Step 3 - Recognizing Faces in each frame of a video file.ipynb

{
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   "execution_count": 1,
   "metadata": {
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   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\lib\\site-packages\\h5py\\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From D:\\Data Science\\To My Git\\My\\Face Recog\\Facenet-Real-time-face-recognition-using-deep-learning-Tensorflow-master\\library\\detect_face.py:210: calling reduce_max (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "keep_dims is deprecated, use keepdims instead\n",
      "WARNING:tensorflow:From D:\\Data Science\\To My Git\\My\\Face Recog\\Facenet-Real-time-face-recognition-using-deep-learning-Tensorflow-master\\library\\detect_face.py:212: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "keep_dims is deprecated, use keepdims instead\n",
      "Loading Modal\n",
      "Model filename: ./model/20191012-185253.pb\n",
      "Start Recognition\n",
      "Detected_FaceNum: 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:98: DeprecationWarning: `imresize` is deprecated!\n",
      "`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
      "Use ``skimage.transform.resize`` instead.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.02222524 0.08025056 0.05950839 0.05506129 0.02846647 0.75448805]]\n",
      "[5]  with accuracy  [0.75448805]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.07736455 0.05107562 0.00794785 0.07519108 0.7280836  0.0603373 ]]\n",
      "[4]  with accuracy  [0.7280836]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.16905698 0.14747242 0.19157955 0.16185728 0.11545911 0.21457465]]\n",
      "[5]  with accuracy  [0.21457465]\n",
      "Detected_FaceNum: 2\n",
      "[[0.01138632 0.11502277 0.03108917 0.04104156 0.02484014 0.77662004]]\n",
      "[5]  with accuracy  [0.77662004]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.04874054 0.04791258 0.00616544 0.10603753 0.75360839 0.03753552]]\n",
      "[4]  with accuracy  [0.75360839]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 2\n",
      "[[0.01370645 0.04858947 0.02726265 0.03327825 0.01641656 0.86074662]]\n",
      "[5]  with accuracy  [0.86074662]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.1782853  0.05414955 0.01084537 0.10732525 0.57563711 0.07375742]]\n",
      "[4]  with accuracy  [0.57563711]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 3\n",
      "[[0.03738297 0.15741211 0.08390607 0.08130759 0.03416151 0.60582976]]\n",
      "[5]  with accuracy  [0.60582976]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.07066535 0.06302592 0.01401291 0.09997338 0.69975156 0.05257088]]\n",
      "[4]  with accuracy  [0.69975156]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.12550005 0.13942628 0.20044449 0.14555507 0.26120496 0.12786915]]\n",
      "[4]  with accuracy  [0.26120496]\n",
      "Detected_FaceNum: 2\n",
      "[[0.03335093 0.1786696  0.05958257 0.04750398 0.02936591 0.65152702]]\n",
      "[5]  with accuracy  [0.65152702]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.05125884 0.08133399 0.01273018 0.0826211  0.72080412 0.05125177]]\n",
      "[4]  with accuracy  [0.72080412]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 2\n",
      "[[0.0502471  0.2778007  0.07417419 0.05730097 0.06256873 0.47790831]]\n",
      "[5]  with accuracy  [0.47790831]\n",
      "[[0.06212055 0.07467581 0.01388604 0.13907101 0.66129518 0.0489514 ]]\n",
      "[4]  with accuracy  [0.66129518]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 2\n",
      "[[0.04698925 0.22664889 0.07059802 0.0501938  0.0506947  0.55487535]]\n",
      "[5]  with accuracy  [0.55487535]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.06587045 0.10121277 0.00951603 0.10082709 0.61862144 0.10395222]]\n",
      "[4]  with accuracy  [0.61862144]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 2\n",
      "[[0.01845531 0.12447754 0.03756097 0.0382701  0.03367037 0.7475657 ]]\n",
      "[5]  with accuracy  [0.7475657]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.05260664 0.07097882 0.00826822 0.15182314 0.65283424 0.06348893]]\n",
