old_contents: # OpenFace API tests.
  #
  # Copyright 2015 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 cv2
  import os
  
  import numpy as np
  np.set_printoptions(precision=2)
  from numpy.linalg import norm
  
  import scipy
  import scipy.spatial
  
  import openface
  
  openfaceDir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
  modelDir = os.path.join(openfaceDir, 'models')
  dlibModelDir = os.path.join(modelDir, 'dlib')
  openfaceModelDir = os.path.join(modelDir, 'openface')
  
  exampleImages = os.path.join(openfaceDir, 'images', 'examples')
  lfwSubset = os.path.join(openfaceDir, 'data', 'lfw-subset')
  
  dlibFacePredictor = os.path.join(dlibModelDir,
                                   "shape_predictor_68_face_landmarks.dat")
  model = os.path.join(openfaceModelDir, 'nn4.small2.v1.t7')
  imgDim = 96
  
  align = openface.AlignDlib(dlibFacePredictor)
  net = openface.TorchNeuralNet(model, imgDim=imgDim)
  
  
  def test_pipeline():
      imgPath = os.path.join(exampleImages, 'lennon-1.jpg')
      bgrImg = cv2.imread(imgPath)
      if bgrImg is None:
          raise Exception("Unable to load image: {}".format(imgPath))
      rgbImg = cv2.cvtColor(bgrImg, cv2.COLOR_BGR2RGB)
      # assert np.isclose(norm(rgbImg), 11.1355)
  
      bb = align.getLargestFaceBoundingBox(rgbImg)
      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)
      # assert np.isclose(norm(alignedFace), 7.61577)
  
      rep = net.forward(alignedFace)
      cosDist = scipy.spatial.distance.cosine(rep, np.ones(128))
      print(cosDist)
      assert np.isclose(cosDist, 0.938840385931)
  
new_contents: # OpenFace API tests.
  #
  # Copyright 2015 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 cv2
  import os
  
  import numpy as np
  np.set_printoptions(precision=2)
  
  import scipy
  import scipy.spatial
  
  import openface
  
  openfaceDir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
  modelDir = os.path.join(openfaceDir, 'models')
  dlibModelDir = os.path.join(modelDir, 'dlib')
  openfaceModelDir = os.path.join(modelDir, 'openface')
  
  exampleImages = os.path.join(openfaceDir, 'images', 'examples')
  lfwSubset = os.path.join(openfaceDir, 'data', 'lfw-subset')
  
  dlibFacePredictor = os.path.join(dlibModelDir,
                                   "shape_predictor_68_face_landmarks.dat")
  model = os.path.join(openfaceModelDir, 'nn4.small2.v1.t7')
  imgDim = 96
  
  align = openface.AlignDlib(dlibFacePredictor)
  net = openface.TorchNeuralNet(model, imgDim=imgDim)
  
  
  def test_pipeline():
      imgPath = os.path.join(exampleImages, 'lennon-1.jpg')
      bgrImg = cv2.imread(imgPath)
      if bgrImg is None:
          raise Exception("Unable to load image: {}".format(imgPath))
      rgbImg = cv2.cvtColor(bgrImg, cv2.COLOR_BGR2RGB)
      # assert np.isclose(norm(rgbImg), 11.1355)
  
      bb = align.getLargestFaceBoundingBox(rgbImg)
      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)
      # assert np.isclose(norm(alignedFace), 7.61577)
  
      rep = net.forward(alignedFace)
      cosDist = scipy.spatial.distance.cosine(rep, np.ones(128))
      print(cosDist)
      assert np.isclose(cosDist, 0.938840385931)
  
subject: Fix flake8 warnings.