Day00_video_seperator_maker.ipynb

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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import cv2\n",
    "import time\n",
    "import glob\n",
    "from IPython.display import clear_output\n"
   ]
  },
  {
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   "source": [
    "def show_img(img):\n",
    "    image_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
    "    plt.imshow(image_rgb)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {},
   "outputs": [],
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Seperate video to images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_one_frame(img, idx):\n",
    "    file_name = './input/tmp_{0:08d}.jpg'.format(idx)\n",
    "    # 寫入圖檔\n",
    "    cv2.imwrite(file_name, img)\n",
    " "
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "video_path = 'input.mp4'\n",
    "\n",
    "vc = cv2.VideoCapture(video_path)\n",
    "fps = vc.get(cv2.CAP_PROP_FPS)\n",
    "frame_count = int(vc.get(cv2.CAP_PROP_FRAME_COUNT))\n",
    "print(frame_count)\n",
    "video = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "for idx in range(frame_count):\n",
    "# for idx in range(600):  # do first 600 frames (20 sec)  \n",
    "    vc.set(1, idx)\n",
    "    ret, frame = vc.read()\n",
    "    height, width, layers = frame.shape\n",
    "    size = (width, height)\n",
    "    \n",
    "    if frame is not None:\n",
    "        process_one_frame(frame, idx)\n",
    "              \n",
    "        clear_output(wait=True)\n",
    "        print(\"process: {}/{}\".format(idx+1 , frame_count))\n",
    "        \n",
    "#         plt.imshow(new_frame)\n",
    "#         plt.show()\n",
    "vc.release()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# process video (one frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_one_frame(img):\n",
    "    # do something here\n",
    "    \n",
    "    return img"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# load video"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "video_path = 'cat.mp4'\n",
    "\n",
    "vc = cv2.VideoCapture(video_path)\n",
    "fps = vc.get(cv2.CAP_PROP_FPS)\n",
    "frame_count = int(vc.get(cv2.CAP_PROP_FRAME_COUNT))\n",
    "video = []"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# process video (main)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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     "end_time": "2020-08-29T18:09:32.496420Z",
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   "outputs": [],
   "source": [
    "tfirstStart = time.time()\n",
    "# for idx in range(frame_count):\n",
    "for idx in range(600):  # do first 600 frames (20 sec)  \n",
    "    tStart = time.time() # time start\n",
    "    vc.set(1, idx)\n",
    "    ret, frame = vc.read()\n",
    "    height, width, layers = frame.shape\n",
    "    size = (width, height)\n",
    "    \n",
    "    if frame is not None:\n",
    "        out_frame = process_one_frame(frame)\n",
    "        video.append(out_frame)\n",
    "        tEnd = time.time() # time end (processing one frame)\n",
    "        \n",
    "        clear_output(wait=True)\n",
    "#         show_img(out_frame)\n",
    "        print(\"process: {}/{}\".format(idx+1 , frame_count))\n",
    "        print(\"Cost {} sec\".format(tEnd - tStart)) \n",
    "        \n",
    "        \n",
    "vc.release()\n",
    "print(\"Total cost {} sec\".format(tEnd - tfirstStart))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "# # cv2 to PIL    \n",
    "# PIL_frame = Image.fromarray(cv2.cvtColor(cv2_frame,cv2.COLOR_BGR2RGB))  \n",
    "# PIL_frame = process_one_frame(PIL_frame)\n",
    "\n",
    "# # PIL to cv2\n",
    "# cv2_frame = cv2.cvtColor(np.asarray(PIL_frame),cv2.COLOR_RGB2BGR)  \n",
    "# cv2_frame = (cv2_frame).astype(np.uint8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# make video"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import cv2\n",
    "import time\n",
    "import glob\n",
    "\n",
    "from IPython.display import clear_output"
   ]
  },
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   "cell_type": "code",
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   },
   "outputs": [],
   "source": [
    "frame_list = sorted(glob.glob('./output/*.jpg'))\n",
    "print(\"frame count: \",len(frame_list))\n",
    "\n",
    "result_name = 'output.mp4'\n",
    "fps = 30\n",
    "shape = cv2.imread(frame_list[0]).shape # delete dimension 3\n",
    "size = (shape[1], shape[0])\n",
    "print(\"frame size: \",size)\n",
    "fourcc = cv2.VideoWriter_fourcc(*'XVID')\n",
    "out = cv2.VideoWriter(result_name, fourcc, fps, size)\n",
    "\n",
    "\n",
    "\n",
    "for idx, path in enumerate(frame_list):\n",
    "    frame = cv2.imread(path)\n",
    "#     print(\"\\r Making videos: {}/{}\".format(idx+1, len(frame_list)))\n",
    "#     clear_output(wait=True)\n",
    "#     show_img(frame)\n",
    "    out.write(frame)\n",
    "\n",
    "out.release()\n",
    "print(\"Finish making video !!!\")"
   ]
  },
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