video_conversion.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='1'></a>\n",
    "# Import modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import keras.backend as K"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4'></a>\n",
    "# Model Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:146: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "K.set_learning_phase(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Input/Output resolution\n",
    "RESOLUTION = 256 # 64x64, 128x128, 256x256\n",
    "assert (RESOLUTION % 64) == 0, \"RESOLUTION should be 64, 128, 256\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Architecture configuration\n",
    "arch_config = {}\n",
    "arch_config['IMAGE_SHAPE'] = (RESOLUTION, RESOLUTION, 3)\n",
    "arch_config['use_self_attn'] = True\n",
    "arch_config['norm'] = \"instancenorm\" # instancenorm, batchnorm, layernorm, groupnorm, none\n",
    "arch_config['model_capacity'] = \"standard\" # standard, lite"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5'></a>\n",
    "# Define models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from networks.faceswap_gan_model import FaceswapGANModel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:507: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.\n",
      "\n",
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:3831: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.\n",
      "\n",
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:3878: The name tf.truncated_normal is deprecated. Please use tf.random.truncated_normal instead.\n",
      "\n",
      "WARNING:tensorflow:From c:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\networks\\custom_inits\\icnr_initializer.py:12: The name tf.keras.initializers.RandomNormal is deprecated. Please use tf.compat.v1.keras.initializers.RandomNormal instead.\n",
      "\n",
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\tensorflow_core\\python\\keras\\initializers.py:143: calling RandomNormal.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Call initializer instance with the dtype argument instead of passing it to the constructor\n",
      "WARNING:tensorflow:From c:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\networks\\custom_inits\\icnr_initializer.py:17: The name tf.image.resize_nearest_neighbor is deprecated. Please use tf.compat.v1.image.resize_nearest_neighbor instead.\n",
      "\n",
      "WARNING:tensorflow:From c:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\networks\\custom_inits\\icnr_initializer.py:18: The name tf.space_to_depth is deprecated. Please use tf.compat.v1.space_to_depth instead.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "model = FaceswapGANModel(**arch_config)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='6'></a>\n",
    "# Load Model Weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:167: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.\n",
      "\n",
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:174: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.\n",
      "\n",
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:179: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.\n",
      "\n",
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:183: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.\n",
      "\n",
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:192: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.\n",
      "\n",
      "WARNING:tensorflow:From C:\\Users\\kc510\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:199: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.\n",
      "\n",
      "Model weights files are successfully loaded.\n"
     ]
    }
   ],
   "source": [
    "model.load_weights(path=\"./models\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='12'></a>\n",
    "# Video Conversion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from converter.video_converter import VideoConverter\n",
    "from detector.face_detector import MTCNNFaceDetector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From c:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\detector\\face_detector.py:25: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.\n",
      "\n",
      "WARNING:tensorflow:From c:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\mtcnn_detect_face.py:127: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.\n",
      "\n",
      "WARNING:tensorflow:From c:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\mtcnn_detect_face.py:179: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.\n",
      "\n",
      "WARNING:tensorflow:From c:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\mtcnn_detect_face.py:215: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Deprecated in favor of operator or tf.math.divide.\n",
      "WARNING:tensorflow:From c:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\mtcnn_detect_face.py:199: The name tf.nn.xw_plus_b is deprecated. Please use tf.compat.v1.nn.xw_plus_b instead.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "mtcnn_weights_dir = \"./mtcnn_weights/\"\n",
    "\n",
    "fd = MTCNNFaceDetector(sess=K.get_session(), model_path=mtcnn_weights_dir)\n",
    "vc = VideoConverter()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "vc.set_face_detector(fd)\n",
    "vc.set_gan_model(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Video conversion configuration\n",
    "\n",
    "\n",
    "- `use_smoothed_bbox`: \n",
    "    - Boolean. Whether to enable smoothed bbox.\n",
    "- `use_kalman_filter`: \n",
    "    - Boolean. Whether to enable Kalman filter.\n",
    "- `use_auto_downscaling`:\n",
    "    - Boolean. Whether to enable auto-downscaling in face detection (to prevent OOM error).\n",
    "- `bbox_moving_avg_coef`: \n",
    "    - Float point between 0 and 1. Smoothing coef. used when use_kalman_filter is set False.\n",
    "- `min_face_area`:\n",
    "    - int x int. Minimum size of face. Detected faces smaller than min_face_area will not be transformed.\n",
    "- `IMAGE_SHAPE`:\n",
    "    - Input/Output resolution of the GAN model\n",
    "- `kf_noise_coef`:\n",
    "    - Float point. Increase by 10x if tracking is slow. Decrease by 1/10x if trakcing works fine but jitter occurs.\n",
    "- `use_color_correction`: \n",
    "    - String of \"adain\", \"adain_xyz\", \"hist_match\", or \"none\". The color correction method to be applied.\n",
