88 lines
2.8 KiB
Python
88 lines
2.8 KiB
Python
# OpenFace tests, run with `nosetests-2.7 -v -d test.py`
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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 cv2
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import os
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import numpy as np
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np.set_printoptions(precision=2)
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from numpy.linalg import norm
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import scipy
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import scipy.spatial
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import openface
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from subprocess import Popen, PIPE
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fileDir = os.path.dirname(os.path.realpath(__file__))
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modelDir = os.path.join(fileDir, 'models')
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dlibModelDir = os.path.join(modelDir, 'dlib')
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openfaceModelDir = os.path.join(modelDir, 'openface')
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dlibFacePredictor = os.path.join(dlibModelDir,
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"shape_predictor_68_face_landmarks.dat")
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networkModel = os.path.join(openfaceModelDir, 'nn4.v1.t7')
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imgDim = 96
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align = openface.AlignDlib(dlibFacePredictor)
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net = openface.TorchNeuralNet(networkModel, imgDim=imgDim)
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def test_pipeline():
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imgPath = os.path.join(fileDir, 'images', 'examples', 'lennon-1.jpg')
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bgrImg = cv2.imread(imgPath)
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if bgrImg is None:
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raise Exception("Unable to load image: {}".format(imgPath))
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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)
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assert bb.left() == 341
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assert bb.right() == 1006
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assert bb.top() == 193
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assert bb.bottom() == 859
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alignedFace = align.alignImg("affine", imgDim, rgbImg, bb)
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assert np.isclose(norm(alignedFace), 8.30662)
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rep = net.forwardImage(alignedFace)
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cosDist = scipy.spatial.distance.cosine(rep, np.ones(128))
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assert np.isclose(cosDist, 1.0133943701889758)
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def test_compare_demo():
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cmd = ['python2', os.path.join(fileDir, 'demos', 'compare.py'),
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os.path.join(fileDir, 'images', 'examples', 'lennon-1.jpg'),
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os.path.join(fileDir, 'images', 'examples', '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(err)
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assert "0.352" in out
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def test_classification_demo():
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cmd = ['python2', os.path.join(fileDir, 'demos', 'classifier.py'),
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'infer',
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os.path.join(fileDir, 'models', 'openface',
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'celeb-classifier.nn4.v1.pkl'),
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os.path.join(fileDir, 'images', 'examples', '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(err)
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assert "Predict SteveCarell with 0.85 confidence." in out
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