Spaces:
Sleeping
Sleeping
File size: 2,894 Bytes
0cdca51 e9c150f 94fcc86 e9c150f 94fcc86 e9c150f 94fcc86 e9c150f 94fcc86 e9c150f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 |
---
title: PersonaMind – ML Model for Extrovert vs Introvert Classification
emoji: 🧠
colorFrom: blue
colorTo: red
sdk: streamlit
sdk_version: "1.40.0" # latest stable streamlit
app_file: app.py
pinned: false
license: mit
---
# PersonalityClassifier — Introvert vs Extrovert Predictor
A lightweight Streamlit app that predicts whether a person is likely an Introvert or Extrovert from simple daily-behavior inputs.
---
## Table of Contents
- **[Demo](#demo)**
- **[Features](#features)**
- **[Installation / Setup](#installation--setup)**
- **[Usage](#usage)**
- **[Configuration / Options](#configuration--options)**
- **[Contributing](#contributing)**
- **[License](#license)**
- **[Acknowledgements / Credits](#acknowledgements--credits)**
---
## Demo
Real demo assets found in `./demo/`:
- Image: `./demo/demo.png`
- Video: `./demo/demo.mp4`
Example render:
If your viewer supports video playback in Markdown, you can also preview the short clip:
```text
./demo/demo.mp4
```
---
## Features
- **Simple UI** built with `streamlit` for quick interaction.
- **Preprocessing utilities** in `utils.py` convert raw inputs to model-ready features.
- **Saved model loading** via `joblib` from `./models/model.pkl`.
- **Deterministic inference** using a binary classifier (Introvert vs Extrovert).
---
## Installation / Setup
Use a Python virtual environment for isolation.
```bash
# Create a virtual environment
python -m venv .venv
# Activate it
# On Linux/Mac:
source .venv/bin/activate
# On Windows:
.venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
```
---
## Usage
Run the Streamlit app locally:
```bash
streamlit run app.py
```
App entrypoint: `app.py`
- Loads the model using `utils.load_model("./models/model.pkl")`.
- Renders inputs and predictions using helpers in `ui.py`.
Expected project structure:
```
PersonalityClassifier/
├─ app.py
├─ ui.py
├─ utils.py
├─ models/
│ └─ model.pkl
└─ demo/
├─ demo.png
└─ demo.mp4
```
---
## Configuration / Options
- **Model path**: `./models/model.pkl` (default in `app.py`). Replace the file if you want another trained model. Ensure the environment includes the libraries used to train/serialize it (e.g., `scikit-learn`).
- **Caching**: `utils.load_model` uses `@st.cache_resource` to cache the loaded model across reruns.
---
## Contributing
Contributions are welcome! Please:
- **Open an issue** to discuss proposed changes.
- **Create a PR** with a clear description, small focused commits, and screenshots for UI changes.
---
## License
This project is licensed under the **MIT License**. See the [`LICENSE`](./LICENSE) file for details.
---
## Acknowledgements / Credits
- **Streamlit** for rapid web UI development.
- **scikit-learn** and **joblib** for model training/serialization workflows.
|