reported experiments achieve mean average precision comparable to or higher than the original paper. The implementation emphasizes readable code and avoids unnecessary custom compilation steps.