      "[4]  with accuracy  [0.65283424]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 2\n",
      "[[0.02736915 0.21710762 0.0878447  0.05063876 0.06165551 0.55538426]]\n",
      "[5]  with accuracy  [0.55538426]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.08590756 0.09438937 0.01032011 0.09125706 0.62966722 0.08845867]]\n",
      "[4]  with accuracy  [0.62966722]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 2\n",
      "[[0.02612288 0.24818896 0.0984843  0.05863802 0.07232034 0.49624549]]\n",
      "[5]  with accuracy  [0.49624549]\n",
      "[[0.06960227 0.0560403  0.00745133 0.12182749 0.71033893 0.03473968]]\n",
      "[4]  with accuracy  [0.71033893]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 2\n",
      "[[0.01521584 0.07907313 0.02934699 0.02647792 0.02317904 0.82670708]]\n",
      "[5]  with accuracy  [0.82670708]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.09809423 0.0722741  0.01338855 0.12822773 0.63228807 0.05572731]]\n",
      "[4]  with accuracy  [0.63228807]\n",
      "Result Indices:  4\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 2\n",
      "[[0.03898307 0.16227673 0.08990512 0.04729669 0.06141403 0.60012437]]\n",
      "[5]  with accuracy  [0.60012437]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Face is very close!\n",
      "Detected_FaceNum: 2\n",
      "[[0.01062739 0.06142435 0.03098508 0.02604692 0.03560968 0.83530657]]\n",
      "[5]  with accuracy  [0.83530657]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Face is very close!\n",
      "Detected_FaceNum: 2\n",
      "[[0.01285971 0.09439485 0.03260671 0.03669327 0.03691984 0.78652562]]\n",
      "[5]  with accuracy  [0.78652562]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Face is very close!\n",
      "Detected_FaceNum: 2\n",
      "[[0.00279242 0.02292918 0.00563146 0.01367074 0.01386423 0.94111199]]\n",
      "[5]  with accuracy  [0.94111199]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Face is very close!\n",
      "Detected_FaceNum: 2\n",
      "[[0.00612767 0.05488295 0.02167787 0.02528717 0.02406671 0.86795763]]\n",
      "[5]  with accuracy  [0.86795763]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Face is very close!\n",
      "Detected_FaceNum: 2\n",
      "[[0.00718533 0.09203052 0.02369311 0.02747787 0.02810151 0.82151166]]\n",
      "[5]  with accuracy  [0.82151166]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Face is very close!\n",
      "Detected_FaceNum: 2\n",
      "[[0.01240313 0.14446298 0.04849234 0.05198205 0.03344764 0.70921186]]\n",
      "[5]  with accuracy  [0.70921186]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Face is very close!\n",
      "Detected_FaceNum: 1\n",
      "[[0.01901533 0.17457862 0.06988472 0.05606476 0.04168836 0.63876822]]\n",
      "[5]  with accuracy  [0.63876822]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.01131234 0.07465722 0.03515246 0.03732664 0.03266787 0.80888347]]\n",
      "[5]  with accuracy  [0.80888347]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00738853 0.04088699 0.01855378 0.0446353  0.01758691 0.87094849]]\n",
      "[5]  with accuracy  [0.87094849]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.0165995  0.05966589 0.02926839 0.04189604 0.02325955 0.82931063]]\n",
      "[5]  with accuracy  [0.82931063]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.01215051 0.07164579 0.03856463 0.04625076 0.02222875 0.80915957]]\n",
      "[5]  with accuracy  [0.80915957]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00137049 0.01100687 0.00449322 0.00970411 0.00944575 0.96397957]]\n",
      "[5]  with accuracy  [0.96397957]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Detected_FaceNum: 1\n",
      "[[0.00927861 0.04789071 0.01309195 0.02531849 0.01772385 0.88669639]]\n",
      "[5]  with accuracy  [0.88669639]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00803618 0.02910591 0.01222234 0.02632504 0.01302321 0.91128731]]\n",
      "[5]  with accuracy  [0.91128731]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00371817 0.01779521 0.00750817 0.01289961 0.00928603 0.9487928 ]]\n",
