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