chuanqi305/MobileNet-SSD

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2127 stars · 1167 forks observed · 2026-08-28

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

A Caffe implementation of the MobileNet-SSD object detection network with pretrained weights on the VOC0712 dataset achieving mAP of 0.727. It includes scripts for running detection demos, creating LMDB datasets, and fine-tuning the model on custom datasets.

Use cases

• run object detection with a fast lightweight model
• fine-tune SSD object detection on my own dataset
• get pretrained MobileNet-SSD weights for Caffe
• convert my labeled images to LMDB for SSD training
• deploy real-time object detection on resource-constrained devices
• reproduce MobileNet-SSD training results in Caffe

When to choose

• you need a lightweight, fast object detection model in the Caffe framework
• you want pretrained VOC0712 weights to fine-tune on a custom dataset
• you are targeting embedded or mobile deployment where speed matters

When to avoid

• you prefer PyTorch or TensorFlow instead of Caffe
• you need state-of-the-art detection accuracy rather than speed
• you need a maintained project with active updates and modern tooling

Facets

library · maturity maintenance

machine-learning computer-vision deep-learning computer-vision machine-learning deep-learning python cross-platform object-detection ssd mobilenet caffe pretrained-weights voc0712 model-training linux

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markdown · JSON · MCP: product_card(name="chuanqi305/MobileNet-SSD")