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Python library RetinaFace for face detection and working with key points (eyes, nose, mouth)

Supports face alignment, easily installed via pip install retina-face, and works based on deep models from the insightface project.

An excellent tool for tasks in computer vision and face recognition.

Usage examples:

from retinaface import RetinaFace

resp = RetinaFace.detect_faces("img1.jpg")
print(resp)

{
"face_1": {
"score": 0.9993440508842468,
"facial_area": [155, 81, 434, 443],
"landmarks": {
"right_eye": [257.82974, 209.64787],
"left_eye": [374.93427, 251.78687],
"nose": [303.4773, 299.91144],
"mouth_right": [228.37329, 338.73193],
"mouth_left": [320.21982, 374.58798]
}
}
}


👉 @DataScienceN
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Python library RetinaFace for face detection and working with key points (eyes, nose, mouth)

Supports face alignment, easily installed via pip install retina-face, and works based on deep models from the insightface project.

An excellent tool for tasks in computer vision and face recognition.

Usage examples:

from retinaface import RetinaFace

resp = RetinaFace.detect_faces("img1.jpg")
print(resp)

{
"face_1": {
"score": 0.9993440508842468,
"facial_area": [155, 81, 434, 443],
"landmarks": {
"right_eye": [257.82974, 209.64787],
"left_eye": [374.93427, 251.78687],
"nose": [303.4773, 299.91144],
"mouth_right": [228.37329, 338.73193],
"mouth_left": [320.21982, 374.58798]
}
}
}


👉 @DataScienceN

BY Python | Machine Learning | Coding | R




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