Implementation of the MTCNN face detection algorithm. This project converted the code from ipazc/mtcnn to TF Lite.
You can install the package through pip:
pip install mtcnn-tflite
Similar to the original implementation, the following example illustrates the ease of use of this package:
>>> from mtcnn_tflite.MTCNN import MTCNN
>>> import cv2
>>>
>>> img = cv2.cvtColor(cv2.imread("ivan.jpg"), cv2.COLOR_BGR2RGB)
>>> detector = MTCNN()
>>> detector.detect_faces(img)
[
{
'box': [276, 88, 51, 68],
'confidence': 0.9989245533943176,
'keypoints': {
'left_eye': (291, 117),
'right_eye': (314, 114),
'nose': (303, 130),
'mouth_left': (296, 143),
'mouth_right': (314, 141)
}
}
]
| Image size | TF version | Process time * |
|---|---|---|
| 561x561 | TF2 | 698ms |
| 561x561 | This repository (TF Lite) | 445ms |
* executed on a CPU: Intel i7-10510U
This work has been carried out within the scope of Digidow, the Christian Doppler Laboratory for Private Digital Authentication in the Physical World, funded by the Christian Doppler Forschungsgesellschaft, 3 Banken IT GmbH, Kepler Universitätsklinikum GmbH, NXP Semiconductors Austria GmbH, and Österreichische Staatsdruckerei GmbH and has partially been supported by the LIT Secure and Correct Systems Lab funded by the State of Upper Austria.