main21.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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     "output_type": "stream",
     "text": [
      "\n",
      "example to show optical flow\n",
      "\n",
      "USAGE: opt_flow.py [<video_source>]\n",
      "\n",
      "Keys:\n",
      " 1 - toggle HSV flow visualization\n",
      " 2 - toggle glitch\n",
      "\n",
      "Keys:\n",
      "    ESC    - exit\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "#import pandas as pd\n",
    "import argparse\n",
    "import PIL.ImageDraw as ImageDraw\n",
    "import PIL.Image as Image\n",
    "import cv2\n",
    "\n",
    "\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "json_file = open(\"/home/ankit/Downloads/Cam_02_North_Ave_EB_Spring_St.json\", \"r\", encoding=\"utf-8\")\n",
    "sh_json= json.load(json_file)\n",
    "json_file.close()\n",
    "\n",
    "dots=[]\n",
    "image = Image.new(\"RGB\", (640, 480))\n",
    "\n",
    "draw = ImageDraw.Draw(image)\n",
    "#print(type( sh_json['Costco_Front_Image_0013.jpg193064']))\n",
    "for person in sh_json:\n",
    "    y=len(sh_json['valid_vertices'])\n",
    "for x in range(0,y):\n",
    "    k=(sh_json['valid_vertices'])\n",
    "    dots.append((k[x][0],k[x][1]))\n",
    "    #print(points)\n",
    "draw.polygon((dots), fill='green')\n",
    "#image.show()\n",
    "image.save('image1.png')\n",
    "\n",
    "\n",
    "#!/usr/bin/env python\n",
    "\n",
    "'''\n",
    "example to show optical flow\n",
    "\n",
    "USAGE: opt_flow.py [<video_source>]\n",
    "\n",
    "Keys:\n",
    " 1 - toggle HSV flow visualization\n",
    " 2 - toggle glitch\n",
    "\n",
    "Keys:\n",
    "    ESC    - exit\n",
    "'''\n",
    "\n",
    "# Python 2/3 compatibility\n",
    "from __future__ import print_function\n",
    "\n",
    "import numpy as np\n",
    "import cv2 as cv\n",
    "import video\n",
    "\n",
    "\n",
    "def draw_flow(points, flow,dots, step=16):\n",
    "    h,  w = points.shape[:2] # heights  and weights in image (if it is 3 then it also give no. of channel of img)\n",
    "    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int) # mesh-grid gives ndarrays all of the same dimensions\n",
    "    fx, fy = flow[y,x].T\n",
    "    points1 = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2) # vstack is use for to collect the array and make stack of array in vertical form (row wise)\n",
    "    points1 = np.int32(points1 + 0.5)\n",
    "    vis = cv.cvtColor(points, cv.COLOR_GRAY2BGR)\n",
    "    #temp_pts = np.array(dots, np.int32)\n",
    "    #temp_pts = temp_pts.reshape((-2, 1, 2)) .astype(int)\n",
    "\n",
    "    temp_pts = np.array(dots, np.int32).reshape((-2, 1, 2)) .astype(int)\n",
    "    cv2.polylines(vis, [temp_pts], True, (0, 255,200), thickness=2)  \n",
    "    cv.polylines(vis, points1, True, (0, 255, 200))\n",
    "    for (x1, y1), (_x2, _y2) in points1:\n",
    "        cv.circle(vis, (x1, y1), 1, (0, 255, 0), -1)\n",
    "    return vis \n",
    "\n",
    "def draw_hsv(flow):\n",
    "    h, w = flow.shape[:2]\n",
    "    fx, fy = flow[:,:,0], flow[:,:,1]\n",
    "    ang = np.arctan2(fy, fx) + np.pi\n",
    "    v = np.sqrt(fx*fx+fy*fy)\n",
    "    hsv = np.zeros((h, w, 3), np.uint8)\n",
    "    hsv[...,0] = ang*(180/np.pi/2)\n",
    "    hsv[...,1] = 255\n",
    "    hsv[...,2] = np.minimum(v*4, 255)\n",
    "    bgr = cv.cvtColor(hsv, cv.COLOR_HSV2BGR)\n",
    "    return bgr\n",
    "\n",
    "\n",
    "def warp_flow(img, flow):\n",
    "    h, w = flow.shape[:2]\n",
    "    flow = -flow\n",
    "    flow[:,:,0] += np.arange(w)\n",
    "    flow[:,:,1] += np.arange(h)[:,np.newaxis]\n",
    "    res = cv.remap(img, flow, None, cv.INTER_LINEAR)\n",
    "    return res\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    import sys    #The sys module provides information about constants, functions and methods of the Python interpreter. \n",
    "                  # dir(system) gives of the available constants, functions and methods.\n",
    "    print(__doc__)\n",
    "    cam = cv2.VideoCapture('/home/ankit/Downloads/opencv-master /samples/data/vtest.avi')\n",
    "    cam.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)\n",
    "    cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)\n",
    "    codec = cv2.VideoWriter_fourcc(*'XVID') \n",
