TuSimple/mx-maskrcnn

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1753 stars · 542 forks observed · 2026-08-28

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

An MXNet implementation of the Mask R-CNN instance segmentation model, built on top of the mx-rcnn Faster R-CNN codebase. It includes training, evaluation, and demo scripts targeting the Cityscapes dataset with a ResNet-50-FPN backbone.

Use cases

• train a Mask R-CNN model on Cityscapes with MXNet
• run instance segmentation on single images
• evaluate instance segmentation mAP on Cityscapes val/test
• republish ROIAlign operator in a custom MXNet build
• use a pretrained Mask R-CNN model for demo inference

When to choose

• you need Mask R-CNN specifically on MXNet rather than PyTorch or TensorFlow
• you are working with Cityscapes-style urban scene segmentation
• you want a reference implementation based on mx-rcnn

When to avoid

• you need COCO training, which was never completed
• you want an actively maintained implementation
• you are on Python 3 or modern MXNet versions, since it targets Python 2.7 and a patched MXNet build

Facets

library · maturity abandoned

machine-learning deep-learning computer-vision image-processing computer-vision machine-learning deep-learning image-processing python mask-rcnn instance-segmentation mxnet object-detection cityscapes coco linux gpu

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For agents

markdown · JSON · MCP: product_card(name="TuSimple/mx-maskrcnn")