Tools implemented in bob.bio.caffe_face¶

Summary¶

Face Image Feature Extractors¶

`bob.bio.caffe_face.extractor.VGGFeatures`([…])	Extract features using the VGG model http://www.robots.ox.ac.uk/~vgg/software/vgg_face/
`bob.bio.caffe_face.extractor.LightCNNExtractor`([…])	Feature extractor of face images using the LightCNNExtractor Caffe model.

Face Image Preprocessors¶

Several preprocessors are also available in this package that are recommended to use with the implemented feature extractors in this package: 'face-detect-vgg', 'face-eyes-vgg', 'face-detect-lightcnn', 'face-eyes-lightcnn'.

Detailed API¶

bob.bio.caffe_face.get_config()[source]¶: Returns a string containing the configuration information.

class bob.bio.caffe_face.extractor.LightCNNExtractor(end_cnn='eltwise_fc1', model_version='LightenedCNN_C')¶

Bases: bob.bio.base.extractor.Extractor

Feature extractor of face images using the LightCNNExtractor Caffe model. For more information please see bob.ip.caffe_extractor.LightCNN

end_cnn¶

The name of the layer that you want to use as a feature.

Type: str, optional

feature_extractor¶

The instance of feature extractor.

Type: bob.ip.caffe_extractor.LightCNN

model_version¶

Which model to use.

Type: str, optional

__call__(image)[source]¶

Extracts features given a gray face image.

Parameters: image (numpy.array) – The gray image. Please see bob.ip.caffe_extractor.LightCNN.__call__ for the required format. For convenience, if the image range is [0,255], it is divided by 255. This assumes that the original image is an int8 image but be careful when relying on this feature.
Returns: The extracted features.
Return type: numpy.array
Raises: ValueError – If the image is not within [0,1] range.

__init__(end_cnn='eltwise_fc1', model_version='LightenedCNN_C')[source]¶: Initialize self. See help(type(self)) for accurate signature.

class bob.bio.caffe_face.extractor.VGGFeatures(feature_layer='fc7')¶

Bases: bob.bio.base.extractor.Extractor

Extract features using the VGG model http://www.robots.ox.ac.uk/~vgg/software/vgg_face/

Parameters:

feature_layer: The layer to be used as features. Possible values are fc6, fc7 or fc8.

__call__(image) → feature[source]¶

Extract features

Parameters:

image3D numpy.ndarray (floats): The image to extract the features from.

Returns:

feature2D numpy.ndarray (floats): The extracted features

__init__(feature_layer='fc7')[source]¶: Initialize self. See help(type(self)) for accurate signature.