Bob interface for mtcnn face and landmark detection¶
This package binds the face and landmark detection from the paper:
- @ARTICLE{7553523,
author={K. Zhang and Z. Zhang and Z. Li and Y. Qiao}, journal={IEEE Signal Processing Letters}, title={Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks}, year={2016}, volume={23}, number={10}, pages={1499-1503}, keywords={Benchmark testing;Computer architecture;Convolution;Detectors;Face;Face detection;Training;Cascaded convolutional neural network (CNN);face alignment;face detection}, doi={10.1109/LSP.2016.2603342}, ISSN={1070-9908}, month={Oct},}
User guide¶
Face Detection and Landmark detection¶
The most simple face detection task is to detect a single face in an image. This task can be achieved using a single command:
>>> import bob.ip.mtcnn
>>> import bob.io.base
>>> import bob.io.base.test_utils
>>> color_image = bob.io.base.load(bob.io.base.test_utils.datafile('testimage.jpg', 'bob.ip.facedetect'))
>>> bounding_box, landmarks = bob.ip.mtcnn.FaceDetector().detect_single_face(color_image)
>>> print(bounding_box.topleft)
(64, 77)
(Source code, png, hires.png, pdf)
Multiple Face Detection¶
The detection of multiple faces can be achieved with a single command:
>>> import bob.ip.mtcnn
>>> import bob.io.base
>>> import bob.io.base.test_utils
>>> color_image = bob.io.base.load(bob.io.base.test_utils.datafile('multiple-faces.jpg', 'bob.ip.mtcnn'))
>>> bounding_box, landmarks = bob.ip.mtcnn.FaceDetector().detect_all_faces(color_image)
>>> print ((bounding_box[0].topleft, bounding_box[0].bottomright))
((28, 189), (102, 244))
(Source code, png, hires.png, pdf)
Landmark detection¶
The detection of landmarks can be done as the following:
>>> import bob.ip.mtcnn
>>> import bob.io.base
>>> import bob.io.base.test_utils
>>> color_image = bob.io.base.load(bob.io.base.test_utils.datafile('testimage.jpg', 'bob.ip.facedetect'))
>>> bounding_box, landmarks = bob.ip.mtcnn.FaceDetector().detect_single_face(color_image)
>>> print (landmarks['leye'])
(174, 219)
Face genometric normalization¶
The detection of landmarks can be done as the following:
>>> import bob.ip.mtcnn
>>> import bob.io.base
>>> import bob.io.base.test_utils
>>> color_image = bob.io.base.load(bob.io.base.test_utils.datafile('testimage.jpg', 'bob.ip.facedetect'))
>>> color_image_norm = bob.ip.mtcnn.FaceDetector().detect_crop(color_image, final_image_size=(224, 224))
>>> color_image_norm_align = bob.ip.mtcnn.FaceDetector().detect_crop_align(color_image, final_image_size=(224, 224))
(Source code, png, hires.png, pdf)
