added the validator for dpm

The current result is : 74.36% (31), a little lower than DPM and
HOG implementations. But, this result is without bounding box prediction
such that some correct result may be classified as false alarms.

bin/bbfdetect.c

@@ -17,10 +17,10 @@ int main(int argc, char** argv)
 	ccv_dense_matrix_t* image = 0;
 	ccv_bbf_classifier_cascade_t* cascade = ccv_load_bbf_classifier_cascade(argv[2]);
 	ccv_read(argv[1], &image, CCV_IO_GRAY | CCV_IO_ANY_FILE);
+	ccv_bbf_param_t params = { .interval = 5, .min_neighbors = 2, .flags = 0, .size = ccv_size(24, 24) };
 	if (image != 0)
 	{
 		unsigned int elapsed_time = get_current_time();
-		ccv_bbf_param_t params = { .interval = 5, .min_neighbors = 2, .flags = 0, .size = ccv_size(24, 24) };
 		ccv_array_t* seq = ccv_bbf_detect_objects(image, &cascade, 1, params);
 		elapsed_time = get_current_time() - elapsed_time;
 		for (i = 0; i < seq->rnum; i++)
@@ -33,21 +33,21 @@ int main(int argc, char** argv)
 		ccv_matrix_free(image);
 	} else {
 		FILE* r = fopen(argv[1], "rt");
-		if (argc == 3)
-			chdir(argv[2]);
+		if (argc == 4)
+			chdir(argv[3]);
 		if(r)
 		{
-			char file[1000 + 1];
-			while(fgets(file, 1000, r))
+			size_t len = 1024;
+			char* file = (char*)malloc(len);
+			ssize_t read;
+			while((read = getline(&file, &len, r)) != -1)
 			{
-				int len = (int)strlen(file);
-				while(len > 0 && isspace(file[len - 1]))
-					len--;
-				file[len] = '\0';
+				while(read > 1 && isspace(file[read - 1]))
+					read--;
+				file[read] = 0;
 				image = 0;
 				ccv_read(file, &image, CCV_IO_GRAY | CCV_IO_ANY_FILE);
 				assert(image != 0);
-				ccv_bbf_param_t params = { .interval = 5, .min_neighbors = 2, .flags = 0, .size = ccv_size(24, 24) };
 				ccv_array_t* seq = ccv_bbf_detect_objects(image, &cascade, 1, params);
 				for (i = 0; i < seq->rnum; i++)
 				{
@@ -57,6 +57,7 @@ int main(int argc, char** argv)
 				ccv_array_free(seq);
 				ccv_matrix_free(image);
 			}
+			free(file);
 			fclose(r);
 		}
 	}

bin/dpmdetect.c

@@ -17,10 +17,10 @@ int main(int argc, char** argv)
 	ccv_dense_matrix_t* image = 0;
 	ccv_read(argv[1], &image, CCV_IO_ANY_FILE);
 	ccv_dpm_mixture_model_t* model = ccv_load_dpm_mixture_model(argv[2]);
+	ccv_dpm_param_t params = { .interval = 8, .min_neighbors = 2, .flags = 0, .threshold = -0.3 };
 	if (image != 0)
 	{
 		unsigned int elapsed_time = get_current_time();
-		ccv_dpm_param_t params = { .interval = 8, .min_neighbors = 2, .flags = 0, .threshold = -0.3 };
 		ccv_array_t* seq = ccv_dpm_detect_objects(image, &model, 1, params);
 		elapsed_time = get_current_time() - elapsed_time;
 		if (seq)
@@ -38,6 +38,40 @@ int main(int argc, char** argv)
 			printf("elapsed time %dms\n", elapsed_time);
 		}
 		ccv_matrix_free(image);
+	} else {
+		FILE* r = fopen(argv[1], "rt");
+		if (argc == 4)
+			chdir(argv[3]);
+		if(r)
+		{
+			size_t len = 1024;
+			char* file = (char*)malloc(len);
+			ssize_t read;
+			while((read = getline(&file, &len, r)) != -1)
+			{
+				while(read > 1 && isspace(file[read - 1]))
+					read--;
+				file[read] = 0;
+				image = 0;
+				ccv_read(file, &image, CCV_IO_GRAY | CCV_IO_ANY_FILE);
+				assert(image != 0);
+				ccv_array_t* seq = ccv_dpm_detect_objects(image, &model, 1, params);
+				if (seq != 0)
+				{
+					for (i = 0; i < seq->rnum; i++)
+					{
+						ccv_root_comp_t* comp = (ccv_root_comp_t*)ccv_array_get(seq, i);
+						printf("%s %d %d %d %d %f %d\n", file, comp->rect.x, comp->rect.y, comp->rect.width, comp->rect.height, comp->confidence, comp->pnum);
+						for (j = 0; j < comp->pnum; j++)
+						printf("| %d %d %d %d %f\n", comp->part[j].rect.x, comp->part[j].rect.y, comp->part[j].rect.width, comp->part[j].rect.height, comp->part[j].confidence);
+					}
+					ccv_array_free(seq);
+				}
+				ccv_matrix_free(image);
+			}
+			free(file);
+			fclose(r);
+		}
 	}
 	ccv_drain_cache();
 	return 0;