    "    output1 = cv2.VideoWriter('/home/ankit/Downloads/opencv-master /samples/python/just.avi', codec, 60.0,(1920,1080))\n",
    "    ret, prev = cam.read() \n",
    "    prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)\n",
    "    show_hsv = False\n",
    "    show_glitch = False\n",
    "    cur_glitch = prev.copy()\n",
    "   \n",
    "    while (cam.isOpened()):\n",
    "        ret, prev = cam.read()\n",
    "        gray = cv.cvtColor(prev, cv.COLOR_BGR2GRAY)\n",
    "        flow = cv.calcOpticalFlowFarneback(prevgray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0) \n",
    "        prevgray = gray\n",
    "        \n",
    "        cv.imshow('flow', draw_flow(gray, flow,dots))  #its shows the image\n",
    "        if show_hsv:\n",
    "            cv.imshow('flow HSV', draw_hsv(flow))\n",
    "        if show_glitch:\n",
    "            cur_glitch = warp_flow(cur_glitch, flow)\n",
    "            cv.imshow('glitch', cur_glitch)\n",
    "            \n",
    "        ch = cv.waitKey(1)\n",
    "        if ch == 27:\n",
    "            break\n",
    "        if ch == ord('1'):\n",
    "            show_hsv = not show_hsv\n",
    "            print('HSV flow visualization is', ['off', 'on'][show_hsv])\n",
    "        if ch == ord('2'):\n",
    "            show_glitch = not show_glitch\n",
    "            if show_glitch:\n",
    "                cur_glitch = img.copy()\n",
    "            print('glitch is', ['off', 'on'][show_glitch])\n",
    "    cam.release()\n",
    "    output1.release()\n",
    "    cv.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(576, 768)\n",
      "(576, 768)\n",
      "SSIM: 0.9052422851964658\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ankit/anaconda3/envs/abc12/lib/python3.7/site-packages/skimage/util/arraycrop.py:177: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  cropped = ar[slices]\n"
     ]
    }
   ],
   "source": [
    "#difference between polygon and image\n",
    "import json\n",
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import PIL.ImageDraw as ImageDraw\n",
    "import PIL.Image as Image\n",
    "from skimage.measure import compare_ssim\n",
    "import imutils\n",
    "import cv2\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "json_file = open(\"/home/ankit/Downloads/Cam_02_North_Ave_EB_Spring_St.json\", \"r\", encoding=\"utf-8\")\n",
    "sh_json= json.load(json_file)\n",
    "json_file.close()\n",
    "\n",
    "dots=[]\n",
    "image = Image.new(\"RGB\", (640, 480))\n",
    "draw = ImageDraw.Draw(image)\n",
    "\n",
    "for person in sh_json:\n",
    "    y=len(sh_json['valid_vertices'])\n",
    "for x in range(0,y):\n",
    "    k=(sh_json['valid_vertices'])\n",
    "    dots.append((k[x][0],k[x][1]))\n",
    "draw.polygon((dots), fill='green')\n",
    "image.show()\n",
    "image.save('image1.png')\n",
    "\n",
    "from __future__ import print_function\n",
    "import numpy as np\n",
    "import cv2 as cv\n",
    "import video\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    import sys    \n",
    "    cam = cv2.VideoCapture('/home/ankit/Downloads/opencv-master /samples/data/vtest.avi')\n",
    "    cam.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)\n",
    "    cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)\n",
    "    codec = cv2.VideoWriter_fourcc(*'XVID') \n",
    "    output1 = cv2.VideoWriter('/home/ankit/Downloads/opencv-master /samples/python/just.avi', codec, 60.0,(1920,1080))\n",
    "    ret, prev = cam.read() \n",
    "    grayB = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)\n",
    "    cv2.imshow('grayB', grayB)\n",
    "    \n",
    "    temp_pts = np.array(dots, np.int32).reshape((-2, 1, 2)) .astype(int)\n",
    "    grayC =cv2.polylines(prev, [temp_pts], True, (0, 255,200),thickness=2,)\n",
    "    grayC=cv2.fillPoly(prev, np.int_([temp_pts]), (0, 0,0))\n",
    "    grayD=cv2.cvtColor(grayC, cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "    print(grayD.shape)\n",
    "    print(grayB.shape)\n",
    "    \n",
    "    cv2.imshow('grayC',grayC)\n",
    "    cv2.imshow('grayD',grayD)\n",
    "    #prev1 = cv2.imread('/home/ankit/Desktop/FamilyNight1.jpg')\n",
    "    #print(prev1.shape)\n",
    "    \n",
    "    (score, diff) = compare_ssim(grayB, grayD, full=True)\n",
    "    diff = (diff * 255).astype(\"uint8\")\n",
    "    print(\"SSIM: {}\".format(score))\n",
