Changeset 687

Timestamp:

02/21/10 16:41:59 (2 years ago)

Author:

mosttw

Message:

Changes to hist_test.m that speed it up, but broke the Hough transform

Location:

branches/2010-image-rec

Files:

: 1 removed
: 3 modified

docs/report.pdf (modified) (previous)
hist_test.asv (deleted)
hist_test.m (modified) (11 diffs)
run.sh (modified) (1 diff)

Legend:

: Unmodified
: Added
: Removed

branches/2010-image-rec/hist_test.m

r683	r687
1		function hist_test(fn, show_images)
2
3		% Test how well histogramming works with our test images
4		%fn = 'images/course-walk/cimg4943.jpg';
5		%fn = 'images/course-walk/cimg4921.jpg';
6		%fn = 'images/elphel/cam-000078.jpeg';
7		%$fn = 'images/elphel/cam-000086.jpeg'; % Hard image
8		%fn = 'images/course-walk/cimg4989.jpg';
9
10		%fn = 'images/elphel/cam-000094.jpeg';
11		fn = 'images/elphel/cam-000081.jpeg';
12
13		fprintf('Running on %s... ', fn);
	1	function hist_test(fn)
	2
	3	show_images = 1;
	4
	5	if show_images
	6	close all;
	7	%fn = 'images/course-walk/cimg4943.jpg';
	8	%fn = 'images/course-walk/cimg4921.jpg';
	9	%fn = 'images/elphel/cam-000078.jpeg';
	10	%$fn = 'images/elphel/cam-000086.jpeg'; % Hard image
	11	%fn = 'images/course-walk/cimg4989.jpg';
	12
	13	%fn = 'images/elphel/cam-000094.jpeg';
	14	fn = 'images/elphel/cam-000081.jpeg';
	15	end
	16
	17	fprintf('Running on %s...\n', fn);
14	18
15	19	% Number of bins in the histogram.
…	…
24	28	s_mean_factor = 0.2; % Seems to most effect obstacle detection
25	29	v_mean_factor = 0.1; % Obstacles and lines
26		t_mean_factor = 0.01;
27		texture_band = 2;
	30	%t_mean_factor = 0.01;
	31	%texture_band = 2;
28	32
29	33	im_rgb = imread(fn);
…	…
33	37
34	38	im = zeros(rows, cols, 4);
35		~~imbig = rgb2hsv(im_rgb);~~
36	39	im_rgb = imresize(im_rgb, 0.25);
37	40
38
39		%fsobel = fspecial('sobel');
40		%hedges = filter2(fsobel , imbig(:,:,texture_band));
41		%vedges = filter2(fsobel', imbig(:,:,texture_band));
42		%edges = sqrt(hedges .^ 2 + vedges .^ 2);
	41	%fprintf('Sobelizing\n');
43	42	edges = double(imread([fn '-sobel-v-5.png']))/255;
44		texture = filter2(fspecial('average', 10), edges);
45		texture = filter2(fspecial('average', 10), texture);
46		texture = filter2(fspecial('average', 10), texture);
47		texture = filter2(fspecial('average', 10), texture);
48		texture = filter2(fspecial('average', 10), texture);
49		texture = filter2(fspecial('average', 10), texture);
50		texture = filter2(fspecial('average', 10), texture);
51		texture = filter2(fspecial('average', 10), texture);
52		texture = filter2(fspecial('average', 10), texture);
53		texture = filter2(fspecial('average', 10), texture);
54		texture = filter2(fspecial('average', 10), texture);
	43
	44	fprintf('Blurring sobel\n');
	45	texture = imresize(edges, .25);
	46	%texture = filter2(fspecial('average', 3), texture);
55	47	texture(texture > 1) = 1;
56	48
57		figure(1);
58		imwrite(texture, [fn '-texture-full.png']);
59
60		texture = imresize(texture, .25);
61
	49	if show_images
	50	figure('Name','Texture'), imshow(texture);
	51	else
	52	imwrite(texture, [fn '-texture.png']);
	53	end
	54
	55
	56	fprintf('Histogramming\n');
62	57	im(:,:,1:3) = rgb2hsv(im_rgb);
63		im(:,:,4) = texture;
	58	%im(:,:,4) = texture;
64	59
65	60
…	…
73	68	grass_s_hist = hist(reshape(clear_area(:,:,2), 1, []), hist_bins);
74	69	grass_v_hist = hist(reshape(clear_area(:,:,3), 1, []), hist_bins);
75		grass_t_hist = hist(reshape(clear_area(:,:,4), 1, []), hist_bins);
	70	%grass_t_hist = hist(reshape(clear_area(:,:,4), 1, []), hist_bins);
76	71
77	72	%hist(reshape(clear_area(:,:,1), 1, []), hist_bins); %displays histogram
…	…
82	77	s = ceil(im(:,:,2) * (hist_bins - 1)) + 1;
83	78	v = ceil(im(:,:,3) * (hist_bins - 1)) + 1;
84		t = ceil(im(:,:,4) * (hist_bins - 1)) + 1;
	79	%t = ceil(im(:,:,4) * (hist_bins - 1)) + 1;
85	80
86	81	% Make masks from the histograms.
…	…
