https://github.com/ck-zhang/eyepy
EyePy is an eye tracking library easily implementable in your projcets
https://github.com/ck-zhang/eyepy
eye-tracking gaze-track mediapipe opencv python
Last synced: 3 months ago
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EyePy is an eye tracking library easily implementable in your projcets
- Host: GitHub
- URL: https://github.com/ck-zhang/eyepy
- Owner: ck-zhang
- License: mit
- Created: 2024-09-28T14:06:09.000Z (10 months ago)
- Default Branch: master
- Last Pushed: 2024-10-18T05:20:29.000Z (9 months ago)
- Last Synced: 2024-10-18T12:56:32.493Z (9 months ago)
- Topics: eye-tracking, gaze-track, mediapipe, opencv, python
- Language: Python
- Homepage:
- Size: 57.6 KB
- Stars: 41
- Watchers: 4
- Forks: 4
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# EyePy
EyePy is a Python library that provides **webcam-based eye tracking**.
Extract facial features, train eye tracking model and predict gaze with super easy to use interface.
The repo also includes a virtual camera script allowing integration with streaming software like OBS.
## Installation
Clone this project:
```shell
git clone https://github.com/ck-zhang/EyePy
```
### Using Pip
```shell
python -m venv venv
source venv/bin/activate # On Windows use: venv\Scripts\activate
pip install -r requirements.txt
```
### Using uv
```shell
# Install uv https://github.com/astral-sh/uv/?tab=readme-ov-file#installation
pip install uv
uv sync
source venv/bin/activate # On Windows use: venv\Scripts\activate
```
## Demo
To run the gaze estimation demo:
```bash
python demo.py [OPTIONS]
```
### Options
| Option | Description | Default |
|-------------------|--------------------------------------------------|---------------------|
| `--filter` | Filter method (`kalman`, `kde`, `none`) | `none` |
| `--camera` | Index of the camera to use | `0` |
| `--calibration` | Calibration method (`9p`, `5p`, `lissajous`) | `9p` |
| `--background` | Path to background image | None |
| `--confidence` | Confidence interval for KDE contours (0 to 1) | `0.5` |
## Virtual Camera Script (only tested on linux)
```bash
python virtual_cam.py [OPTIONS]
```
### Virtual Camera Options
| Option | Description | Default |
|-------------------|--------------------------------------------------|---------------------|
| `--filter` | Filter method (`kalman`, `kde`, `none`) | `none` |
| `--camera` | Index of the camera to use | `0` |
| `--calibration` | Calibration method (`9p`, `5p`, `lissajous`) | `9p` |
| `--confidence` | Confidence interval for KDE contours (0 to 1) | `0.5` |
### Virtual camera demo
https://github.com/user-attachments/assets/7337f28c-6ce6-4252-981a-db77db5509f6
## Usage as library
### Initialization
```python
from EyePy import GazeEstimator
gaze_estimator = GazeEstimator()
```
### Feature Extraction
```python
import cv2
image = cv2.imread('image.jpg')
features, blink_detected = gaze_estimator.extract_features(image)
if features is None:
print("No face detected.")
elif blink_detected:
print("Blink detected!")
else:
print("Extracted features:", features)
```
### Training the Model
```python
X = [[...], [...], ...] # Each element is a feature vector
y = [[x1, y1], [x2, y2], ...] # Corresponding gaze coordinates
gaze_estimator.train(X, y)
```
### Predicting Gaze Location
```python
predicted_gaze = gaze_estimator.predict([features])
print("Predicted gaze coordinates:", predicted_gaze[0])
```
## Future Work
### TODO
- [x] Virtual camera script ~~Integrate with OBS~~
- [ ] Integrate with opentrack
Any suggestions for features and improvements are welcome.
If you enjoyed using EyePy, consider giving it a star.