Added draw matches to write text and no lines as mode=3.

.gitignore

@@ -0,0 +1,2 @@
+build/*
+*.pyc

CMakeLists.txt

@@ -1,13 +1,14 @@
 cmake_minimum_required(VERSION 2.8)
 project( gms_match_demo)
+set( CMAKE_CXX_STANDARD 11 )
 
-# OpenCV 
+# OpenCV
 find_package( OpenCV REQUIRED )
 
-# 
-include_directories( 
+#
+include_directories(
  include
-${OpenCV_INCLUDE_DIRS} 
+${OpenCV_INCLUDE_DIRS}
 )
 
 

data/README.md

@@ -0,0 +1,12 @@
+# README on Photos
+
+This describes the photos kf_\*.png
+They photos are drawn from a video sequence. The numbers denote the keyframe number. For example kf_972.png and kf_973.png are consecutive frames. 
+
+There are 3 separate physical locations
+
+- kf_8, kf_12, kf_558, kf_589 are captured in same physical location. 
+
+- kf_972, kf_973, kf_2397 are captured in same physical location. 
+
+- kf_1140, kf_2582, kf_2583 are captured in same physical location.

include/Header.h

@@ -9,11 +9,11 @@
 #include <vector>
 #include <iostream>
 #include <ctime>
+#include <string>
 using namespace std;
 using namespace cv;
 
 #ifdef USE_GPU
 	#include <opencv2/cudafeatures2d.hpp>
 	using cuda::GpuMat;
 #endif
-

include/gms_matcher.h

@@ -3,7 +3,7 @@
 
 #define THRESH_FACTOR 6
 
-// 8 possible rotation and each one is 3 X 3 
+// 8 possible rotation and each one is 3 X 3
 const int mRotationPatterns[8][9] = {
 	1,2,3,
 	4,5,6,
@@ -45,8 +45,8 @@ const double mScaleRatios[5] = { 1.0, 1.0 / 2, 1.0 / sqrt(2.0), sqrt(2.0), 2.0 }
 class gms_matcher
 {
 public:
-	// OpenCV Keypoints & Correspond Image Size & Nearest Neighbor Matches 
-	gms_matcher(const vector<KeyPoint> &vkp1, const Size size1, const vector<KeyPoint> &vkp2, const Size size2, const vector<DMatch> &vDMatches) 
+	// OpenCV Keypoints & Correspond Image Size & Nearest Neighbor Matches
+	gms_matcher(const vector<KeyPoint> &vkp1, const Size size1, const vector<KeyPoint> &vkp2, const Size size2, const vector<DMatch> &vDMatches)
 	{
 		// Input initialize
 		NormalizePoints(vkp1, size1, mvP1);
@@ -58,7 +58,7 @@ class gms_matcher
 		mGridSizeLeft = Size(20, 20);
 		mGridNumberLeft = mGridSizeLeft.width * mGridSizeLeft.height;
 
-		// Initialize the neihbor of left grid 
+		// Initialize the neihbor of left grid
 		mGridNeighborLeft = Mat::zeros(mGridNumberLeft, 9, CV_32SC1);
 		InitalizeNiehbors(mGridNeighborLeft, mGridSizeLeft);
 	};
@@ -87,14 +87,14 @@ class gms_matcher
 	// value  : how many matches from idx_left to idx_right
 	Mat mMotionStatistics;
 
-	// 
+	//
 	vector<int> mNumberPointsInPerCellLeft;
 
 	// Inldex  : grid_idx_left
 	// Value   : grid_idx_right
 	vector<int> mCellPairs;
 
-	// Every Matches has a cell-pair 
+	// Every Matches has a cell-pair
 	// first  : grid_idx_left
 	// second : grid_idx_right
 	vector<pair<int, int> > mvMatchPairs;
@@ -110,7 +110,7 @@ class gms_matcher
 public:
 
 	// Get Inlier Mask
-	// Return number of inliers 
+	// Return number of inliers
 	int GetInlierMask(vector<bool> &vbInliers, bool WithScale = false, bool WithRotation = false);
 
 private:
@@ -177,7 +177,7 @@ class gms_matcher
 		return x + y * mGridSizeRight.width;
 	}
 