      "[5]  with accuracy  [0.9487928]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00656797 0.03254762 0.02016366 0.01969375 0.02280319 0.89822381]]\n",
      "[5]  with accuracy  [0.89822381]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.019612   0.07119531 0.04262675 0.04749155 0.02703315 0.79204124]]\n",
      "[5]  with accuracy  [0.79204124]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00583667 0.04103206 0.01696472 0.03175755 0.01838389 0.88602511]]\n",
      "[5]  with accuracy  [0.88602511]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00792712 0.03952244 0.02432356 0.03342361 0.02424702 0.87055624]]\n",
      "[5]  with accuracy  [0.87055624]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00531956 0.01791703 0.01727557 0.01868525 0.01604952 0.92475307]]\n",
      "[5]  with accuracy  [0.92475307]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00321382 0.02561989 0.01197254 0.01930713 0.01511297 0.92477366]]\n",
      "[5]  with accuracy  [0.92477366]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00332783 0.02311548 0.01032799 0.01693742 0.01082285 0.93546843]]\n",
      "[5]  with accuracy  [0.93546843]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.0035618  0.01936458 0.00971134 0.01841369 0.01021585 0.93873274]]\n",
      "[5]  with accuracy  [0.93873274]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00391052 0.01119992 0.00937699 0.01581122 0.01121219 0.94848916]]\n",
      "[5]  with accuracy  [0.94848916]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.01089599 0.01994301 0.02281636 0.0336516  0.02087156 0.89182148]]\n",
      "[5]  with accuracy  [0.89182148]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.01109425 0.05899794 0.02806797 0.04822705 0.02518372 0.82842906]]\n",
      "[5]  with accuracy  [0.82842906]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00479745 0.01248251 0.01044557 0.01202776 0.01243965 0.94780705]]\n",
      "[5]  with accuracy  [0.94780705]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00735993 0.01368136 0.01655769 0.01174307 0.01428518 0.93637277]]\n",
      "[5]  with accuracy  [0.93637277]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00497476 0.02253894 0.01031365 0.01693964 0.01532082 0.92991218]]\n",
      "[5]  with accuracy  [0.92991218]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00380628 0.01741233 0.00778031 0.01401979 0.01385473 0.94312656]]\n",
      "[5]  with accuracy  [0.94312656]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00833596 0.04211935 0.01774641 0.02505174 0.01684449 0.88990204]]\n",
      "[5]  with accuracy  [0.88990204]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.01175504 0.03134238 0.025487   0.03288906 0.01527486 0.88325165]]\n",
      "[5]  with accuracy  [0.88325165]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00607343 0.0260617  0.01587329 0.01792284 0.00897144 0.9250973 ]]\n",
      "[5]  with accuracy  [0.9250973]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00544588 0.03898367 0.02048262 0.02093939 0.01472281 0.89942562]]\n",
      "[5]  with accuracy  [0.89942562]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00283951 0.00940936 0.00598294 0.00821934 0.01110325 0.9624456 ]]\n",
      "[5]  with accuracy  [0.9624456]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.01194846 0.03264437 0.03605157 0.05577935 0.03151315 0.8320631 ]]\n",
      "[5]  with accuracy  [0.8320631]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 2\n",
      "[[0.00644656 0.01874533 0.01783674 0.02649293 0.0223381  0.90814034]]\n",
      "[5]  with accuracy  [0.90814034]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "[[0.16905794 0.12086101 0.27207001 0.12630291 0.09552523 0.21618288]]\n",
      "[2]  with accuracy  [0.27207001]\n",
      "Detected_FaceNum: 1\n",
      "[[0.00495572 0.01988096 0.01024374 0.01984418 0.01378392 0.93129149]]\n",
      "[5]  with accuracy  [0.93129149]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00615202 0.0202596  0.01884366 0.02908253 0.02368277 0.90197941]]\n",
      "[5]  with accuracy  [0.90197941]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00541876 0.01611261 0.01694716 0.01276669 0.01726136 0.93149341]]\n",
