Turning in my Computer Vision Toolbox

Face_Detect.ipynb

@@ -0,0 +1,74 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import cv2\n",
+    "\n",
+    "\n",
+    "cap = cv2.VideoCapture('Jason.mp4')\n",
+    "\n",
+    "face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')\n",
+    "kernel = np.ones((21,21),'uint8')\n",
+    "\n",
+    "while(True):\n",
+    "\n",
+    "    ret, frame = cap.read()\n",
+    "    faces = face_cascade.detectMultiScale(frame, scaleFactor=1.2, minSize=(20,20))\n",
+    "    for (x,y,w,h) in faces:\n",
+    "        frame[y:y+h, x:x+w,:] = cv2.dilate(frame[y:y+h,x:x+w,:], kernel)\n",
+    "\n",
+    "    for (x,y,w,h) in faces:\n",
+    "        cv2.circle(frame, (x + int(w/2),y + int(h/2)), int(w/2), (0,255,255), thickness=-1)\n",
+    "        cv2.circle(frame, (x + int(w/4),y + int(h/4)), 10, (0,0,0), thickness=-1)\n",
+    "\n",
+    "        cv2.circle(frame, (x + w - int(w/4),y + int(h/4)), 10, (0,0,0), thickness=-1)\n",
+    "        cv2.ellipse(frame, (x + int(w/2), y + h - int(h/4)), (int(w/4), int(h/5)), 180, 180, 360, (0,0,0))\n",
+    "\n",
+    "    cv2.imshow('frame',frame)\n",
+    "    if cv2.waitKey(1) & 0xFF == ord('q'):\n",
+    "        break\n",
+    "\n",
+    "\n",
+    "cap.release()\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
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+   "display_name": "Python 2",
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+}