123 lines
4.2 KiB
Python
123 lines
4.2 KiB
Python
# OpenFace demo tests.
|
|
#
|
|
# Copyright 2015-2016 Carnegie Mellon University
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
|
|
import os
|
|
import re
|
|
import shutil
|
|
import tempfile
|
|
|
|
from subprocess import Popen, PIPE
|
|
|
|
openfaceDir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
|
|
exampleImages = os.path.join(openfaceDir, 'images', 'examples')
|
|
lfwSubset = os.path.join(openfaceDir, 'data', 'lfw-subset')
|
|
|
|
|
|
def test_compare_demo():
|
|
cmd = ['python2', os.path.join(openfaceDir, 'demos', 'compare.py'),
|
|
os.path.join(exampleImages, 'lennon-1.jpg'),
|
|
os.path.join(exampleImages, 'lennon-2.jpg')]
|
|
p = Popen(cmd, stdout=PIPE, stderr=PIPE)
|
|
(out, err) = p.communicate()
|
|
print(out)
|
|
print(err)
|
|
assert "0.763" in out
|
|
|
|
|
|
def test_classification_demo_pretrained():
|
|
cmd = ['python2', os.path.join(openfaceDir, 'demos', 'classifier.py'),
|
|
'infer',
|
|
os.path.join(openfaceDir, 'models', 'openface',
|
|
'celeb-classifier.nn4.small2.v1.pkl'),
|
|
os.path.join(exampleImages, 'carell.jpg')]
|
|
p = Popen(cmd, stdout=PIPE, stderr=PIPE)
|
|
(out, err) = p.communicate()
|
|
print(out)
|
|
print(err)
|
|
assert "Predict SteveCarell with 0.97 confidence." in out
|
|
|
|
|
|
def test_classification_demo_pretrained_multi():
|
|
cmd = ['python2', os.path.join(openfaceDir, 'demos', 'classifier.py'),
|
|
'infer', '--multi',
|
|
os.path.join(openfaceDir, 'models', 'openface',
|
|
'celeb-classifier.nn4.small2.v1.pkl'),
|
|
os.path.join(exampleImages, 'longoria-cooper.jpg')]
|
|
p = Popen(cmd, stdout=PIPE, stderr=PIPE)
|
|
(out, err) = p.communicate()
|
|
print(out)
|
|
print(err)
|
|
assert "Predict EvaLongoria @ x=91 with 0.99 confidence." in out
|
|
assert "Predict BradleyCooper @ x=191 with 0.99 confidence." in out
|
|
|
|
|
|
def test_classification_demo_training():
|
|
assert os.path.isdir(lfwSubset), "Get lfw-subset by running ./data/download-lfw-subset.sh"
|
|
|
|
workDir = tempfile.mkdtemp(prefix='OpenFaceCls-')
|
|
|
|
cmd = ['python2', os.path.join(openfaceDir, 'util', 'align-dlib.py'),
|
|
os.path.join(lfwSubset, 'raw'), 'align', 'outerEyesAndNose',
|
|
os.path.join(workDir, 'aligned')]
|
|
p = Popen(cmd, stdout=PIPE, stderr=PIPE)
|
|
(out, err) = p.communicate()
|
|
print(out)
|
|
print(err)
|
|
assert p.returncode == 0
|
|
|
|
cmd = ['python2', os.path.join(openfaceDir, 'util', 'align-dlib.py'),
|
|
os.path.join(lfwSubset, 'raw'), 'align', 'outerEyesAndNose',
|
|
os.path.join(workDir, 'aligned')]
|
|
p = Popen(cmd, stdout=PIPE, stderr=PIPE)
|
|
(out, err) = p.communicate()
|
|
print(out)
|
|
print(err)
|
|
assert p.returncode == 0
|
|
|
|
cmd = ['th', './batch-represent/main.lua',
|
|
'-data', os.path.join(workDir, 'aligned'),
|
|
'-outDir', os.path.join(workDir, 'reps')]
|
|
p = Popen(cmd, stdout=PIPE, stderr=PIPE)
|
|
(out, err) = p.communicate()
|
|
print(out)
|
|
print(err)
|
|
assert p.returncode == 0
|
|
|
|
cmd = ['python2', os.path.join(openfaceDir, 'demos', 'classifier.py'),
|
|
'train',
|
|
os.path.join(workDir, 'reps')]
|
|
p = Popen(cmd, stdout=PIPE, stderr=PIPE)
|
|
(out, err) = p.communicate()
|
|
print(out)
|
|
print(err)
|
|
assert p.returncode == 0
|
|
|
|
cmd = ['python2', os.path.join(openfaceDir, 'demos', 'classifier.py'),
|
|
'infer',
|
|
os.path.join(workDir, 'reps', 'classifier.pkl'),
|
|
os.path.join(lfwSubset, 'raw', 'Adrien_Brody', 'Adrien_Brody_0001.jpg')]
|
|
p = Popen(cmd, stdout=PIPE, stderr=PIPE)
|
|
(out, err) = p.communicate()
|
|
print(out)
|
|
print(err)
|
|
m = re.search('Predict (.*) with (.*) confidence', out)
|
|
assert m is not None
|
|
assert m.group(1) == 'Adrien_Brody'
|
|
assert float(m.group(2)) >= 0.80
|
|
|
|
shutil.rmtree(workDir)
|