dog-qiuqiu/MobileNet-Yolo
Lightweight YOLOv3 object detection models using MobileNetV2 backbone, optimized for mobile deployment with NCNN and MNN inference frameworks.
Not currently ranked — collecting fresh signals.
star history
This repository provides MobileNetV2-YOLOv3-Lite and Nano variants optimized for real-time object detection on mobile devices. It implements depthwise separable convolutions from MobileNetV2 to reduce computational cost (0.5BFlops) while maintaining reasonable accuracy. The project supports face detection with landmark regression and provides C language samples for NCNN deployment, targeting ARM processors on devices like Huawei P40.
Frequently asked
- What is dog-qiuqiu/MobileNet-Yolo?
- Lightweight YOLOv3 object detection models using MobileNetV2 backbone, optimized for mobile deployment with NCNN and MNN inference frameworks.
- Is MobileNet-Yolo open source?
- Yes — dog-qiuqiu/MobileNet-Yolo is an open-source project tracked on heatdrop.
- What language is MobileNet-Yolo written in?
- dog-qiuqiu/MobileNet-Yolo is primarily written in C.
- How popular is MobileNet-Yolo?
- dog-qiuqiu/MobileNet-Yolo has 1.7k stars on GitHub.
- Where can I find MobileNet-Yolo?
- dog-qiuqiu/MobileNet-Yolo is on GitHub at https://github.com/dog-qiuqiu/MobileNet-Yolo.