94	89	%grass_t_mask(grass_t_hist < mean(grass_t_hist) * t_mean_factor) = 0;
95	90
	91	fprintf('Generating mask\n');
96	92	% Ungodly slow loop through the pixels
97	93	mask = zeros(rows, cols);
…	…
99	95	for c = 1:cols
100	96	if grass_h_mask(h(r,c)) && grass_s_mask(s(r,c)) && ...
101		grass_v_mask(v(r,c)) ~~...~~ && grass_t_mask(t(r,c))
102		mask(r,c) = 1;
	97	grass_v_mask(v(r,c)) % && grass_t_mask(t(r,c))
	98	mask(r, c) = 1;
103	99	end
104	100	end
105	101	end
106	102
107		imwrite(mask, [fn '-mask-raw.png']);
	103	if show_images
	104	figure('Name','Raw mask'), imshow(mask)
	105	else
	106	imwrite(mask, [fn '-mask-raw.png']);
	107	end
108	108
109	109	% Clean things up a bit
…	…
111	111	mask = imclose(mask, se);
112	112
113		imwrite(mask, [fn, '-mask-closed.png']);
114
115		tempMask=mask*-1+1;
116		bottomlist=bottomFind(tempMask);
117		imshow(tempMask);
	113	if show_images
	114	figure('Name','Cleaned up mask'), imshow(mask)
	115	else
	116	imwrite(mask, [fn '-mask-cleaned.png']);
	117	end
	118
	119	fprintf('Locating obstacles\n');
	120	tempMask = mask * -1 + 1;
	121	bottomlist = bottomFind(tempMask);
	122	figure('Name','Obstacle points'), imshow(im_rgb);
118	123	hold on;
119		scatter(bottomlist(:,1),-bottomlist(:,2));
120		print('-depsc', [fn '-obstacle-points.png']);
121
122		line_mask = texture;
	124	scatter(bottomlist(:,1), -bottomlist(:,2));
	125	if ~show_images
	126	print('-depsc', [fn '-obstacle-points.eps']);
	127	end
	128
	129	line_mask = zeros(size(texture));
123	130	threshold = .42;
124	131	line_mask(texture > threshold & mask == 0) = 1;
125		line_mask(texture <= threshold \| mask ~= 0) = 0;
126		imwrite(line_mask, [fn '-line-mask.png']);
	132	if show_images
	133	figure('Name','Line mask'), imshow(line_mask)
	134	else
	135	imwrite(line_mask, [fn '-line-mask.png']);
	136	end
127	137
128	138	% Display
129		figure(2);
130		imshow([double(im_rgb) / 255])%; bw2rgb(mask)]);
	139	figure('Name','Clear area'), imshow([double(im_rgb) / 255])%; bw2rgb(mask)]);
131	140
132	141	% Draw a box over the "clear" area
…	…
137	146	line([left_x right_x right_x left_x left_x], ...
138	147	[top_y top_y bottom_y bottom_y top_y],'LineWidth',4,'Color','red');
139
140		%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
141
142		figure(3);
	148
	149	if ~show_images
	150	print('-depsc', [fn '-clear-area.png']);
	151	end
	152
	153
	154	fprintf('Hough transform\n');
143	155
144	156	[H,T,R] = hough(line_mask);
	157	figure('Name','Hough peaks');
145	158	imshow(H,[],'XData',T,'YData',R,'InitialMagnification','fit');
146	159	xlabel('\theta'), ylabel('\rho');
…	…
150	163	y = R(P(:,1));
151	164	plot(x,y,'s','color','white');
152		print('-depsc', [fn '-hough-peaks.eps']);
	165	if ~show_images
	166	print('-depsc', [fn '-hough-peaks.eps']);
	167	end
153	168
154	169	lines = houghlines(line_mask,T,R,P,'FillGap',5,'MinLength',7);
155		figure, imshow(im_rgb), hold on
156		max_len = 0;
	170	figure('Name','Hough lines'), imshow(im_rgb), hold on
157	171	for k = 1:length(lines)
158	172	xy = [lines(k).point1; lines(k).point2];
…	…
162	176	plot(xy(1,1),xy(1,2),'x','LineWidth',8,'Color','yellow');
163	177	plot(xy(2,1),xy(2,2),'x','LineWidth',8,'Color','red');
164
165		% determine the endpoints of the longest line segment
166		len = norm(lines(k).point1 - lines(k).point2);
167		if ( len > max_len)
168		max_len = len;
169		xy_long = xy;
170		end
171		end
172
173		% highlight the longest line segment
174		plot(xy_long(:,1),xy_long(:,2),'LineWidth',8,'Color','cyan');
175		print('-depsc', [fn '-hough-lines.eps']);
176
177
178		%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	178	end
	179
	180	if ~show_points
	181	print('-depsc', [fn '-hough-lines.eps']);
	182	end
	183
179	184
180	185	fprintf('Done\n');

branches/2010-image-rec/run.sh

r683	r687
12	12	fi
13	13	matlab $MFLAGS -r "hist_test('"$i"'); exit"
	14	exit
14	15	done
15	16