Face Pose Pytorch

🔥🔥The pytorch implement of the head pose estimation(yaw,roll,pitch) and emotion detection with SOTA performance in real time.Easy to deploy, easy to use, and high accuracy.Solve all problems of face detection at one time.(极简，极快，高效是我们的宗旨)

AI & Machine LearningPythonMIT

Abstract

Face Pose Pytorch is an open-source AI & Machine Learning project. 🔥🔥The pytorch implement of the head pose estimation(yaw,roll,pitch) and emotion detection with SOTA performance in real time.Easy to deploy, easy to use, and high accuracy.Solve all problems of face detection at one time.(极简，极快，高效是我们的宗旨). It is built using Python, PyTorch. The complete source code is publicly available on GitHub under the MIT License, making it a useful reference for students building an AI & Machine Learning mini project or final-year project.

1. Introduction

The pytorch implement of the head pose estimation(yaw,roll,pitch) and emotion detection with SOTA performance in real time.Easy to deploy, easy to use, and high accuracy.Solve all problems of face detection at one time.(极简，极快，高效是我们的宗旨)

The head angle, especially the accuracy of facial emotion recognition, has reached the world's top level. However, for some reasons, we only open source prediction code.

We will release the ultra-high precision model in future(Including angles and emotion). If you need, please add a github star and leave email, I will send it to you separately.

2. Objective

🔥🔥The pytorch implement of the head pose estimation(yaw,roll,pitch) and emotion detection with SOTA performance in real time.Easy to deploy, easy to use, and high accuracy.Solve all problems of face detection at one time.(极简，极快，高效是我们的宗旨)

This project demonstrates how Python, PyTorch can be applied to a real-world AI & Machine Learning problem.

4. Technology Stack

PythonPyTorch

5. System Requirements

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

  • Python 3.8 or later
  • pip / virtualenv for dependencies
  • VS Code, PyCharm or Jupyter Notebook
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/WIKI2020/FacePose_pytorch.git
cd FacePose_pytorch

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 WIKI2020 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.

View Source on GitHubDownload ZIP

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