# mini-face
## Installation with `pip`
> Requirements: `python >= 3.12`, `numpy >= 1.21`.
1. Install the package with a following command:
```shell
python3 -m pip install mini-face
```
2. Download model data files (`model` and `AU_predictors`) from this repository or official
[OpenFace release](https://github.com/TadasBaltrusaitis/OpenFace/releases).
You will also need files from [OpenFace models](https://github.com/TadasBaltrusaitis/OpenFace/wiki/Model-download).
## Example
To estimate gaze on a single image, simply run:
```python
from pathlib import Path
import cv2
import numpy as np
from mini_face import gaze, PredictionMode
if __name__ == "__main__":
extractor = gaze.Extractor(
mode=PredictionMode.IMAGE, # Specify prediction mode
focal_length=(500.0, 500.0), # Specify camera parameters
optical_center=(860.0, 540.0), # required for proper 3D estimation
models_directory=Path("./model"), # Pass a directory to search for OpenFace weights in
)
image = cv2.imread("test_image.jpg")
result = extractor.predict(
image, # Pass the image to analyze
np.array([0, 0, 1080, 1920]) # along with a region to search for face in
)
print(f"{result = }")
```
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"description": "# mini-face\n\n## Installation with `pip`\n> Requirements: `python >= 3.12`, `numpy >= 1.21`.\n1. Install the package with a following command:\n```shell\n python3 -m pip install mini-face\n```\n2. Download model data files (`model` and `AU_predictors`) from this repository or official\n [OpenFace release](https://github.com/TadasBaltrusaitis/OpenFace/releases).\n You will also need files from [OpenFace models](https://github.com/TadasBaltrusaitis/OpenFace/wiki/Model-download).\n\n## Example\nTo estimate gaze on a single image, simply run:\n\n```python\nfrom pathlib import Path\n\nimport cv2\nimport numpy as np\nfrom mini_face import gaze, PredictionMode\n\n\nif __name__ == \"__main__\":\n extractor = gaze.Extractor(\n mode=PredictionMode.IMAGE, # Specify prediction mode\n focal_length=(500.0, 500.0), # Specify camera parameters\n optical_center=(860.0, 540.0), # required for proper 3D estimation\n models_directory=Path(\"./model\"), # Pass a directory to search for OpenFace weights in\n )\n\n image = cv2.imread(\"test_image.jpg\")\n result = extractor.predict(\n image, # Pass the image to analyze\n np.array([0, 0, 1080, 1920]) # along with a region to search for face in\n )\n\n print(f\"{result = }\")\n```\n",
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