78 lines
2.4 KiB
Python
78 lines
2.4 KiB
Python
# OpenFace batch-represent tests.
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#
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# Copyright 2015 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 shutil
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import tempfile
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import numpy as np
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np.set_printoptions(precision=2)
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import pandas as pd
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import scipy
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import scipy.spatial
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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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modelDir = os.path.join(openfaceDir, 'models')
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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_batch_represent():
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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='OpenFaceBatchRep-')
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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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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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assert p.returncode == 0
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fname = os.path.join(workDir, 'reps', 'labels.csv')
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labels = pd.read_csv(fname, header=None).as_matrix()
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fname = os.path.join(workDir, 'reps', 'reps.csv')
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embeddings = pd.read_csv(fname, header=None).as_matrix()
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brody1 = brody2 = None
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for i, (cls, label) in enumerate(labels):
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print(label)
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if "Brody_0001" in label:
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brody1 = embeddings[i]
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elif "Brody_0002" in label:
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brody2 = embeddings[i]
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assert brody1 is not None
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assert brody2 is not None
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cosDist = scipy.spatial.distance.cosine(brody1, brody2)
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print(cosDist)
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assert np.isclose(cosDist, 0.113500484192)
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shutil.rmtree(workDir)
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