From 0948df52b850b908e7a74cb589d19fa29eb30368 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Tue, 08 May 2018 14:27:45 +0000
Subject: [PATCH] Merge pull request #741 from IlyaOvodov/Fix_detector_output
---
src/image.c | 105 +++++++++++++++++++++++++++--------
src/box.h | 11 +++
src/convolutional_layer.c | 2
src/detector.c | 10 ++-
src/darknet.c | 5 +
src/image.h | 2
6 files changed, 104 insertions(+), 31 deletions(-)
diff --git a/src/box.h b/src/box.h
index 0aa0c59..9553b12 100644
--- a/src/box.h
+++ b/src/box.h
@@ -37,6 +37,13 @@
int sort_class;
} detection;
+typedef struct detection_with_class {
+ detection det;
+ // The most probable class id: the best class index in this->prob.
+ // Is filled temporary when processing results, otherwise not initialized
+ int best_class;
+} detection_with_class;
+
box float_to_box(float *f);
float box_iou(box a, box b);
float box_rmse(box a, box b);
@@ -48,4 +55,8 @@
box decode_box(box b, box anchor);
box encode_box(box b, box anchor);
+// Creates array of detections with prob > thresh and fills best_class for them
+// Return number of selected detections in *selected_detections_num
+detection_with_class* get_actual_detections(detection *dets, int dets_num, float thresh, int* selected_detections_num);
+
#endif
diff --git a/src/convolutional_layer.c b/src/convolutional_layer.c
index 9a76bdf..b8065fd 100644
--- a/src/convolutional_layer.c
+++ b/src/convolutional_layer.c
@@ -491,7 +491,7 @@
size_t total_byte;
check_error(cudaMemGetInfo(&free_byte, &total_byte));
if (l->workspace_size > free_byte || l->workspace_size >= total_byte / 2) {
- printf(" used slow CUDNN algo without Workspace! \n");
+ printf(" used slow CUDNN algo without Workspace! Need memory: %d, available: %d\n", l->workspace_size, (free_byte < total_byte/2) ? free_byte : total_byte/2);
cudnn_convolutional_setup(l, cudnn_smallest);
l->workspace_size = get_workspace_size(*l);
}
diff --git a/src/darknet.c b/src/darknet.c
index 74ac16a..5407269 100644
--- a/src/darknet.c
+++ b/src/darknet.c
@@ -18,7 +18,7 @@
#endif
extern void predict_classifier(char *datacfg, char *cfgfile, char *weightfile, char *filename, int top);
-extern void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh);
+extern void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, int ext_output);
extern void run_voxel(int argc, char **argv);
extern void run_yolo(int argc, char **argv);
extern void run_detector(int argc, char **argv);
@@ -391,8 +391,9 @@
run_detector(argc, argv);
} else if (0 == strcmp(argv[1], "detect")){
float thresh = find_float_arg(argc, argv, "-thresh", .24);
+ int ext_output = find_arg(argc, argv, "-ext_output");
char *filename = (argc > 4) ? argv[4]: 0;
- test_detector("cfg/coco.data", argv[2], argv[3], filename, thresh);
+ test_detector("cfg/coco.data", argv[2], argv[3], filename, thresh, ext_output);
} else if (0 == strcmp(argv[1], "cifar")){
run_cifar(argc, argv);
} else if (0 == strcmp(argv[1], "go")){
diff --git a/src/detector.c b/src/detector.c
index e891cd7..71ede10 100644
--- a/src/detector.c
+++ b/src/detector.c
@@ -1041,7 +1041,8 @@
}
#endif // OPENCV
-void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, float hier_thresh, int dont_show)
+void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh,
+ float hier_thresh, int dont_show, int ext_output)
{
list *options = read_data_cfg(datacfg);
char *name_list = option_find_str(options, "names", "data/names.list");
@@ -1093,7 +1094,7 @@
int nboxes = 0;
detection *dets = get_network_boxes(&net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes, letterbox);
if (nms) do_nms_sort(dets, nboxes, l.classes, nms);