    "    cv2.imshow('Diff',diff)\n",
    "    cv2.waitKey(0)\n",
    "    cam.release()\n",
    "    output1.release()\n",
    "    cv.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
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    }
   ],
   "source": [
    "#Determine if a point is inside a given polygon or not\n",
    "# Polygon is a list of (x,y) pairs. This function\n",
    "# returns True or False.  The algorithm is called\n",
    "# the \"Ray Casting Method\".\n",
    "\n",
    "iota=[]\n",
    "def isPointInPath(pointa, poly):\n",
    "    \"\"\"\n",
    "    x, y -- x and y coordinates of point\n",
    "    poly -- a list of tuples [(x, y), (x, y), ...]\n",
    "    \"\"\"\n",
    "    \n",
    "    for (x,y) in pointa: \n",
    "        num = len(poly)\n",
    "        i = 0\n",
    "        j = num - 1\n",
    "        c = False\n",
    "        for i in range(num):\n",
    "            if ((poly[i][1] > y) != (poly[j][1] > y)) and \\\n",
    "                    (x < poly[i][0] + (poly[j][0] - poly[i][0]) * (y - poly[i][1])/\n",
    "                                     (poly[j][1] - poly[i][1])):\n",
    "                c = not c\n",
    "            j = i\n",
    "            print(c)\n",
    "        if(c==False):\n",
    "            iota.append((x,y)) \n",
    "    temp_pts1 = np.array(iota, np.int32).reshape((-2, 1, 2)) .astype(int)\n",
    "    grayf=cv2.polylines(prevgray, [temp_pts1],False, (0, 255,200), thickness=2)\n",
    "    cv.imshow('grayf',grayf)\n",
    "    return c\n",
    "\n",
    "def draw_flow(points, flow,dots, step=16):\n",
    "    h,  w = points.shape[:2] # heights  and weights in image (if it is 3 then it also give no. of channel of img)\n",
    "    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int) # mesh-grid gives ndarrays all of the same dimensions\n",
    "    fx, fy = flow[y,x].T\n",
    "    points1 = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2) # vstack is use for to collect the array and make stack of array in vertical form (row wise)\n",
    "    points1 = np.int32(points1 + 0.5)\n",
    "    vis = cv.cvtColor(points, cv.COLOR_GRAY2BGR)\n",
    "     \n",
    "    temp_pts = np.array(dots, np.int32).reshape((-2, 1, 2)) .astype(int)\n",
    "    cv2.polylines(vis, [temp_pts], True, (0, 255,200), thickness=2)  \n",
    "    cv.polylines(vis,points1, True, (0, 255, 200))\n",
    "    for (x1, y1), (_x2, _y2) in points1:\n",
    "        cv.circle(vis, (x1, y1), 1, (0, 255, 0), -1)\n",
    "    return vis \n",
    "\n",
    "if __name__ == '__main__':\n",
    "    import sys  \n",
    "    \n",
    "    cam = cv2.VideoCapture('/home/ankit/Downloads/opencv-master /samples/data/vtest.avi')\n",
    "    cam.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)\n",
    "    cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)\n",
    "    codec = cv2.VideoWriter_fourcc(*'XVID') \n",
    "    output1 = cv2.VideoWriter('/home/ankit/Downloads/opencv-master /samples/python/just.avi', codec, 60.0,(1920,1080))\n",
    "\n",
    "\n",
    "    ret, prev = cam.read() \n",
    "    prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)\n",
    "    r=len(prevgray)\n",
    "    \n",
    "    show_hsv = False\n",
    "    show_glitch = False\n",
    "    cur_glitch = prev.copy()\n",
    "    \n",
    "    pointa=[]\n",
    "    for i in range(0,r):    \n",
    "        k=prevgray[0][i]\n",
    "        a =prevgray[1][i]\n",
    "        pointa.append((k,a))\n",
    "    #print(prevgray)\n",
    "    #print(pointa)\n",
    "    #print(len(prevgray))\n",
    "    #print(len(pointa))\n",
    "    print(isPointInPath(pointa, dots))\n",
    "    \n",
    "    while(cam.isOpened()):\n",
    "        ret, prev = cam.read()\n",
    "        gray = cv.cvtColor(prev, cv.COLOR_BGR2GRAY) \n",
    "        flow = cv.calcOpticalFlowFarneback(prevgray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0) \n",
    "        prevgray = gray\n",
    "        \n",
    "        cv.imshow('flow', draw_flow(gray, flow,dots))                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
    "        \n",
    "        if show_hsv:\n",
    "            cv.imshow('flow HSV', draw_hsv(flow))\n",
    "        if show_glitch:\n",
    "            cur_glitch = warp_flow(cur_glitch, flow)\n",
    "            cv.imshow('glitch', cur_glitch)\n",