bin/dpmvldtr.rb

@@ -0,0 +1,61 @@
+#!/usr/bin/env ruby
+
+exit unless ARGV.length == 2
+
+truth = Hash.new
+total = 0
+
+files = Dir.glob(ARGV[0] + '/*.txt')
+
+files.each do |file|
+	name = nil;
+	boxes = Array.new
+	File.new(file).each_line do |line|
+		next if line[0] == '#'
+		name = line[line.rindex('/') + 1, line.rindex('"') - (line.rindex('/') + 1)] if line[0, 14].downcase  == "image filename"
+		if line[0, 16].downcase == "bounding box for"
+			i = line.scan(/object\s*(\d+)/)[0][0].to_i
+			coord = line.scan(/\((\d+),\s*(\d+)\)\s*-\s*\((\d+),\s*(\d+)\)/)[0]
+			boxes[i - 1] = { :x => coord[0].to_i, :y => coord[1].to_i, :width => coord[2].to_i - coord[0].to_i, :height => coord[3].to_i - coord[1].to_i }
+		end
+	end
+	truth[name] = boxes;
+	total += boxes.length;
+end
+
+fa = 0
+tp = 0
+
+File.new(ARGV[1]).each_line do |line|
+	next if line[0] == '|'
+	args = line.split(" ")
+	name = args[0][args[0].rindex('/') + 1, args[0].length - (args[0].rindex('/') + 1)]
+	if !truth[name]
+		fa += 1
+	else
+		x = args[1].to_i
+		y = args[2].to_i
+		width = args[3].to_i
+		height = args[4].to_i
+		outlier = true
+		truth[name].each do |obj|
+			opx_min = [obj[:x], x].max
+			opy_min = [obj[:y], y].max
+			opx_max = [obj[:x] + obj[:width], x + width].min
+			opy_max = [obj[:y] + obj[:height], y + height].min
+			r0 = [opx_max - opx_min, 0].max * [opy_max - opy_min, 0].max
+			r1 = obj[:width] * obj[:height] * 0.5
+			if r0 > r1
+				outlier = false
+				break
+			end
+		end
+		if outlier
+			fa += 1
+		else
+			tp += 1
+		end
+	end
+end
+
+print ((tp.to_f / total.to_f * 10000).round / 100.0).to_s + "% ("+ fa.to_s + ")\n"

lib/ccv_dpm.c

@@ -52,7 +52,7 @@ ccv_array_t* ccv_dpm_detect_objects(ccv_dense_matrix_t* a, ccv_dpm_mixture_model
 	double scale = pow(2., 1. / (params.interval + 1.));
 	int next = params.interval + 1;
 	int scale_upto = (int)(log((double)ccv_min(hr, wr)) / log(scale)) - next;
-	if (scale_upto < 1) // image is too small to be interesting
+	if (scale_upto < 0) // image is too small to be interesting
 		return 0;
 	ccv_dense_matrix_t** pyr = (ccv_dense_matrix_t**)alloca((scale_upto + next * 2) * sizeof(ccv_dense_matrix_t*));
 	memset(pyr, 0, (scale_upto + next * 2) * sizeof(ccv_dense_matrix_t*));