Mercurial Hosting > traffic-intelligence
changeset 238:be3761a09b20
added functions to input point correspondences
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
---|---|
date | Mon, 09 Jul 2012 00:46:04 -0400 |
parents | 6774bdce03f1 |
children | 93c26e45efd8 |
files | python/compute-homography.py |
diffstat | 1 files changed, 61 insertions(+), 18 deletions(-) [+] |
line wrap: on
line diff
--- a/python/compute-homography.py Fri Jul 06 01:08:38 2012 -0400 +++ b/python/compute-homography.py Mon Jul 09 00:46:04 2012 -0400 @@ -2,13 +2,14 @@ import sys,getopt +import matplotlib.pyplot as plt import numpy as np import cv2 import cvutils import utils -options, args = getopt.getopt(sys.argv[1:], 'h',['help','video_frame=']) +options, args = getopt.getopt(sys.argv[1:], 'hp:i:w:n:u:',['help']) options = dict(options) # TODO process camera intrinsic and extrinsic parameters to obtain image to world homography, taking example from Work/src/python/generate-homography.py script @@ -51,29 +52,71 @@ # cvFindHomography(imagePoints, worldPoints, H); +if '--help' in options.keys() or '-h' in options.keys() or len(options) == 0: + print('Usage: {0} --help|-h [-p point-correspondences.txt] [ -i video-frame] [ -w world-frame] [n number-points] [-u unit-per-pixel=1]'.format(sys.argv[0])) + print('''The input data can be provided either as point correspondences already saved + in a text file or inputed by clicking a certain number of points (>=4) + in a video frame and a world image. -if '--help' in options.keys() or '-h' in options.keys() or len(args) == 0: - print('Usage: {0} --help|-h [--video_frame <video frame filename>] [<point_correspondences.txt>]'.format(sys.argv[0])) - print('''The positional argument should be the name - of a file containing at least 4 non-colinear point coordinates (point correspondences: +The point correspondence file contains at least 4 non-colinear point coordinates +with the following format: - the first two lines are the x and y coordinates in the projected space (usually world space) - the last two lines are the x and y coordinates in the origin space (usually image space) -if providing a video frame, the image points and back projected world points will be plotted''') +If providing video and world images, with a number of points to input +and a ration to convert pixels to world distance unit (eg meters per pixel), +the images will be shown in turn and the user should click +in the same order the corresponding points in world and image spaces. ''') sys.exit() -dstPts, srcPts = cvutils.loadPointCorrespondences(args[0]) -homography, mask = cv2.findHomography(srcPts, dstPts) # method=0, ransacReprojThreshold=3 -np.savetxt(utils.removeExtension(sys.argv[1])+'-homography.txt',homography) +homography = np.array([]) +if '-p' in options.keys(): + worldPts, videoPts = cvutils.loadPointCorrespondences(args[0]) + homography, mask = cv2.findHomography(videoPts, worldPts) # method=0, ransacReprojThreshold=3 +elif '-i' in options.keys() and '-w' in options.keys(): + nPoints = 4 + if '-n' in options.keys(): + nPoints = int(options['-n']) + unitsPerPixel = 1 + if '-u' in options.keys(): + unitsPerPixel = float(options['-u']) + worldImg = plt.imread(options['-w']) + videoImg = plt.imread(options['-i']) + print('Click on {0} points in the video frame'.format(nPoints)) + plt.figure() + plt.imshow(videoImg) + videoPts = np.array(plt.ginput(nPoints)) + print('Click on {0} points in the world image'.format(nPoints)) + plt.figure() + plt.imshow(worldImg) + worldPts = unitsPerPixel*np.array(plt.ginput(nPoints)) + plt.close('all') + homography, mask = cv2.findHomography(videoPts, worldPts) + # save the points in file + f = open('point-correspondences.txt', 'a') + np.savetxt(f, worldPts.T) + np.savetxt(f, videoPts.T) + f.close() -if '--video_frame' in options.keys() and homography.size>0: - img = cv2.imread(options['--video_frame']) - for p in srcPts: - cv2.circle(img,tuple(p),2,cvutils.cvRed) +if homography.size>0: + np.savetxt('homography.txt',homography) + +if '-i' in options.keys() and homography.size>0: + videoImg = cv2.imread(options['-i']) + worldImg = cv2.imread(options['-w']) invHomography = np.linalg.inv(homography) - projectedDstPts = cvutils.projectArray(invHomography, dstPts.T).T - for i,p in enumerate(projectedDstPts): - cv2.circle(img,tuple(np.int32(np.round(p))),2,cvutils.cvBlue) - print('img: {0} / projected: {1}'.format(srcPts[i], p)) - cv2.imshow('video frame',img) + projectedWorldPts = cvutils.projectArray(invHomography, worldPts.T).T + if '-u' in options.keys(): + unitsPerPixel = float(options['-u']) + projectedVideoPts = cvutils.projectArray(invHomography, videoPts.T).T + for i in range(worldPts.shape[0]): + cv2.circle(videoImg,tuple(np.int32(np.round(videoPts[i]))),2,cvutils.cvRed) + cv2.circle(videoImg,tuple(np.int32(np.round(projectedWorldPts[i]))),2,cvutils.cvBlue) + if '-u' in options.keys(): + cv2.circle(worldImg,tuple(np.int32(np.round(worldPts[i]/unitsPerPixel))),2,cvutils.cvRed) + cv2.circle(worldImg,tuple(np.int32(np.round(projectedVideoPts[i]/unitsPerPixel))),2,cvutils.cvRed) + #print('img: {0} / projected: {1}'.format(videoPts[i], p)) + cv2.imshow('video frame',videoImg) + if '-u' in options.keys(): + cv2.imshow('world image',worldImg) cv2.waitKey()