    "        ch = cv.waitKey(1)\n",
    "        if ch == 27:\n",
    "            break\n",
    "        if ch == ord('1'):\n",
    "            show_hsv = not show_hsv\n",
    "            print('HSV flow visualization is', ['off', 'on'][show_hsv])\n",
    "        if ch == ord('2'):\n",
    "            show_glitch = not show_glitch\n",
    "            if show_glitch:\n",
    "                cur_glitch = img.copy()\n",
    "            print('glitch is', ['off', 'on'][show_glitch])\n",
    "\n",
    "    cam.release()\n",
    "    output1.release()\n",
    "    cv.destroyAllWindows()\n",
    "\n",
    "\n",
    "\n",
    "## Test\n",
    "\n",
    "#polygon = [(0,10),(10,10),(10,0),(0,0)]\n",
    "\n",
    "#point_x = 0\n",
    "#point_y =380\n",
    "\n",
    "## Call the function with the points and the polygon\n",
    "#print(point_in_poly(gray,dots))\n",
    "\n",
    "              \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Input images must have the same dimensions.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-5-760c9ea74cee>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m    105\u001b[0m         \u001b[0mflow\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalcOpticalFlowFarneback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprevgray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrayB\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m15\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1.2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    106\u001b[0m         \u001b[0mprevgray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgrayB\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 107\u001b[0;31m         \u001b[0mcv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'flow'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdraw_flow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgrayB\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflow\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdots\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m#its shows the image\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    108\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    109\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-5-760c9ea74cee>\u001b[0m in \u001b[0;36mdraw_flow\u001b[0;34m(points, flow, dots, step)\u001b[0m\n\u001b[1;32m     57\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mx1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0m_x2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_y2\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mpoints1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     58\u001b[0m         \u001b[0mcv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcircle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mx1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m255\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 59\u001b[0;31m     \u001b[0;34m(\u001b[0m\u001b[0mscore\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdiff\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompare_ssim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgrayB\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfull\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     60\u001b[0m     \u001b[0mdiff\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdiff\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0;36m255\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"uint8\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     61\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"SSIM: {}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/abc12/lib/python3.7/site-packages/skimage/measure/_structural_similarity.py\u001b[0m in \u001b[0;36mcompare_ssim\u001b[0;34m(X, Y, win_size, gradient, data_range, multichannel, gaussian_weights, full, **kwargs)\u001b[0m\n\u001b[1;32m     83\u001b[0m     \"\"\"\n\u001b[1;32m     84\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 85\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Input images must have the same dimensions.'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     86\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     87\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mmultichannel\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Input images must have the same dimensions."
