opencv-descriptor.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A test of OpenCV feature descriptors (please see https://youtu.be/qBw1OVd_i6Q)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Test on different feature descriptor in OpenCV\n",
    "# Note that you need to install opencv-contrib-python besides opencv-python\n",
    "# some versions of OpenCV does not work, 3.4.2.16 should work\n",
    "# pip install --user opencv-python==3.4.2.16\n",
    "# pip install --user opencv-contrib-python==3.4.2.16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "from scipy.stats import norm\n",
    "from scipy.signal import convolve2d\n",
    "\n",
    "cap = cv2.VideoCapture(1) # using my webcam\n",
    "window_name='camera'\n",
    "\n",
    "cv2.namedWindow(window_name,cv2.WND_PROP_FULLSCREEN)\n",
    "cv2.setWindowProperty(window_name,cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)\n",
    "\n",
    "# desc = cv2.xfeatures2d.SIFT_create()\n",
    "# desc = cv2.xfeatures2d.SURF_create()\n",
    "# desc = cv2.KAZE_create()\n",
    "# desc = cv2.AKAZE_create()\n",
    "desc = cv2.BRISK_create()\n",
    "\n",
    "while (True):\n",
    "    ret, frame = cap.read()\n",
    "    frame=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "    (kps, descs) = desc.detectAndCompute(frame, None)\n",
    "    img2 = cv2.drawKeypoints(frame,kps,frame.copy(),color=(0,255,0), flags=0)\n",
    "    \n",
    "    cv2.imshow(window_name,img2)\n",
    "#    out.write(frame)\n",
    "    if cv2.waitKey(1) & 0xFF == ord('q'): # btw, you need to click the screen first. And then \n",
    "                                         # press q to quit\n",
    "        break\n",
    "        \n",
    "cap.release()\n",
    "\n",
    "#out.release()\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Try to match features of webcam frames with a pre-captured image. You will need to change the filename 'window.jpg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "from scipy.stats import norm\n",
    "from scipy.signal import convolve2d\n",
    "\n",
    "cap = cv2.VideoCapture(1)\n",
    "window_name='camera'\n",
    "\n",
    "img1 = cv2.imread('window.jpg', cv2.IMREAD_GRAYSCALE)\n",
    "\n",
    "cv2.namedWindow(window_name,cv2.WND_PROP_FULLSCREEN)\n",
    "cv2.setWindowProperty(window_name,cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)\n",
    "\n",
    "\n",
    "\n",
    "# desc = cv2.xfeatures2d.SIFT_create()\n",
    "desc = cv2.xfeatures2d.SURF_create()\n",
    "# desc = cv2.KAZE_create()\n",
    "# desc = cv2.AKAZE_create()\n",
    "# desc = cv2.BRISK_create()\n",
    "\n",
    "kps1, descs1 = desc.detectAndCompute(img1, None)\n",
    "matcher = cv2.DescriptorMatcher_create(cv2.DescriptorMatcher_FLANNBASED)\n",
    "\n",
    "while (True):\n",
    "    ret, frame = cap.read()\n",
    "    img2=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "    (kps, descs) = desc.detectAndCompute(img2, None)\n",
    "    knn_matches = matcher.knnMatch(descs1, descs, 2)\n",
    "\n",
    "    \n",
    "    ratio_thresh = 0.6\n",
    "    good_matches = []\n",
    "    for m,n in knn_matches:\n",
    "        if m.distance < ratio_thresh * n.distance:\n",
    "            good_matches.append(m)  \n",
    "            \n",
    "    #-- Draw matches\n",
    "    img_matches = np.empty((max(img1.shape[0], img2.shape[0]), img1.shape[1]+img2.shape[1], 3), dtype=np.uint8)\n",
    "    cv2.drawMatches(img1, kps1, img2, kps, good_matches, img_matches, flags=cv2.DrawMatchesFlags_NOT_DRAW_SINGLE_POINTS)\n",
    "    #-- Show detected matches\n",
    "#     cv2.imshow('Good Matches', img_matches)\n",
    "    cv2.imshow(window_name,img_matches)\n",
    "    #    out.write(frame)\n",
    "    if cv2.waitKey(1) & 0xFF == ord('q'): # btw, you need to click the screen first. And then \n",
    "                                         # press q to quit\n",
    "        break\n",
    "        \n",
    "cap.release()\n",
    "\n",
    "#out.release()\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Like the above, but also warp one of the image to match the other"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "from scipy.stats import norm\n",
    "from scipy.signal import convolve2d\n",
    "\n",
    "cap = cv2.VideoCapture(1)\n",
    "window_name='camera'\n",
    "\n",
    "img1 = cv2.imread('window.jpg', cv2.IMREAD_GRAYSCALE)\n",
    "\n",
    "cv2.namedWindow(window_name)\n",
    "cv2.namedWindow('warp')\n",
    "#cv2.namedWindow(window_name,cv2.WND_PROP_FULLSCREEN)\n",
    "#cv2.setWindowProperty(window_name,cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)\n",
    "\n",
    "\n",
    "\n",
    "# desc = cv2.xfeatures2d.SIFT_create()\n",
    "desc = cv2.xfeatures2d.SURF_create()\n",
    "# desc = cv2.KAZE_create()\n",
    "# desc = cv2.AKAZE_create()\n",
    "# desc = cv2.BRISK_create()\n",
    "\n",
    "kps1, descs1 = desc.detectAndCompute(img1, None)\n",
    "matcher = cv2.DescriptorMatcher_create(cv2.DescriptorMatcher_FLANNBASED)\n",
    "\n",
    "while (True):\n",
    "    ret, frame = cap.read()\n",
    "    img2=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "    (kps, descs) = desc.detectAndCompute(img2, None)\n",
    "    knn_matches = matcher.knnMatch(descs1, descs, 2)\n",
    "\n",
    "    \n",
    "    ratio_thresh = 0.6\n",
    "    good_matches = []\n",
    "    for m,n in knn_matches:\n",
    "        if m.distance < ratio_thresh * n.distance:\n",
    "            good_matches.append(m)  \n",
    "            \n",
    "    #-- Draw matches\n",
    "    if len(good_matches)> 15:\n",
    "        h, status = cv2.findHomography(np.array([[*(kps1[q.queryIdx].pt)] for q in good_matches]), \\\n",
    "                   np.array([[*(kps[q.trainIdx].pt)] for q in good_matches]),method=cv2.RANSAC)\n",
    "        if h is None:\n",
    "            continue\n",
    "        im_out = cv2.warpPerspective(img1, h, (img2.shape[1],img2.shape[0]))\n",
    "        cv2.imshow('warp',im_out)\n",
    "    \n",
    "    img_matches = np.empty((max(img1.shape[0], img2.shape[0]), img1.shape[1]+img2.shape[1], 3), dtype=np.uint8)\n",
    "    cv2.drawMatches(img1, kps1, img2, kps, good_matches, img_matches, flags=cv2.DrawMatchesFlags_NOT_DRAW_SINGLE_POINTS)\n",
    "    #-- Show detected matches\n",
    "#     cv2.imshow('Good Matches', img_matches)\n",
    "    cv2.imshow(window_name,img_matches)\n",
    "    #    out.write(frame)\n",
    "    if cv2.waitKey(1) & 0xFF == ord('q'): # btw, you need to click the screen first. And then \n",
    "                                         # press q to quit\n",
    "        break\n",
    "        \n",
    "cap.release()\n",
    "\n",
    "#out.release()\n",
    "\n",
    "cv2.destroyAllWindows()"
   ]
  }
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