      "[5]  with accuracy  [0.93149341]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00605661 0.01641183 0.0185554  0.01410648 0.01733759 0.92753208]]\n",
      "[5]  with accuracy  [0.92753208]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00964805 0.02627287 0.0218388  0.02236285 0.03085574 0.88902168]]\n",
      "[5]  with accuracy  [0.88902168]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00374657 0.014376   0.01815977 0.01084203 0.02013194 0.9327437 ]]\n",
      "[5]  with accuracy  [0.9327437]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.01281856 0.04072023 0.04195317 0.04376526 0.03052776 0.83021503]]\n",
      "[5]  with accuracy  [0.83021503]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00495721 0.02213954 0.00964964 0.02021999 0.02012146 0.92291216]]\n",
      "[5]  with accuracy  [0.92291216]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n",
      "Detected_FaceNum: 1\n",
      "[[0.00348722 0.01017201 0.00418024 0.01452784 0.01279273 0.95483995]]\n",
      "[5]  with accuracy  [0.95483995]\n",
      "Result Indices:  5\n",
      "['Bill_Hader', 'Kate_McKinnon', 'bobby_moynihan', 'jason_sudeikis', 'kenan_thompson', 'kristen_wiig']\n"
     ]
    }
   ],
   "source": [
    "from __future__ import absolute_import\n",
    "from __future__ import division\n",
    "from __future__ import print_function\n",
    "import tensorflow as tf\n",
    "from scipy import misc\n",
    "import cv2\n",
    "import numpy as np\n",
    "from library import facenet\n",
    "from library import detect_face\n",
    "import os\n",
    "import time\n",
    "import pickle\n",
    "\n",
    "input_video=\"example_mov.avi\"\n",
    "modeldir = './model/20191012-185253.pb'\n",
    "classifier_filename = './class/classifier.pkl'\n",
    "npy='./npy'\n",
    "train_img=\"./face_dataset\"\n",
    "\n",
    "with tf.Graph().as_default():\n",
    "    gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.6)\n",
    "    sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options, log_device_placement=False))\n",
    "    with sess.as_default():\n",
    "        pnet, rnet, onet = detect_face.create_mtcnn(sess, npy)\n",
    "\n",
    "        minsize = 20  # minimum size of face\n",
    "        threshold = [0.6, 0.7, 0.7]  # three steps's threshold\n",
    "        factor = 0.709  # scale factor\n",
    "        margin = 44\n",
    "        frame_interval = 3\n",
    "        batch_size = 1000\n",
    "        image_size = 182\n",
    "        input_image_size = 160\n",
    "        \n",
    "        HumanNames = os.listdir(train_img)\n",
    "        HumanNames.sort()\n",
    "\n",
    "        print('Loading Modal')\n",
    "        facenet.load_model(modeldir)\n",
    "        images_placeholder = tf.get_default_graph().get_tensor_by_name(\"input:0\")\n",
    "        embeddings = tf.get_default_graph().get_tensor_by_name(\"embeddings:0\")\n",
    "        phase_train_placeholder = tf.get_default_graph().get_tensor_by_name(\"phase_train:0\")\n",
    "        embedding_size = embeddings.get_shape()[1]\n",
    "\n",
    "\n",
    "        classifier_filename_exp = os.path.expanduser(classifier_filename)\n",
    "        with open(classifier_filename_exp, 'rb') as infile:\n",
    "            (model, class_names) = pickle.load(infile)\n",
    "\n",
    "        video_capture = cv2.VideoCapture(input_video)\n",
    "        c = 0\n",
    "\n",
    "\n",
    "        print('Start Recognition')\n",
    "        prevTime = 0\n",
    "        while True:\n",
    "            ret, frame = video_capture.read()\n",
    "\n",
    "            frame = cv2.resize(frame, (0,0), fx=0.5, fy=0.5)    #resize frame (optional)\n",
    "\n",
    "            curTime = time.time()+1    # calc fps\n",
    "            timeF = frame_interval\n",
    "\n",
    "            if (c % timeF == 0):\n",
    "                find_results = []\n",
    "\n",
    "                if frame.ndim == 2:\n",
    "                    frame = facenet.to_rgb(frame)\n",
    "                frame = frame[:, :, 0:3]\n",
