Source code for wbia_cnn.test

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
tests a test set of data using a specified, pre0trained model and weights
"""
from __future__ import absolute_import, division, print_function
from wbia_cnn import utils
import utool as ut
import six  # NOQA

print, rrr, profile = ut.inject2(__name__)


[docs]def test( data_fpath, model, weights_fpath, results_dpath=None, labels_fpath=None, **kwargs ): """ Driver function Args: data_fpath (?): labels_fpath (?): model (?): weights_fpath (?): """ ###################################################################################### # Load the data print('\n[data] loading data...') print('data_fpath = %r' % (data_fpath,)) X_test, y_test = utils.load(data_fpath, labels_fpath) if len(X_test.shape) == 3: # add channel dimension for implicit grayscale X_test.shape = X_test.shape + (1,)
# return test_data(X_test, y_test, model, weights_fpath, results_dpath, **kwargs) if __name__ == '__main__': """ CommandLine: python -m wbia_cnn.test python -m wbia_cnn.test --allexamples python -m wbia_cnn.test --allexamples --noface --nosrc CommandLine: cd %CODE_DIR%/wbia_cnn/code cd $CODE_DIR/wbia_cnn/code code cd wbia_cnn/code python test.py PythonPrereqs: pip install theano pip install git+https://github.com/Lasagne/Lasagne.git pip install git+git://github.com/lisa-lab/pylearn2.git #pip install lasagne #pip install pylearn2 git clone git://github.com/lisa-lab/pylearn2.git git clone https://github.com/Lasagne/Lasagne.git cd pylearn2 python setup.py develop cd .. cd Lesagne git checkout 8758ac1434175159e5c1f30123041799c2b6098a python setup.py develop """ import multiprocessing multiprocessing.freeze_support() # for win32 import utool as ut # NOQA ut.doctest_funcs()