-	// Assign Matches to Cell Pairs 
+	// Assign Matches to Cell Pairs
 	void AssignMatchPairs(int GridType);
 
 	// Verify Cell Pairs
@@ -193,7 +193,7 @@ class gms_matcher
 		for (int yi = -1; yi <= 1; yi++)
 		{
 			for (int xi = -1; xi <= 1; xi++)
-			{	
+			{
 				int idx_xx = idx_x + xi;
 				int idx_yy = idx_y + yi;
 
@@ -222,13 +222,13 @@ class gms_matcher
 		mGridSizeRight.height = mGridSizeLeft.height * mScaleRatios[Scale];
 		mGridNumberRight = mGridSizeRight.width * mGridSizeRight.height;
 
-		// Initialize the neihbor of right grid 
+		// Initialize the neihbor of right grid
 		mGridNeighborRight = Mat::zeros(mGridNumberRight, 9, CV_32SC1);
 		InitalizeNiehbors(mGridNeighborRight, mGridSizeRight);
 	}
 
 
-	// Run 
+	// Run
 	int run(int RotationType);
 };
 
@@ -292,7 +292,7 @@ int gms_matcher::GetInlierMask(vector<bool> &vbInliers, bool WithScale, bool Wit
 				vbInliers = mvbInlierMask;
 				max_inlier = num_inlier;
 			}
-			
+
 		}
 		return max_inlier;
 	}
@@ -356,7 +356,7 @@ void gms_matcher::VerifyCellPairs(int RotationType) {
 		int idx_grid_rt = mCellPairs[i];
 
 		const int *NB9_lt = mGridNeighborLeft.ptr<int>(i);
-		const int *NB9_rt = mGridNeighborRight.ptr<int>(idx_grid_rt); 
+		const int *NB9_rt = mGridNeighborRight.ptr<int>(idx_grid_rt);
 
 		int score = 0;
 		double thresh = 0;
@@ -389,13 +389,13 @@ int gms_matcher::run(int RotationType) {
 	mMotionStatistics = Mat::zeros(mGridNumberLeft, mGridNumberRight, CV_32SC1);
 	mvMatchPairs.assign(mNumberMatches, pair<int, int>(0, 0));
 
-	for (int GridType = 1; GridType <= 4; GridType++) 
+	for (int GridType = 1; GridType <= 4; GridType++)
 	{
 		// initialize
 		mMotionStatistics.setTo(0);
 		mCellPairs.assign(mGridNumberLeft, -1);
 		mNumberPointsInPerCellLeft.assign(mGridNumberLeft, 0);
-		
+
 		AssignMatchPairs(GridType);
 		VerifyCellPairs(RotationType);
 
@@ -421,7 +421,7 @@ inline Mat DrawInlier(Mat &src1, Mat &src2, vector<KeyPoint> &kpt1, vector<KeyPo
 	src1.copyTo(output(Rect(0, 0, src1.cols, src1.rows)));
 	src2.copyTo(output(Rect(src1.cols, 0, src2.cols, src2.rows)));
 
-	if (type == 1)
+	if (type == 1) // Only Lines
 	{
 		for (size_t i = 0; i < inlier.size(); i++)
 		{
@@ -430,7 +430,7 @@ inline Mat DrawInlier(Mat &src1, Mat &src2, vector<KeyPoint> &kpt1, vector<KeyPo
 			line(output, left, right, Scalar(0, 255, 255));
 		}
 	}
-	else if (type == 2)
+	else if (type == 2) // Lines and Circles
 	{
 		for (size_t i = 0; i < inlier.size(); i++)
 		{
@@ -447,6 +447,20 @@ inline Mat DrawInlier(Mat &src1, Mat &src2, vector<KeyPoint> &kpt1, vector<KeyPo
 			circle(output, right, 1, Scalar(0, 255, 0), 2);
 		}
 	}
+	else // Circles and Text
+	{
+		for (size_t i = 0; i < inlier.size(); i++)
+		{
+			Point2f left = kpt1[inlier[i].queryIdx].pt;
+			Point2f right = (kpt2[inlier[i].trainIdx].pt + Point2f((float)src1.cols, 0.f));
+			circle(output, left, 1, Scalar(0, 255, 255), 2);
+			circle(output, right, 1, Scalar(0, 255, 0), 2);
+
+			cv::putText( output, to_string(i), left, cv::FONT_HERSHEY_COMPLEX_SMALL, 0.3, cv::Scalar(255,0,255)  );
+			cv::putText( output, to_string(i), right, cv::FONT_HERSHEY_COMPLEX_SMALL, 0.3, cv::Scalar(255,0,255)  );
+
+		}
+	}
 
