File size: 1,010 Bytes
ab1b805 6e059fd ab1b805 6e059fd ab1b805 1507bf1 ab1b805 1507bf1 ab1b805 1507bf1 | 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 | ---
title: Facial Keypoints Detection
emoji: 🚀
colorFrom: red
colorTo: red
sdk: docker
app_port: 8501
tags:
- streamlit
pinned: false
short_description: Streamlit template space
---
# 🧠 Facial Keypoints Detection
A Streamlit application that predicts facial keypoints using a trained ResNet model.
---
## 📌 What this app does
- Upload a face image
- Converts image to grayscale
- Resizes to 96x96
- Predicts facial keypoints (eyes, nose, mouth, etc.)
- Visualizes the keypoints directly on the image
---
## 🖼 Example Workflow
1. Upload a front-facing face image
2. Model predicts keypoints
3. Red dots appear on facial landmarks
---
## 🏗 Model
- Architecture: ResNet-based CNN
- Input shape: 96x96 grayscale
- Output: (x, y) coordinates for facial landmarks
- Loss used during training: MSE
---
## 🛠 Tech Stack
- Streamlit
- TensorFlow / Keras
- NumPy
- Matplotlib
- Pillow
---
## 🚀 Run locally
```bash
pip install -r requirements.txt
streamlit run src/streamlit_app.py
|