# Mini-face
## Installation with pip
> Requirements: `python 3.12`, `numpy >= 1.21`.
1. Install the package with a following command:
```
python3 -m pip install mini-face
```
2. Download model data files (subdirectories **/model/** and **/AU_predictors/**) from this repository or official
<a href="https://github.com/TadasBaltrusaitis/OpenFace/releases" title="OpenFace releases">OpenFace release</a>.
You will also need files from <a href="https://github.com/TadasBaltrusaitis/OpenFace/wiki/Model-download" title="OpenFace models">here</a>.
## Python usage
Below is a minimalist example of using the module from Python code:
```
import cv2
import numpy as np
from mini_face import GazeFeatureExtractor
from mini_face import PredictionMode
if __name__ == "__main__":
image = cv2.imread("test_image.jpg")
extractor = GazeFeatureExtractor(
mode=PredictionMode.IMAGE,
focal_length=(500, 500),
optical_center=(860.0, 540.0),
models_directory="./model",
)
result = extractor.predict(image, np.array([0.0, 0.0, 1080.0, 1920.0]))
print(f"{result = }")
```
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"description": "# Mini-face\r\n\r\n## Installation with pip\r\n> Requirements: `python 3.12`, `numpy >= 1.21`.\r\n1. Install the package with a following command:\r\n```\r\n python3 -m pip install mini-face\r\n```\r\n2. Download model data files (subdirectories **/model/** and **/AU_predictors/**) from this repository or official\r\n <a href=\"https://github.com/TadasBaltrusaitis/OpenFace/releases\" title=\"OpenFace releases\">OpenFace release</a>.\r\n You will also need files from <a href=\"https://github.com/TadasBaltrusaitis/OpenFace/wiki/Model-download\" title=\"OpenFace models\">here</a>.\r\n\r\n## Python usage\r\nBelow is a minimalist example of using the module from Python code:\r\n\r\n```\r\n import cv2\r\n import numpy as np\r\n from mini_face import GazeFeatureExtractor\r\n from mini_face import PredictionMode\r\n\r\n if __name__ == \"__main__\":\r\n image = cv2.imread(\"test_image.jpg\")\r\n extractor = GazeFeatureExtractor(\r\n mode=PredictionMode.IMAGE,\r\n focal_length=(500, 500),\r\n optical_center=(860.0, 540.0),\r\n models_directory=\"./model\",\r\n )\r\n\r\n result = extractor.predict(image, np.array([0.0, 0.0, 1080.0, 1920.0]))\r\n\r\n print(f\"{result = }\")\r\n```\r\n",
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