Metadata-Version: 2.4
Name: academic_emotion
Version: 0.1.2
Summary: Emotion analysis tools for academic workflows
Author-email: Hanqing Tian <hanqingt@student.unimelb.edu.au>
License: MIT
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: deepface==0.0.80
Requires-Dist: torch==2.1.1
Requires-Dist: transformers==4.37.0
Requires-Dist: opencv-python==4.8.1.78
Requires-Dist: Pillow==10.1.0
Requires-Dist: numpy==1.23.5
Requires-Dist: tensorflow==2.10.1
Requires-Dist: keras==2.10.0
Requires-Dist: retina-face==0.0.17
Requires-Dist: mtcnn==0.1.1
Requires-Dist: pandas==1.5.3
Provides-Extra: dev
Requires-Dist: pytest>=7; extra == "dev"
Requires-Dist: ruff>=0.5; extra == "dev"
Requires-Dist: black>=24.0; extra == "dev"
Requires-Dist: ipykernel; extra == "dev"
Dynamic: license-file

# academic-emotion

Emotion analysis tools for academic conference videos built on DeepFace, PyTorch, and Transformers.

This project provides a lightweight, reproducible setup for experimenting with facial emotion recognition with video inputs.
---

## Demo

Below are example facial emotion from one coauther's conference presentation:

  Left to right: neutral, little happy, very happy

---

## Installation

Please create a new environment to install (Python ≥ 3.10 is required):

```bash
pip install academic_emotion
