tusen-ai/simpledet

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3085 stars · 481 forks observed · 2026-08-28

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

SimpleDet is a Python framework built on MXNet for object detection and instance recognition. It provides state-of-the-art detection models (FasterRCNN, MaskRCNN, RetinaNet, TridentNet, NASFPN, EfficientNet, etc.) with FP16 training and scalable distributed training out of the box.

Use cases

• train object detection models on COCO
• run instance segmentation with Mask R-CNN
• train detection models with FP16 mixed precision on GPU
• distributed multi-GPU object detection training
• benchmark state-of-the-art detection architectures like TridentNet and NASFPN
• fine-tune pretrained detection models on custom datasets
• knowledge distillation for detection models

When to choose

• you need a modular, config-driven detection framework on MXNet
• you want memory-efficient FP16 or INT8 training for detection
• you need out-of-the-box scalable distributed training
• you want broad coverage of detection and instance segmentation models in one codebase

When to avoid

• your stack is PyTorch or TensorFlow based
• you need actively maintained software - the last release was 2021
• you only need inference without training
• you work outside Linux/Ubuntu environments without Docker

Facets

framework · maturity maintenance

machine-learning deep-learning computer-vision image-processing gpu-computing computer-vision deep-learning machine-learning image-processing python object-detection instance-segmentation mxnet fp16-training distributed-training mask-rcnn faster-rcnn retinanet knowledge-distillation linux gpu docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="tusen-ai/simpledet")