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()