- draw_detections_v3(im, dets, nboxes, thresh, names, alphabet, l.classes);
+ draw_detections_v3(im, dets, nboxes, thresh, names, alphabet, l.classes, ext_output);
free_detections(dets, nboxes);
save_image(im, "predictions");
if (!dont_show) {
@@ -1145,6 +1146,9 @@
int num_of_clusters = find_int_arg(argc, argv, "-num_of_clusters", 5);
int width = find_int_arg(argc, argv, "-width", -1);
int height = find_int_arg(argc, argv, "-height", -1);
+ // extended output in test mode (output of rect bound coords)
+ // and for recall mode (extended output table-like format with results for best_class fit)
+ int ext_output = find_arg(argc, argv, "-ext_output");
if(argc < 4){
fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
return;
@@ -1181,7 +1185,7 @@
if(strlen(weights) > 0)
if (weights[strlen(weights) - 1] == 0x0d) weights[strlen(weights) - 1] = 0;
char *filename = (argc > 6) ? argv[6]: 0;
- if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, dont_show);
+ if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, dont_show, ext_output);
else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show);
else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights, outfile);
else if(0==strcmp(argv[2], "recall")) validate_detector_recall(datacfg, cfg, weights);
diff --git a/src/image.c b/src/image.c
index 499306b..467b95c 100644
--- a/src/image.c
+++ b/src/image.c
@@ -230,27 +230,76 @@
return alphabets;
}
-void draw_detections_v3(image im, detection *dets, int num, float thresh, char **names, image **alphabet, int classes)
-{
- int i, j;
- for (i = 0; i < num; ++i) {
- char labelstr[4096] = { 0 };
- int class_id = -1;
- for (j = 0; j < classes; ++j) {
- if (dets[i].prob[j] > thresh) {
- if (class_id < 0) {
- strcat(labelstr, names[j]);
- class_id = j;
- }
- else {
- strcat(labelstr, ", ");
- strcat(labelstr, names[j]);
- }
- printf("%s: %.0f%%\n", names[j], dets[i].prob[j] * 100);
+
+// Creates array of detections with prob > thresh and fills best_class for them
+detection_with_class* get_actual_detections(detection *dets, int dets_num, float thresh, int* selected_detections_num)
+{
+ int selected_num = 0;
+ detection_with_class* result_arr = calloc(dets_num, sizeof(detection_with_class));
+ for (int i = 0; i < dets_num; ++i) {
+ int best_class = -1;
+ float best_class_prob = thresh;
+ for (int j = 0; j < dets[i].classes; ++j) {
+ if (dets[i].prob[j] > best_class_prob ) {
+ best_class = j;
+ best_class_prob = dets[i].prob[j];
}
}
- if (class_id >= 0) {
+ if (best_class >= 0) {
+ result_arr[selected_num].det = dets[i];
+ result_arr[selected_num].best_class = best_class;
+ ++selected_num;
+ }
+ }
+ if (selected_detections_num)
+ *selected_detections_num = selected_num;
+ return result_arr;
+}
+
+// compare to sort detection** by bbox.x
+int compare_by_lefts(const void *a_ptr, const void *b_ptr) {
+ const detection_with_class* a = (detection_with_class*)a_ptr;
+ const detection_with_class* b = (detection_with_class*)b_ptr;
+ const float delta = (a->det.bbox.x - a->det.bbox.w/2) - (b->det.bbox.x - b->det.bbox.w/2);
+ return delta < 0 ? -1 : delta > 0 ? 1 : 0;
+}
+
+// compare to sort detection** by best_class probability
+int compare_by_probs(const void *a_ptr, const void *b_ptr) {
+ const detection_with_class* a = (detection_with_class*)a_ptr;
+ const detection_with_class* b = (detection_with_class*)b_ptr;
+ float delta = a->det.prob[a->best_class] - b->det.prob[b->best_class];
+ return delta < 0 ? -1 : delta > 0 ? 1 : 0;
+}
+
+void draw_detections_v3(image im, detection *dets, int num, float thresh, char **names, image **alphabet, int classes, int ext_output)
+{
+ int selected_detections_num;
