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src/a/n/antispoofing.verification.gmm-1.0.2/antispoofing/verification/features/dct.py   antispoofing.verification.gmm(Download)
      # Converts to grayscale
      if(len(img_unk.shape) == 3):
        img = bob.ip.rgb_to_gray(img_unk)
      else:
        img = img_unk
 
  # Converts to grayscale
  if(len(img_input.shape) == 3): img = bob.ip.rgb_to_gray(img_input)
  else: img = img_input
 

src/a/n/antispoofing.motion-1.1.1/antispoofing/motion/script/framediff.py   antispoofing.motion(Download)
    # start the work here...
    vin = input.load() # load all in one shot.
    prev = bob.ip.rgb_to_gray(vin[0,:,:,:])
    curr = numpy.empty_like(prev)
    data = numpy.zeros((len(vin), 2), dtype='float64')
    data[0] = (numpy.NaN, numpy.NaN)
 
    for k in range(1, vin.shape[0]):
      bob.ip.rgb_to_gray(vin[k,:,:,:], curr)

src/x/b/xbob.paper.tpami2013-1.0.0/xbob/paper/tpami2013/features.py   xbob.paper.tpami2013(Download)
      # Converts to grayscale
      if(img_unk.ndim == 3):
        img = bob.ip.rgb_to_gray(img_unk)
      else:
        img = img_unk

src/a/n/antispoofing.lbptop-1.0.4/antispoofing/lbptop/spoof/calclbptop.py   antispoofing.lbptop(Download)
 
    if bbx and bbx.is_valid() and bbx.height > bbxsize_filter:
      frame = bob.ip.rgb_to_gray(rgbFrameSequence[k,:,:,:])
      cutframe = frame[bbx.y:(bbx.y+bbx.height),bbx.x:(bbx.x+bbx.width)] # cutting the box region
      tempbbx = numpy.ndarray((sz, sz), 'float64')

src/m/a/maskattack.study-1.0.0/maskattack/study/antispoof/lbp.py   maskattack.study(Download)
        img = bob.io.load(str(os.path.join(indir,obj.path+'_'+str(ind).zfill(2)+'.png')))
        if len(img.shape)>2:
          img = bob.ip.rgb_to_gray(img)
        image2 = numpy.zeros((64,64))
        bob.ip.scale(numpy.array(img),image2)

src/m/a/maskattack.study-1.0.0/maskattack/study/analyze/lbp.py   maskattack.study(Download)
        img = bob.io.load(str(os.path.join(indir,obj.path+'_'+str(ind).zfill(2)+'.png')))
        if len(img.shape)>2:
          img = bob.ip.rgb_to_gray(img)
        image2 = numpy.zeros((64,64))
        bob.ip.scale(numpy.array(img),image2)

src/e/s/estimate.gender-0.4/estimate/gender/estimateGender.py   estimate.gender(Download)
        img = bob.io.load(obj_path)
        if len(img.shape)>2:
          img = bob.ip.rgb_to_gray(img)
        if dbname == 'banca':
          eyes = db.annotations(obj.id)

src/m/a/maskattack.study-1.0.0/maskattack/study/analyze/isv.py   maskattack.study(Download)
        img = bob.io.load(str(os.path.join(indir,obj.path+'_'+str(ind).zfill(2)+'.png')))
        if len(img.shape)>2:
          img = bob.ip.rgb_to_gray(img)
        image2 = numpy.zeros((64,64))
        bob.ip.scale(numpy.array(img),image2)

src/m/a/maskattack.study-1.0.0/maskattack/study/accumulate/hdf5_to_grayscale.py   maskattack.study(Download)
        img = color[frame,:,:,:]
        eye = eyes[frame,:].astype('float')
        face_eyes_norm(bob.ip.rgb_to_gray(img), cropped_image, re_y = eye[1], re_x = eye[0], le_y = eye[3], le_x = eye[2])
        file_name = os.path.join(args.outputdir,f.split('.')[0]+'_%s.png') %str(frame/30+1).zfill(2)
        bob.io.save(cropped_image.astype('uint8'), file_name)

src/a/n/antispoofing.lbptop-1.0.4/antispoofing/lbptop/script/lbptop_calculate_parameters.py   antispoofing.lbptop(Download)
    grayFrames = numpy.zeros(shape=(nFrames,vin.shape[2],vin.shape[3]))
    for i in range(nFrames):
      grayFrames[i] = bob.ip.rgb_to_gray(vin[i,:,:,:])
      if(tan_triggs):
        grayFrames[i] = tantriggs(grayFrames[i])

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