     ]
    }
   ],
   "source": [
    "import json\n",
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "#import pandas as pd\n",
    "import argparse\n",
    "import PIL.ImageDraw as ImageDraw\n",
    "import PIL.Image as Image\n",
    "import cv2\n",
    "\n",
    "\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "json_file = open(\"/home/ankit/Downloads/Cam_02_North_Ave_EB_Spring_St.json\", \"r\", encoding=\"utf-8\")\n",
    "sh_json= json.load(json_file)\n",
    "json_file.close()\n",
    "\n",
    "dots=[]\n",
    "image = Image.new(\"RGB\", (640, 480))\n",
    "\n",
    "draw = ImageDraw.Draw(image)\n",
    "#print(type( sh_json['Costco_Front_Image_0013.jpg193064']))\n",
    "for person in sh_json:\n",
    "    y=len(sh_json['valid_vertices'])\n",
    "for x in range(0,y):\n",
    "    k=(sh_json['valid_vertices'])\n",
    "    dots.append((k[x][0],k[x][1]))\n",
    "    #print(points)\n",
    "draw.polygon((dots), fill='green')\n",
    "#image.show()\n",
    "#image.save('image1.png')\n",
    "\n",
    "\n",
    "#!/usr/bin/env python\n",
    "\n",
    "# Python 2/3 compatibility\n",
    "from __future__ import print_function\n",
    "\n",
    "import numpy as np\n",
    "import cv2 as cv\n",
    "import video\n",
    "\n",
    "\n",
    "def draw_flow(points, flow,dots, step=16):\n",
    "    h,  w = points.shape[:2] \n",
    "    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int)\n",
    "    fx, fy = flow[y,x].T\n",
    "    points1 = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2)\n",
    "    points1 = np.int32(points1 + 0.5)\n",
    "    vis = cv.cvtColor(points, cv.COLOR_GRAY2BGR)\n",
    "    \n",
    "    temp_pts = np.array(dots, np.int32).reshape((-2, 1, 2)) .astype(int)\n",
    "    cv2.polylines(vis, [temp_pts], True, (0, 255,200), thickness=2)  \n",
    "    cv.polylines(vis, points1, True, (0, 255, 200))\n",
    "    for (x1, y1), (_x2, _y2) in points1:\n",
    "        cv.circle(vis, (x1, y1), 1, (0, 255, 0), -1)\n",
    "    (score, diff) = compare_ssim(grayB, vis, full=True)\n",
    "    diff = (diff * 255).astype(\"uint8\")\n",
    "    print(\"SSIM: {}\".format(score))\n",
    "    cv2.imshow('Diff',diff)\n",
    "    cv2.waitKey(0)\n",
    "    return vis \n",
    "\n",
    "def draw_hsv(flow):\n",
    "    h, w = flow.shape[:2]\n",
    "    fx, fy = flow[:,:,0], flow[:,:,1]\n",
    "    ang = np.arctan2(fy, fx) + np.pi\n",
    "    v = np.sqrt(fx*fx+fy*fy)\n",
    "    hsv = np.zeros((h, w, 3), np.uint8)\n",
    "    hsv[...,0] = ang*(180/np.pi/2)\n",
    "    hsv[...,1] = 255\n",
    "    hsv[...,2] = np.minimum(v*4, 255)\n",
    "    bgr = cv.cvtColor(hsv, cv.COLOR_HSV2BGR)\n",
    "    return bgr\n",
    "\n",
    "\n",
    "def warp_flow(img, flow):\n",
    "    h, w = flow.shape[:2]\n",
    "    flow = -flow\n",
    "    flow[:,:,0] += np.arange(w)\n",
    "    flow[:,:,1] += np.arange(h)[:,np.newaxis]\n",
    "    res = cv.remap(img, flow, None, cv.INTER_LINEAR)\n",
    "    return res\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    import sys    \n",
    "    cam = cv2.VideoCapture('/home/ankit/Downloads/opencv-master /samples/data/vtest.avi')\n",
    "    cam.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)\n",
    "    cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)\n",
    "    codec = cv2.VideoWriter_fourcc(*'XVID') \n",
    "    output1 = cv2.VideoWriter('/home/ankit/Downloads/opencv-master /samples/python/just.avi', codec, 60.0,(1920,1080))\n",
    "    \n",
    "    ret, prev = cam.read() \n",
    "    prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)\n",