    "- `detec_threshold`: \n",
    "    - Float point between 0 and 1. Decrease its value if faces are missed. Increase its value to reduce false positives.\n",
    "- `roi_coverage`: \n",
    "    - Float point between 0 and 1 (exclusive). Center area of input images to be cropped (Suggested range: 0.85 ~ 0.95)\n",
    "- `enhance`: \n",
    "    - Float point. A coef. for contrast enhancement in the region of alpha mask (Suggested range: 0. ~ 0.4)\n",
    "- `output_type`: \n",
    "    - Layout format of output video: 1. [ result ], 2. [ source | result ], 3. [ source | result | mask ]\n",
    "- `direction`: \n",
    "    - String of \"AtoB\" or \"BtoA\". Direction of face transformation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "options = {\n",
    "    # ===== Fixed =====\n",
    "    \"use_smoothed_bbox\": True,\n",
    "    \"use_kalman_filter\": True,\n",
    "    \"use_auto_downscaling\": False,\n",
    "    \"bbox_moving_avg_coef\": 0.65,\n",
    "    \"min_face_area\": 35 * 35,\n",
    "    \"IMAGE_SHAPE\": model.IMAGE_SHAPE,\n",
    "    # ===== Tunable =====\n",
    "    \"kf_noise_coef\": 3e-3,\n",
    "    \"use_color_correction\": \"hist_match\",\n",
    "    \"detec_threshold\": 0.7,\n",
    "    \"roi_coverage\": 0.9,\n",
    "    \"enhance\": 0.,\n",
    "    \"output_type\": 3,\n",
    "    \"direction\": \"AtoB\",\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Start video conversion\n",
    "\n",
    "\n",
    "- `input_fn`: \n",
    "    - String. Input video path.\n",
    "- `output_fn`: \n",
    "    - String. Output video path.\n",
    "- `duration`: \n",
    "    - None or a non-negative float tuple: (start_sec, end_sec). Duration of input video to be converted\n",
    "    - e.g., setting `duration = (5, 7.5)` outputs a 2.5-sec-long video clip corresponding to 5s ~ 7.5s of the input video."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_fn = \"1.mp4\"\n",
    "output_fn = \"OUTPUT_VIDEO.mp4\"\n",
    "duration = None "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Moviepy - Building video OUTPUT_VIDEO.mp4.\n",
      "MoviePy - Writing audio in OUTPUT_VIDEOTEMP_MPY_wvf_snd.mp3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": []
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MoviePy - Done.\n",
      "Moviepy - Writing video OUTPUT_VIDEO.mp4\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "t:   0%|          | 5/1812 [00:30<3:25:52,  6.84s/it, now=None]"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-13-1b358f26260b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mvc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconvert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput_fn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minput_fn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput_fn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moutput_fn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mduration\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mduration\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mc:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\converter\\video_converter.py\u001b[0m in \u001b[0;36mconvert\u001b[1;34m(self, input_fn, output_fn, options, duration)\u001b[0m\n\u001b[0;32m     89\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     90\u001b[0m             \u001b[0mclip\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mclip1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfl_image\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mimg\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprocess_video\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 91\u001b[1;33m         \u001b[0mclip\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite_videofile\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput_fn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maudio\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     92\u001b[0m         \u001b[0mclip1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreader\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     93\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<decorator-gen-181>\u001b[0m in \u001b[0;36mwrite_videofile\u001b[1;34m(self, filename, fps, codec, bitrate, audio, audio_fps, preset, audio_nbytes, audio_codec, audio_bitrate, audio_bufsize, temp_audiofile, rewrite_audio, remove_temp, write_logfile, verbose, threads, ffmpeg_params, logger)\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\decorators.py\u001b[0m in \u001b[0;36mrequires_duration\u001b[1;34m(f, clip, *a, **k)\u001b[0m\n\u001b[0;32m     52\u001b[0m         \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Attribute 'duration' not set\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     53\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 54\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mclip\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     55\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     56\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<decorator-gen-180>\u001b[0m in \u001b[0;36mwrite_videofile\u001b[1;34m(self, filename, fps, codec, bitrate, audio, audio_fps, preset, audio_nbytes, audio_codec, audio_bitrate, audio_bufsize, temp_audiofile, rewrite_audio, remove_temp, write_logfile, verbose, threads, ffmpeg_params, logger)\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\decorators.py\u001b[0m in \u001b[0;36muse_clip_fps_by_default\u001b[1;34m(f, clip, *a, **k)\u001b[0m\n\u001b[0;32m    133\u001b[0m              for (k,v) in k.items()}\n\u001b[0;32m    134\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 135\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mclip\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0mnew_a\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mnew_kw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m<decorator-gen-179>\u001b[0m in \u001b[0;36mwrite_videofile\u001b[1;34m(self, filename, fps, codec, bitrate, audio, audio_fps, preset, audio_nbytes, audio_codec, audio_bitrate, audio_bufsize, temp_audiofile, rewrite_audio, remove_temp, write_logfile, verbose, threads, ffmpeg_params, logger)\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\decorators.py\u001b[0m in \u001b[0;36mconvert_masks_to_RGB\u001b[1;34m(f, clip, *a, **k)\u001b[0m\n\u001b[0;32m     20\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mclip\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mismask\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     