+ detection_with_class* selected_detections = get_actual_detections(dets, num, thresh, &selected_detections_num);
+
+ // text output
+ qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_lefts);
+ for (int i = 0; i < selected_detections_num; ++i) {
+ const int best_class = selected_detections[i].best_class;
+ printf("%s: %.0f%%", names[best_class], selected_detections[i].det.prob[best_class] * 100);
+ if (ext_output)
+ printf("\t(left: %.0f\ttop: %.0f\tw: %0.f\th: %0.f)\n",
+ (selected_detections[i].det.bbox.x - selected_detections[i].det.bbox.w / 2)*im.w,
+ (selected_detections[i].det.bbox.y - selected_detections[i].det.bbox.h / 2)*im.h,
+ selected_detections[i].det.bbox.w*im.w, selected_detections[i].det.bbox.h*im.h);
+ else
+ printf("\n");
+ for (int j = 0; j < classes; ++j) {
+ if (selected_detections[i].det.prob[j] > thresh && j != best_class) {
+ printf("%s: %.0f%%\n", names[j], selected_detections[i].det.prob[j] * 100);
+ }
+ }
+ }
+
+ // image output
+ qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_probs);
+ for (int i = 0; i < selected_detections_num; ++i) {
int width = im.h * .006;
if (width < 1)
width = 1;
@@ -262,8 +311,8 @@
}
*/
- //printf("%d %s: %.0f%%\n", i, names[class_id], prob*100);
- int offset = class_id * 123457 % classes;
+ //printf("%d %s: %.0f%%\n", i, names[selected_detections[i].best_class], prob*100);
+ int offset = selected_detections[i].best_class * 123457 % classes;
float red = get_color(2, offset, classes);
float green = get_color(1, offset, classes);
float blue = get_color(0, offset, classes);
@@ -274,7 +323,7 @@
rgb[0] = red;
rgb[1] = green;
rgb[2] = blue;
- box b = dets[i].bbox;
+ box b = selected_detections[i].det.bbox;
//printf("%f %f %f %f\n", b.x, b.y, b.w, b.h);
int left = (b.x - b.w / 2.)*im.w;
@@ -295,12 +344,20 @@
draw_box_width(im, left, top, right, bot, width, red, green, blue);
if (alphabet) {
+ char labelstr[4096] = { 0 };
+ strcat(labelstr, names[selected_detections[i].best_class]);
+ for (int j = 0; j < classes; ++j) {
+ if (selected_detections[i].det.prob[j] > thresh && j != selected_detections[i].best_class) {
+ strcat(labelstr, ", ");
+ strcat(labelstr, names[j]);
+ }
+ }
image label = get_label_v3(alphabet, labelstr, (im.h*.03));
draw_label(im, top + width, left, label, rgb);
free_image(label);
}
- if (dets[i].mask) {
- image mask = float_to_image(14, 14, 1, dets[i].mask);
+ if (selected_detections[i].det.mask) {
+ image mask = float_to_image(14, 14, 1, selected_detections[i].det.mask);
image resized_mask = resize_image(mask, b.w*im.w, b.h*im.h);
image tmask = threshold_image(resized_mask, .5);
embed_image(tmask, im, left, top);
@@ -308,8 +365,8 @@
free_image(resized_mask);
free_image(tmask);
}
- }
}
+ free(selected_detections);
}
void draw_detections(image im, int num, float thresh, box *boxes, float **probs, char **names, image **alphabet, int classes)
diff --git a/src/image.h b/src/image.h
index ebf28e8..d047f62 100644
--- a/src/image.h
+++ b/src/image.h
@@ -23,7 +23,7 @@
void draw_label(image a, int r, int c, image label, const float *rgb);
void write_label(image a, int r, int c, image *characters, char *string, float *rgb);
void draw_detections(image im, int num, float thresh, box *boxes, float **probs, char **names, image **labels, int classes);
-void draw_detections_v3(image im, detection *dets, int num, float thresh, char **names, image **alphabet, int classes);
+void draw_detections_v3(image im, detection *dets, int num, float thresh, char **names, image **alphabet, int classes, int ext_output);
image image_distance(image a, image b);
void scale_image(image m, float s);
image crop_image(image im, int dx, int dy, int w, int h);
--
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