 	return output;
 }
@@ -456,7 +470,3 @@ inline void imresize(Mat &src, int height) {
 	int width = static_cast<int>(src.cols * 1.0 / ratio);
 	resize(src, src, Size(width, height));
 }
-
-
-
-

python/README.md

@@ -0,0 +1,42 @@
+# Usage of gms_matcher.py
+
+Cntains 2 classes, viz. GmsMatcher and GmsRobe. 
+
+## GmsMatcher 
+This class is the original work as presented in the paper. 
+```
+@inproceedings{bian2017gms,
+  title={GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence},
+  author={JiaWang Bian and Wen-Yan Lin and Yasuyuki Matsushita and Sai-Kit Yeung and Tan Dat Nguyen and Ming-Ming Cheng},
+  booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
+  year={2017}
+}
+```
+
+For demo usage see function, `demo_gms_original_implementation()` in `demo.py`
+
+
+## GmsRobe
+This class extents the functionality of GmsMatcher.
+The GmsMatcher returns an array of DMatch. This might be sometimes convinent to use. 
+As you need to make reference to the keypoints to get to the image co-ordinates in question. 
+
+GmsRobe class defines the following functions
+     - match2( imC, imP )<br/>
+		Given current image(imC) and prev image(imP) returns GMS matches co-ordinates (x,y)_i
+            Essentially this is a thin wrapper around the original GmsMatcher class
+
+
+     - match3( imC, imP, imCm )<br/>
+		To find 3way correspondences, ie. a set of point co-ordinates in imC which also occur in imP and imCm. a<-->b<-->c. Note: The order in which the images is given is critical. 
+
+
+     - match2_guided( imC, pt1, imP ) <br/>
+		Given current image (imC), with pts_C 2xN as input points on imC, the
+        objective is to find these points in previous image (imP)
+
+        The way we do this is to first compute all the matches between imC and imP.
+        Then filter these matches to include only those pysically close to input points.
+
+
+Following functions return 2xN matrix with (x,y) of matches.