21\u001b[0m         \u001b[0mclip\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mclip\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_RGB\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 22\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mclip\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     23\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     24\u001b[0m \u001b[1;33m@\u001b[0m\u001b[0mdecorator\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdecorator\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\video\\VideoClip.py\u001b[0m in \u001b[0;36mwrite_videofile\u001b[1;34m(self, filename, fps, codec, bitrate, audio, audio_fps, preset, audio_nbytes, audio_codec, audio_bitrate, audio_bufsize, temp_audiofile, rewrite_audio, remove_temp, write_logfile, verbose, threads, ffmpeg_params, logger)\u001b[0m\n\u001b[0;32m    305\u001b[0m                            \u001b[0mverbose\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mverbose\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mthreads\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mthreads\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    306\u001b[0m                            \u001b[0mffmpeg_params\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mffmpeg_params\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 307\u001b[1;33m                            logger=logger)\n\u001b[0m\u001b[0;32m    308\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    309\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mremove_temp\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mmake_audio\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\video\\io\\ffmpeg_writer.py\u001b[0m in \u001b[0;36mffmpeg_write_video\u001b[1;34m(clip, filename, fps, codec, bitrate, preset, withmask, write_logfile, audiofile, verbose, threads, ffmpeg_params, logger)\u001b[0m\n\u001b[0;32m    219\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    220\u001b[0m         for t,frame in clip.iter_frames(logger=logger, with_times=True,\n\u001b[1;32m--> 221\u001b[1;33m                                         fps=fps, dtype=\"uint8\"):\n\u001b[0m\u001b[0;32m    222\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mwithmask\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    223\u001b[0m                 \u001b[0mmask\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m255\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mclip\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmask\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_frame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\Clip.py\u001b[0m in \u001b[0;36miter_frames\u001b[1;34m(self, fps, with_times, logger, dtype)\u001b[0m\n\u001b[0;32m    470\u001b[0m         \u001b[0mlogger\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mproglog\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdefault_bar_logger\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlogger\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    471\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mt\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mlogger\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miter_bar\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mduration\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0mfps\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 472\u001b[1;33m             \u001b[0mframe\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_frame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    473\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mdtype\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mframe\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    474\u001b[0m                 \u001b[0mframe\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mframe\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<decorator-gen-137>\u001b[0m in \u001b[0;36mget_frame\u001b[1;34m(self, t)\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(f, *a, **kw)\u001b[0m\n\u001b[0;32m     87\u001b[0m         new_kw = {k: fun(v) if k in varnames else v\n\u001b[0;32m     88\u001b[0m                  for (k,v) in kw.items()}\n\u001b[1;32m---> 89\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mnew_a\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mnew_kw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     90\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mdecorator\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdecorator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwrapper\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     91\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\Clip.py\u001b[0m in \u001b[0;36mget_frame\u001b[1;34m(self, t)\u001b[0m\n\u001b[0;32m     91\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mframe\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     92\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 93\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmake_frame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     94\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     95\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mfl\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfun\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mapply_to\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkeep_duration\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\Clip.py\u001b[0m in \u001b[0;36m<lambda>\u001b[1;34m(t)\u001b[0m\n\u001b[0;32m    134\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    135\u001b[0m         \u001b[1;31m#mf = copy(self.make_frame)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 136\u001b[1;33m         \u001b[0mnewclip\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_make_frame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mt\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mfun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_frame\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    137\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    138\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mkeep_duration\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\moviepy\\video\\VideoClip.py\u001b[0m in \u001b[0;36m<lambda>\u001b[1;34m(gf, t)\u001b[0m\n\u001b[0;32m    488\u001b[0m         \"\"\"\n\u001b[0;32m    