    " \n",
    "    show_hsv = False\n",
    "    show_glitch = False\n",
    "    cur_glitch = prev.copy()\n",
    "   \n",
    "    while (cam.isOpened()):\n",
    "        ret, prev = cam.read()\n",
    "        grayB = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)\n",
    "        flow = cv.calcOpticalFlowFarneback(prevgray, grayB, None, 0.5, 3, 15, 3, 5, 1.2, 0)         \n",
    "        prevgray = grayB\n",
    "        cv.imshow('flow', draw_flow(grayB, flow,dots))  #its shows the image\n",
    "        \n",
    "        \n",
    "        if show_hsv:\n",
    "            cv.imshow('flow HSV', draw_hsv(flow))\n",
    "        if show_glitch:\n",
    "            cur_glitch = warp_flow(cur_glitch, flow)\n",
    "            cv.imshow('glitch', cur_glitch)\n",
    "        \n",
    "        \n",
    "\n",
    "        ch = cv.waitKey(1)\n",
    "        if ch == 27:\n",
    "            break\n",
    "        if ch == ord('1'):\n",
    "            show_hsv = not show_hsv\n",
    "            print('HSV flow visualization is', ['off', 'on'][show_hsv])\n",
    "        if ch == ord('2'):\n",
    "            show_glitch = not show_glitch\n",
    "            if show_glitch:\n",
    "                cur_glitch = img.copy()\n",
    "            print('glitch is', ['off', 'on'][show_glitch])\n",
    "    cam.release()\n",
    "    output1.release()\n",
    "    cv.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "example to show optical flow\n",
      "\n",
      "USAGE: opt_flow.py [<video_source>]\n",
      "\n",
      "Keys:\n",
      " 1 - toggle HSV flow visualization\n",
      " 2 - toggle glitch\n",
      "\n",
      "Keys:\n",
      "    ESC    - exit\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import cv2\n",
    "\n",
    "def draw_flow(points, flow,dots, step=16):\n",
    "    h,  w = points.shape[:2] # heights  and weights in image (if it is 3 then it also give no. of channel of img)\n",
    "    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int) # mesh-grid gives ndarrays all of the same dimensions\n",
    "    fx, fy = flow[y,x].T\n",
    "    points1 = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2) # vstack is use for to collect the array and make stack of array in vertical form (row wise)\n",
    "    points1 = np.int32(points1 + 0.5)\n",
    "    vis = cv.cvtColor(points, cv.COLOR_GRAY2BGR)\n",
    "    #temp_pts = np.array(dots, np.int32)\n",
    "    #temp_pts = temp_pts.reshape((-2, 1, 2)) .astype(int)\n",
    "\n",
    "    temp_pts = np.array(dots, np.int32).reshape((-2, 1, 2)) .astype(int)\n",
    "    cv2.polylines(vis, [temp_pts], True, (0, 255,200), thickness=2)  \n",
    "    cv.polylines(vis, points1, True, (0, 255, 200))\n",
    "    for (x1, y1), (_x2, _y2) in points1:\n",
    "        cv.circle(vis, (x1, y1), 1, (0, 255, 0), -1)\n",
    "    fgmask = fgbg.apply(vis)\n",
    "    cv2.imshow('fgmask',vis)\n",
    "    cv2.imshow('frame',fgmask)\n",
    "    return vis \n",
    "\n",
    "def draw_hsv(flow):\n",
    "    h, w = flow.shape[:2]\n",
    "    fx, fy = flow[:,:,0], flow[:,:,1]\n",
    "    ang = np.arctan2(fy, fx) + np.pi\n",
    "    v = np.sqrt(fx*fx+fy*fy)\n",
    "    hsv = np.zeros((h, w, 3), np.uint8)\n",
    "    hsv[...,0] = ang*(180/np.pi/2)\n",
    "    hsv[...,1] = 255\n",
    "    hsv[...,2] = np.minimum(v*4, 255)\n",
    "    bgr = cv.cvtColor(hsv, cv.COLOR_HSV2BGR)\n",
    "    return bgr\n",
    "\n",
    "\n",
    "def warp_flow(img, flow):\n",
    "    h, w = flow.shape[:2]\n",
    "    flow = -flow\n",
