bubbliiiing/faster-rcnn-pytorch

Health v2 · maintenance only

Adoption not part of the score

1833 stars · 362 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch implementation of the Faster R-CNN two-stage object detection model, supporting training on VOC-format datasets with ResNet or VGG backbones. It includes pretrained weights, training/prediction/evaluation scripts, and extensive comments aimed at learners.

Use cases

• train a faster rcnn object detector on my own dataset
• pytorch implementation of faster rcnn
• object detection with voc format annotations
• learn how two-stage object detection works
• run object detection on images and videos with pretrained weights
• fine-tune faster rcnn with custom classes

When to choose

• you want a readable, well-commented Faster R-CNN implementation for learning or teaching
• your data is in or convertible to VOC format
• you need a working baseline detector with pretrained VOC weights

When to avoid

• you need production-grade, actively maintained detection tooling
• you want the latest architectures like DETR or YOLO variants
• you need COCO-format support or recent PyTorch versions out of the box

Facets

library · maturity maintenance

machine-learning deep-learning computer-vision image-processing deep-learning computer-vision machine-learning image-processing python cross-platform object-detection faster-rcnn pytorch voc-dataset two-stage-detector pretrained-weights educational gpu

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markdown · JSON · MCP: product_card(name="bubbliiiing/faster-rcnn-pytorch")