nmr-classifier

Jisun Kang

nmr-classifier is a Python (2 and 3) library to implement the nuclear norm regression for classification. This package uses facial structural information to recognize facial images.

Install

You can use pip to install nmr-classifier.

# install
pip install nmr_classifier

# update
pip install --update nmr_classifier

# check
import nmr_classifier

Resource

• https://pypi.org/project/nmr-classifier/

Example

Here is an example using the Oliveti data set.

# import olivetti dataset
from sklearn.datasets import fetch_olivetti_faces
olivetti = fetch_olivetti_faces()

# create occlusion
num=91; n = 400; occlusion_percent = 0.2; 
black_size = round(test_img.shape[1]*occlusion_percent)
loc = random.randint(0,64-black_size)
test_img[loc:loc+black_size,loc:loc+black_size] = np.zeros((black_size,black_size))

# create target vector
target = list(olivetti.target)

# import classifier
from nmr_classifier.fast_admm_nmr_classifier import nmr_classifier

# define classifier
clf = nmr_classifier()

# fitting dataset
clf.fit(train_img, test_img)

# classification
clf.classifier(train_img, test_img, num, target)

For detailed introduction and tutorial, please see "doc_nmr-classifier" (https://github.com/riverKangg/nmr_classifier/blob/master/doc_nmr-classifier.py)

Update

• 0.2.4 : nmr_reconstruction