cmdbug/YOLOv5_NCNN
Mobile deployment toolkit for computer vision models including YOLOv5, YOLOv4, NanoDet, DBFace, and pose estimation using ncnn.
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This repository provides deployment solutions for various deep learning computer vision models on mobile platforms. It supports running object detection models (YOLOv5s, YOLOv4-tiny, NanoDet, YOLO-Fastest), instance segmentation (Yolact), pose estimation (Simple-Pose), face detection (DBFace, Landmark106), and OCR (ChineseOCR-lite) on Android and iOS devices. The deployment uses the ncnn neural network inference framework optimized for mobile hardware.
Frequently asked
- What is cmdbug/YOLOv5_NCNN?
- Mobile deployment toolkit for computer vision models including YOLOv5, YOLOv4, NanoDet, DBFace, and pose estimation using ncnn.
- Is YOLOv5_NCNN open source?
- Yes — cmdbug/YOLOv5_NCNN is open source, released under the GPL-3.0 license.
- What language is YOLOv5_NCNN written in?
- cmdbug/YOLOv5_NCNN is primarily written in C++.
- How popular is YOLOv5_NCNN?
- cmdbug/YOLOv5_NCNN has 1.6k stars on GitHub.
- Where can I find YOLOv5_NCNN?
- cmdbug/YOLOv5_NCNN is on GitHub at https://github.com/cmdbug/YOLOv5_NCNN.