489\u001b[0m         \u001b[0mapply_to\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mapply_to\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 490\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfl\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mgf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mt\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mimage_func\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mapply_to\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    491\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    492\u001b[0m     \u001b[1;31m# --------------------------------------------------------------\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\converter\\video_converter.py\u001b[0m in \u001b[0;36m<lambda>\u001b[1;34m(img)\u001b[0m\n\u001b[0;32m     88\u001b[0m             \u001b[0mclip\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mclip1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfl_image\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mimg\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprocess_video\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msubclip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mduration\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mduration\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     89\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 90\u001b[1;33m             \u001b[0mclip\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mclip1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfl_image\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mimg\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprocess_video\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     91\u001b[0m         \u001b[0mclip\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite_videofile\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput_fn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maudio\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     92\u001b[0m         \u001b[0mclip1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreader\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\kc510\\Documents\\Neural Network\\MinorProject\\Second_test(D)\\converter\\video_converter.py\u001b[0m in \u001b[0;36mprocess_video\u001b[1;34m(self, input_img, options)\u001b[0m\n\u001b[0;32m    198\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mconf_score\u001b[0m \u001b[1;33m>=\u001b[0m \u001b[0mbest_conf_score\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    199\u001b[0m                 \u001b[0mmask_map\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresult_a\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 200\u001b[1;33m                 \u001b[0mmask_map\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmask_map\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m.15\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0minput_img\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m255\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    201\u001b[0m                 \u001b[1;31m# Possible bug: when small faces are detected before the most confident face,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    202\u001b[0m                 \u001b[1;31m#               the mask_map will show brighter input_img\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<__array_function__ internals>\u001b[0m in \u001b[0;36mclip\u001b[1;34m(*args, **kwargs)\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\numpy\\core\\fromnumeric.py\u001b[0m in \u001b[0;36mclip\u001b[1;34m(a, a_min, a_max, out, **kwargs)\u001b[0m\n\u001b[0;32m   2095\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2096\u001b[0m     \"\"\"\n\u001b[1;32m-> 2097\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0m_wrapfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'clip'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0ma_min\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0ma_max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mout\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2098\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2099\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\numpy\\core\\fromnumeric.py\u001b[0m in \u001b[0;36m_wrapfunc\u001b[1;34m(obj, method, *args, **kwds)\u001b[0m\n\u001b[0;32m     56\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     57\u001b[0m     \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 58\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mbound\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     59\u001b[0m     \u001b[1;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     60\u001b[0m         \u001b[1;31m# A TypeError occurs if the object does have such a method in its\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\numpy\\core\\_methods.py\u001b[0m in \u001b[0;36m_clip\u001b[1;34m(a, min, max, out, casting, **kwargs)\u001b[0m\n\u001b[0;32m    139\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    140\u001b[0m         return _clip_dep_invoke_with_casting(\n\u001b[1;32m--> 141\u001b[1;33m             um.clip, a, min, max, out=out, casting=casting, **kwargs)\n\u001b[0m\u001b[0;32m    142\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    143\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_mean\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkeepdims\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\numpy\\core\\_methods.py\u001b[0m in \u001b[0;36m_clip_dep_invoke_with_casting\u001b[1;34m(ufunc, out, casting, *args, **kwargs)\u001b[0m\n\u001b[0;32m     92\u001b[0m     \u001b[1;31m# try to deal with broken casting rules\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     93\u001b[0m     \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 94\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mufunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mout\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     95\u001b[0m     \u001b[1;32mexcept\u001b[0m \u001b[0m_exceptions\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_UFuncOutputCastingError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     96\u001b[0m         \u001b[1;31m# Numpy 1.17.0, 2019-02-24\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "vc.convert(input_fn=input_fn, output_fn=output_fn, options=options, duration=duration)"
   ]
  }
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