    "                bounding_boxes, _ = detect_face.detect_face(frame, minsize, pnet, rnet, onet, threshold, factor)\n",
    "                nrof_faces = bounding_boxes.shape[0]\n",
    "                print('Detected_FaceNum: %d' % nrof_faces)\n",
    "\n",
    "                if nrof_faces > 0:\n",
    "                    det = bounding_boxes[:, 0:4]\n",
    "                    img_size = np.asarray(frame.shape)[0:2]\n",
    "\n",
    "                    cropped = []\n",
    "                    scaled = []\n",
    "                    scaled_reshape = []\n",
    "                    bb = np.zeros((nrof_faces,4), dtype=np.int32)\n",
    "\n",
    "                    for i in range(nrof_faces):\n",
    "                        emb_array = np.zeros((1, embedding_size))\n",
    "\n",
    "                        bb[i][0] = det[i][0]\n",
    "                        bb[i][1] = det[i][1]\n",
    "                        bb[i][2] = det[i][2]\n",
    "                        bb[i][3] = det[i][3]\n",
    "\n",
    "                        # inner exception\n",
    "                        if bb[i][0] <= 0 or bb[i][1] <= 0 or bb[i][2] >= len(frame[0]) or bb[i][3] >= len(frame):\n",
    "                            print('Face is very close!')\n",
    "                            continue\n",
    "\n",
    "                        cropped.append(frame[bb[i][1]:bb[i][3], bb[i][0]:bb[i][2], :])\n",
    "                        cropped[i] = facenet.flip(cropped[i], False)\n",
    "                        scaled.append(misc.imresize(cropped[i], (image_size, image_size), interp='bilinear'))\n",
    "                        scaled[i] = cv2.resize(scaled[i], (input_image_size,input_image_size),\n",
    "                                               interpolation=cv2.INTER_CUBIC)\n",
    "                        scaled[i] = facenet.prewhiten(scaled[i])\n",
    "                        scaled_reshape.append(scaled[i].reshape(-1,input_image_size,input_image_size,3))\n",
    "                        feed_dict = {images_placeholder: scaled_reshape[i], phase_train_placeholder: False}\n",
    "                        emb_array[0, :] = sess.run(embeddings, feed_dict=feed_dict)\n",
    "                        predictions = model.predict_proba(emb_array)\n",
    "                        print(predictions)\n",
    "                        best_class_indices = np.argmax(predictions, axis=1)\n",
    "                        best_class_probabilities = predictions[np.arange(len(best_class_indices)), best_class_indices]\n",
    "                        # print(\"predictions\")\n",
    "                        print(best_class_indices,' with accuracy ',best_class_probabilities)\n",
    "\n",
    "                        # print(best_class_probabilities)\n",
    "                        if best_class_probabilities>0.53:\n",
    "                            cv2.rectangle(frame, (bb[i][0], bb[i][1]), (bb[i][2], bb[i][3]), (0, 255, 0), 2)    #boxing face\n",
    "\n",
    "                            #plot result idx under box\n",
    "                            text_x = bb[i][0]\n",
    "                            text_y = bb[i][3] + 20\n",
    "                            print('Result Indices: ', best_class_indices[0])\n",
    "                            print(HumanNames)\n",
    "                            for H_i in HumanNames:\n",
    "                                if HumanNames[best_class_indices[0]] == H_i:\n",
    "                                    result_names = HumanNames[best_class_indices[0]]\n",
    "                                    cv2.putText(frame, result_names, (text_x, text_y), cv2.FONT_HERSHEY_COMPLEX_SMALL,\n",
    "                                                1, (0, 0, 255), thickness=1, lineType=2)\n",
    "                else:\n",
    "                    print('Alignment Failure')\n",
    "            # c+=1\n",
    "            cv2.imshow('Video', frame)\n",
    "\n",
    "            if cv2.waitKey(1) & 0xFF == ord('q'):\n",
    "                break\n",
    "\n",
    "        video_capture.release()\n",
    "        cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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