Ncnn Example

Abstract

1. Introduction

ncnn example: mask detection: anticonv face detection: retinaface&&mtcnn&&centerface, track: iou tracking, landmark: zqcnn, recognize: mobilefacenet classifier: mobilenet object detecter: mobilenetssd

2. Objective

ncnn example: mask detection: anticonv face detection: retinaface&&mtcnn&&centerface, track: iou tracking, landmark: zqcnn, recognize: mobilefacenet classifier: mobilenet object detecter: mobilenetssd

This project demonstrates how C++ can be applied to a real-world AI & Machine Learning problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Arduino IDE / PlatformIO or a C++ compiler (g++)
• Target board (e.g. Arduino, ESP32) where applicable
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/MirrorYuChen/ncnn_example.git
cd ncnn_example

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Deploy the model as a web app with Streamlit, Flask or FastAPI
• Compare against an additional model and report the metric difference
• Add explainability (SHAP / Grad-CAM)

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What dataset does the project use and how was it pre-processed?
2. Which algorithm / model architecture is used and why was it chosen over alternatives?
3. How are training and testing data split, and how is overfitting avoided?
4. Which evaluation metrics (accuracy, precision, recall, F1) are reported and what do they mean here?
5. How would you deploy this model for real users?

9. Source Code & License

This project is developed by MirrorYuChen and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.