openface/tests/openface_api_tests.py

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# OpenFace API tests.
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#
# Copyright 2015-2016 Carnegie Mellon University
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#
# 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 cv2
import os
import numpy as np
np.set_printoptions(precision=2)
import scipy
import scipy.spatial
import openface
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openfaceDir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
modelDir = os.path.join(openfaceDir, 'models')
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dlibModelDir = os.path.join(modelDir, 'dlib')
openfaceModelDir = os.path.join(modelDir, 'openface')
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exampleImages = os.path.join(openfaceDir, 'images', 'examples')
lfwSubset = os.path.join(openfaceDir, 'data', 'lfw-subset')
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dlibFacePredictor = os.path.join(dlibModelDir,
"shape_predictor_68_face_landmarks.dat")
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model = os.path.join(openfaceModelDir, 'nn4.small2.v1.t7')
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imgDim = 96
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align = openface.AlignDlib(dlibFacePredictor)
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net = openface.TorchNeuralNet(model, imgDim=imgDim)
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def test_pipeline():
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imgPath = os.path.join(exampleImages, 'lennon-1.jpg')
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bgrImg = cv2.imread(imgPath)
if bgrImg is None:
raise Exception("Unable to load image: {}".format(imgPath))
rgbImg = cv2.cvtColor(bgrImg, cv2.COLOR_BGR2RGB)
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# assert np.isclose(norm(rgbImg), 11.1355)
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bb = align.getLargestFaceBoundingBox(rgbImg)
print ("Bounding box found was: ")
print (bb)
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assert bb.left() == 341
assert bb.right() == 1006
assert bb.top() == 193
assert bb.bottom() == 859
alignedFace = align.align(imgDim, rgbImg, bb,
landmarkIndices=openface.AlignDlib.OUTER_EYES_AND_NOSE)
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# assert np.isclose(norm(alignedFace), 7.61577)
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rep = net.forward(alignedFace)
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cosDist = scipy.spatial.distance.cosine(rep, np.ones(128))
print(cosDist)
assert np.isclose(cosDist, 0.938840385931)