diff --git a/Retinafacedetection.ipynb b/Retinafacedetection.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from IPython.display import display, Javascript\n",
+    "from utilpack.util import *\n",
+    "\n",
+    "from retinaface import RetinaFace\n",
+    "from deepface import DeepFace\n",
+    "\n",
+    "from datetime import datetime\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import cv2\n",
+    "\n",
+    "import numpy as np\n",
+    "import os\n",
+    "import h5py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filename = 'video.avi'\n",
+    "frames_per_second = 24.0\n",
+    "res = '720p'\n",
+    "\n",
+    "# Set resolution for the video capture\n",
+    "# Function adapted from https://kirr.co/0l6qmh\n",
+    "def change_res(cap, width, height):\n",
+    "    cap.set(3, width)\n",
+    "    cap.set(4, height)\n",
+    "\n",
+    "# Standard Video Dimensions Sizes\n",
+    "STD_DIMENSIONS =  {\n",
+    "    \"480p\": (640, 480),\n",
+    "    \"720p\": (1280, 720),\n",
+    "    \"1080p\": (1920, 1080),\n",
+    "    \"4k\": (3840, 2160),\n",
+    "}\n",
+    "\n",
+    "\n",
+    "# grab resolution dimensions and set video capture to it.\n",
+    "def get_dims(cap, res='1080p'):\n",
+    "    width, height = STD_DIMENSIONS[\"480p\"]\n",
+    "    if res in STD_DIMENSIONS:\n",
+    "        width,height = STD_DIMENSIONS[res]\n",
+    "    ## change the current caputre device\n",
+    "    ## to the resulting resolution\n",
+    "    change_res(cap, width, height)\n",
+    "    return width, height\n",
+    "\n",
+    "# Video Encoding, might require additional installs\n",
+    "# Types of Codes: http://www.fourcc.org/codecs.php\n",
+    "VIDEO_TYPE = {\n",
+    "    'avi': cv2.VideoWriter_fourcc(*'XVID'),\n",
+    "    #'mp4': cv2.VideoWriter_fourcc(*'H264'),\n",
+    "    'mp4': cv2.VideoWriter_fourcc(*'XVID'),\n",
+    "}\n",
+    "\n",
+    "def get_video_type(filename):\n",
+    "    filename, ext = os.path.splitext(filename)\n",
+    "    if ext in VIDEO_TYPE:\n",
+    "      return  VIDEO_TYPE[ext]\n",
+    "    return VIDEO_TYPE['avi']\n",
+    "\n",
+    "cap = cv2.VideoCapture(0)\n",
+    "out = cv2.VideoWriter(filename, get_video_type(filename), 25, get_dims(cap, res))\n",
+    "start_time = datetime.now()\n",
+    "\n",
+    "while True:\n",
+    "    ret, frame = cap.read()\n",
+    "    img_cv = cv2.imshow('frame',frame)\n",
+    "    \n",
+    "    # diff = (datetime.now() - start_time).seconds # converting into seconds\n",
+    "    # print(diff)\n",
+    "    # while( diff <= duration ):\n",
+    "    out.write(frame)\n",
+    "    # rgb_image = cv2.cvtColor(img_cv,PyImageUtil.cv2.COLOR_BGR2RGB).astype(np.float32)\n",
+    "\n",
+    "    # # cv2.imwrite(\"NewPicture.jpg\",frame)\n",
+    "    # diff = (datetime.now() - start_time).seconds\n",
+    "    # print(diff)\n",
+    "    if cv2.waitKey(1) & 0xFF == ord('q'):\n",
+    "        break\n",
+    "    # # img_path = \"NewPicture.jpg\"\n",
+    "    # img = cv2.imread(rgb_image)\n",
+    "    # obj = RetinaFace.detect_faces(rgb_image)\n",
+    "    # RetinaFace.get_image()\n",
+    "    # img.shape\n",
+    "\n",
+    "    # for key in obj.keys():\n",
+    "    #     identity = obj[key]\n",
+    "    #     # print(identity)\n",
+    "    #     facial_area = identity[\"facial_area\"]\n",
+    "    #     cv2.rectangle(img, (facial_area[2],facial_area[3]),(facial_area[0],facial_area[1]),(255,255,255),1)\n",
+    "\n",
+    "    # plt.figure(figsize=(20,20))\n",
+    "    # plt.imshow(img[:,:,::-1])\n",
+    "    # plt.show\n",
+    "\n",
+    "cap.release()\n",
+    "out.release()\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "img_path = \"NewPicture.jpg\"\n",
+    "img = cv2.imread(img_path)\n",
+    "obj = RetinaFace.detect_faces(img_path)\n",
+    "\n",
+    "img.shape\n",
+    "\n",
+    "for key in obj.keys():\n",
+    "    identity = obj[key]\n",
+    "    # print(identity)\n",
+    "    facial_area = identity[\"facial_area\"]\n",
+    "    cv2.rectangle(img, (facial_area[2],facial_area[3]),(facial_area[0],facial_area[1]),(255,255,255),1)\n",
+    "\n",
+    "plt.figure(figsize=(20,20))\n",
+    "plt.imshow(img[:,:,::-1])\n",
+    "plt.show"
+   ]
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "e13dd8a849d904006525f725a94fd9290dba9eb122ef777785557ae33676f1f8"
+  },
+  "kernelspec": {
+   "display_name": "Python 3.6.13 ('compare')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.13"
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+ "nbformat_minor": 2
+}