python/demo.py

@@ -0,0 +1,125 @@
+## This script has demo use cases for the original GmsMatcher class as well as
+## for the GmsRobe class.
+
+import math
+from enum import Enum
+
+import cv2
+import numpy as np
+cv2.ocl.setUseOpenCL(False)
+
+import time
+import code
+
+
+from gms_matcher import GmsMatcher
+from gms_matcher import GmsRobe
+from gms_matcher import DrawingType
+
+def imresize(src, height):
+    ratio = src.shape[0] * 1.0/height
+    width = int(src.shape[1] * 1.0/ratio)
+    return cv2.resize(src, (width, height))
+
+def demo_match3():
+
+    imgP = cv2.imread("../data/kf_1140.png") #curr
+    imgC = cv2.imread("../data/kf_2583.png") #prev
+    imgCm = cv2.imread("../data/kf_2581.png") #currm
+
+    gms = GmsRobe()
+
+    print 'Test gmsrobe.match3()'
+    startT = time.time()
+    pts_C, pts_P, pts_Cm = gms.match3( imgC, imgP, imgCm )
+    print 'gmsrobe.match3 took (ms): %4.2f' %(1000.*(time.time() - startT ) )
+
+    gridd = gms.plot_3way_match( imgC, pts_C,   imgP, pts_P,    imgCm, pts_Cm, show_random_points=40 )
+    gridd2 = gms.plot_3way_match( imgC, pts_C,   imgP, pts_P,    imgCm, pts_Cm, show_random_points=-1, enable_lines=False )
+    cv2.imshow( 'showing 3way match. Randomly selected 40 points only', gridd )
+    cv2.imshow( 'showing 3way match.', gridd2 )
+    cv2.waitKey(0)
+
+
+
+def demo_match2_guided():
+
+    print 'Test gmsrobe.match2_guided()'
+    imgP = cv2.imread("../data/kf_1140.png") #curr
+    imgC = cv2.imread("../data/kf_2583.png") #prev
+
+    orb = cv2.ORB_create(50)
+    kp1 = orb.detect(imgC, None)
+    print 'nORB Pts:', len(kp1)
+    pts_C = np.transpose( np.array([ np.array(k.pt) for k in kp1 ]) ) #2xN
+
+
+    gms = GmsRobe()
+
+    startT = time.time()
+    ptC, ptP = gms.match2_guided( imgC, pts_C, imgP )
+    print 'Elapsed total (ms): %4.2f' %(1000.0 * (time.time() - startT )  )
+    print 'nGuided Pts: ', ptC.shape[1]
+
+    cv2.imshow( 'orb points on curr', gms.plot_points_on_image( imgC, pts_C ) )
+    cv2.imshow( 'xcanvas', gms.plot_point_sets( imgC, ptC, imgP, ptP ) )
+    cv2.waitKey(0)
+
+
+
+
+def demo_match2():
+    print 'Test simple gmsrobe.match2()'
+    imgP = cv2.imread("../data/kf_972.png") #curr
+    imgC = cv2.imread("../data/kf_973.png") #prev
+
+    gms = GmsRobe()
+
+    startT = time.time()
+    ptC, ptP = gms.match2( imgC, imgP )
+    print 'Elapsed total (ms): %4.2f' %(1000.0 * (time.time() - startT )  )
+
+
+    xcanvas = gms.plot_point_sets( imgC, ptC, imgP, ptP, enable_lines=False )
+    xcanvas2 = gms.plot_point_sets( imgC, ptC, imgP, ptP, show_random_points=60 )
+
+    # r = np.random.randint( 0, ptC.shape[1], 50 )
+    # xcanvas = gms.plot_point_sets( imgC, ptC[:,r], imgCm, ptCm[:,r] )
+    cv2.imshow( 'All matches', xcanvas )
+    cv2.imshow( 'Only show 60 random matches', xcanvas2 )
+    cv2.waitKey(0)
+
+
+
+def demo_gms_original_implementation():
+    print 'Test for Original GMS Implementation, ie. class GmsMatcher'
+    # img1 = cv2.imread("../data/nn_left.jpg")
+    # img2 = cv2.imread("../data/nn_right.jpg")
+
+    # img1 = imresize(img1, 240)
+    # img2 = imresize(img2, 240)
+
+    img1 = cv2.imread("../data/kf_2581.png")
+    img2 = cv2.imread("../data/kf_2583.png")
+
+
+    gms = GmsMatcher(verbosity=1)
+    startT = time.time()
+    matches = gms.compute_matches(img1, img2)
+    print 'gms.compute_matches took (ms): %4.2f' %(1000.*(time.time() - startT ) )
+    gms.draw_matches(img1, img2, DrawingType.POINTS_AND_TEXT)
+
+if __name__ == '__main__':
+    # Try any of the 4 demos.
+    which_demo = raw_input('a:demo_match3\nb:demo_match2_guided\nc:demo_match2\nd:demo_gms_original_implementation\nWhich demo do you want to try? ')
+    print( '%s' %(which_demo))
+
+    if which_demo == 'a':
+        demo_match3()
+    if which_demo == 'b':
+        demo_match2_guided()
+    if which_demo == 'c':
+        demo_match2()
+
+    if which_demo == 'd':
+        demo_gms_original_implementation()