    "    flow[:,:,0] += np.arange(w)\n",
    "    flow[:,:,1] += np.arange(h)[:,np.newaxis]\n",
    "    res = cv.remap(img, flow, None, cv.INTER_LINEAR)\n",
    "    return res\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    import sys    #The sys module provides information about constants, functions and methods of the Python interpreter. \n",
    "                  # dir(system) gives of the available constants, functions and methods.\n",
    "    print(__doc__)\n",
    "    cam = cv2.VideoCapture('/home/ankit/Downloads/opencv-master /samples/data/vtest.avi')\n",
    "    fgbg = cv2.createBackgroundSubtractorMOG2()\n",
    "    cam.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)\n",
    "    cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)\n",
    "    codec = cv2.VideoWriter_fourcc(*'XVID') \n",
    "    output1 = cv2.VideoWriter('/home/ankit/Downloads/opencv-master /samples/python/just.avi', codec, 60.0,(1920,1080))\n",
    "    ret, prev = cam.read() \n",
    "    prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)\n",
    "    show_hsv = False\n",
    "    show_glitch = False\n",
    "    cur_glitch = prev.copy()\n",
    "   \n",
    "    while (cam.isOpened()):\n",
    "        ret, prev = cam.read()\n",
    "        \n",
    "        gray = cv.cvtColor(prev, cv.COLOR_BGR2GRAY)\n",
    "        flow = cv.calcOpticalFlowFarneback(prevgray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0) \n",
    "        prevgray = gray\n",
    "        cv.imshow('flow', draw_flow(gray, flow,dots))  #its shows the image\n",
    "        \n",
    "        if show_hsv:\n",
    "            cv.imshow('flow HSV', draw_hsv(flow))\n",
    "        if show_glitch:\n",
    "            cur_glitch = warp_flow(cur_glitch, flow)\n",
    "            cv.imshow('glitch', cur_glitch)\n",
    "            \n",
    "        ch = cv.waitKey(1)\n",
    "        if ch == 27:\n",
    "            break\n",
    "        if ch == ord('1'):\n",
    "            show_hsv = not show_hsv\n",
    "            print('HSV flow visualization is', ['off', 'on'][show_hsv])\n",
    "        if ch == ord('2'):\n",
    "            show_glitch = not show_glitch\n",
    "            if show_glitch:\n",
    "                cur_glitch = img.copy()\n",
    "            print('glitch is', ['off', 'on'][show_glitch])\n",
    "    cam.release()\n",
    "    output1.release()\n",
    "    cv.destroyAllWindows()\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n"
     ]
    }
   ],
   "source": [
    "#Determine if a point is inside a given polygon or not\n",
    "# Polygon is a list of (x,y) pairs. This function\n",
    "# returns True or False.  The algorithm is called\n",
    "# the \"Ray Casting Method\".\n",
    "\n",
    "iota=[]\n",
    "def isPointInPath(pointa, poly):\n",
    "    \"\"\"\n",
    "    x, y -- x and y coordinates of point\n",
    "    poly -- a list of tuples [(x, y), (x, y), ...]\n",
    "    \"\"\"\n",
    "    \n",
    "    for x,y in pointa: \n",
    "        num = len(poly)\n",
    "        i = 0\n",
    "        j = num - 1\n",
    "        c = False\n",
    "        for i in range(num):\n",
    "            if ((poly[i][1] > y) != (poly[j][1] > y)) and \\\n",
    "                    (x < poly[i][0] + (poly[j][0] - poly[i][0]) * (y - poly[i][1]) /\n",
    "                                     (poly[j][1] - poly[i][1])):\n",
    "                c = not c\n",
    "            j = i\n",
    "        if(c==False):\n",
    "            iota.append((x,y))\n",
    "    return c\n",
    "\n",
    "\n",
    "def draw_flow(points, flow,dots, step=16):\n",
    "    h,  w = points.shape[:2] # heights  and weights in image (if it is 3 then it also give no. of channel of img)\n",
    "    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int) # mesh-grid gives ndarrays all of the same dimensions\n",
    "    fx, fy = flow[y,x].T\n",
    "    points1 = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2) # vstack is use for to collect the array and make stack of array in vertical form (row wise)\n",
    "    points1 = np.int32(points1 + 0.5)\n",
    "    vis = cv.cvtColor(points, cv.COLOR_GRAY2BGR)\n",
    "    #temp_pts = np.array(dots, np.int32)\n",
    "    #temp_pts = temp_pts.reshape((-2, 1, 2)) .astype(int)\n",
    "\n",
    "    temp_pts = np.array(dots, np.int32).reshape((-2, 1, 2)) .astype(int)\n",
    "    cv2.polylines(vis, [temp_pts], True, (0, 255,200), thickness=2)  \n",
    "    cv.polylines(vis,points1, True, (0, 255, 200))\n",
    "    for (x1, y1), (_x2, _y2) in points1:\n",
    "        cv.circle(vis, (x1, y1), 1, (0, 255, 0), -1)\n",
    "    return vis \n",
    "\n",
    "if __name__ == '__main__':\n",
    "    import sys  \n",
    "    \n",
    "    cam = cv2.VideoCapture('/home/ankit/Downloads/opencv-master /samples/data/vtest.avi')\n",
    "    cam.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)\n",
    "    cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)\n",
    "    codec = cv2.VideoWriter_fourcc(*'XVID') \n",
    "    output1 = cv2.VideoWriter('/home/ankit/Downloads/opencv-master /samples/python/just.avi', codec, 60.0,(1920,1080))\n",
    "\n",
    "\n",
    "    ret, prev = cam.read() \n",
    "    prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)\n",
    "    r=len(prevgray)\n",
    "    \n",
    "    show_hsv = False\n",
    "    show_glitch = False\n",
    "    cur_glitch = prev.copy()\n",
    "    \n",
    "    pointa=[]\n",
    "    for i in range(0,r):    \n",
    "        k=prevgray[0][i]\n",
    "        a =prevgray[1][i]\n",
    "        pointa.append((k,a))\n",
    "    #print(prevgray)\n",
    "    #print(pointa)\n",
    "    #print(len(prevgray))\n",
    "    #print(len(pointa))\n",
    "    print(isPointInPath(pointa, dots))\n",
    "    \n",
    "    while(cam.isOpened()):\n",
    "        ret, prev = cam.read()\n",
    "        gray = cv.cvtColor(prev, cv.COLOR_BGR2GRAY) \n",
    "        flow = cv.calcOpticalFlowFarneback(prevgray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0) \n",
    "        prevgray = gray\n",
    "        \n",
    "        cv.imshow('flow', draw_flow(gray, flow,dots))                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
    "        \n",
    "        if show_hsv:\n",
    "            cv.imshow('flow HSV', draw_hsv(flow))\n",
    "        if show_glitch:\n",
    "            cur_glitch = warp_flow(cur_glitch, flow)\n",
    "            cv.imshow('glitch', cur_glitch)\n",
    "        ch = cv.waitKey(1)\n",
    "        if ch == 27:\n",
    "            break\n",
    "        if ch == ord('1'):\n",
    "            show_hsv = not show_hsv\n",
    "            print('HSV flow visualization is', ['off', 'on'][show_hsv])\n",
    "        if ch == ord('2'):\n",
    "            show_glitch = not show_glitch\n",
    "            if show_glitch:\n",
    "                cur_glitch = img.copy()\n",
    "            print('glitch is', ['off', 'on'][show_glitch])\n",
    "\n",
    "    cam.release()\n",
    "    output1.release()\n",
    "    cv.destroyAllWindows()\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  }
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