From 989ab8c38a02fa7ea9c25108151736c62e81c972 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Fri, 24 Apr 2015 17:27:50 +0000
Subject: [PATCH] IOU loss function
---
src/network.c | 3
src/detection.c | 60 +++++-----
src/utils.h | 4
src/imagenet.c | 2
src/data.c | 20 +-
src/detection_layer.h | 2
src/darknet.c | 1
src/detection_layer.c | 242 ++++++++++++++++++++++++++++++++++++---
8 files changed, 272 insertions(+), 62 deletions(-)
diff --git a/src/darknet.c b/src/darknet.c
index 46a8c82..411efdf 100644
--- a/src/darknet.c
+++ b/src/darknet.c
@@ -93,6 +93,7 @@
int main(int argc, char **argv)
{
+ //test_box();
//test_convolutional_layer();
if(argc < 2){
fprintf(stderr, "usage: %s <function>\n", argv[0]);
diff --git a/src/data.c b/src/data.c
index 2b74386..f1f5b80 100644
--- a/src/data.c
+++ b/src/data.c
@@ -65,22 +65,22 @@
return X;
}
-typedef struct box{
+typedef struct{
int id;
float x,y,w,h;
float left, right, top, bottom;
-} box;
+} box_label;
-box *read_boxes(char *filename, int *n)
+box_label *read_boxes(char *filename, int *n)
{
- box *boxes = calloc(1, sizeof(box));
+ box_label *boxes = calloc(1, sizeof(box_label));
FILE *file = fopen(filename, "r");
if(!file) file_error(filename);
float x, y, h, w;
int id;
int count = 0;
while(fscanf(file, "%d %f %f %f %f", &id, &x, &y, &w, &h) == 5){
- boxes = realloc(boxes, (count+1)*sizeof(box));
+ boxes = realloc(boxes, (count+1)*sizeof(box_label));
boxes[count].id = id;
boxes[count].x = x;
boxes[count].y = y;
@@ -97,11 +97,11 @@
return boxes;
}
-void randomize_boxes(box *b, int n)
+void randomize_boxes(box_label *b, int n)
{
int i;
for(i = 0; i < n; ++i){
- box swap = b[i];
+ box_label swap = b[i];
int index = rand_r(&data_seed)%n;
b[i] = b[index];
b[index] = swap;
@@ -114,7 +114,7 @@
labelpath = find_replace(labelpath, ".jpg", ".txt");
labelpath = find_replace(labelpath, ".JPEG", ".txt");
int count = 0;
- box *boxes = read_boxes(labelpath, &count);
+ box_label *boxes = read_boxes(labelpath, &count);
randomize_boxes(boxes, count);
float x,y,w,h;
float left, top, right, bot;
@@ -174,10 +174,10 @@
if(background) truth[index++] = 0;
truth[index+id] = 1;
index += classes;
- truth[index++] = y;
truth[index++] = x;
- truth[index++] = h;
+ truth[index++] = y;
truth[index++] = w;
+ truth[index++] = h;
}
free(boxes);
}
diff --git a/src/detection.c b/src/detection.c
index c61c799..f61da67 100644
--- a/src/detection.c
+++ b/src/detection.c
@@ -81,9 +81,9 @@
if (imgnet){
plist = get_paths("/home/pjreddie/data/imagenet/det.train.list");
}else{
- //plist = get_paths("/home/pjreddie/data/voc/trainall.txt");
+ plist = get_paths("/home/pjreddie/data/voc/trainall.txt");
//plist = get_paths("/home/pjreddie/data/coco/trainval.txt");
- plist = get_paths("/home/pjreddie/data/voc/all2007-2012.txt");
+ //plist = get_paths("/home/pjreddie/data/voc/all2007-2012.txt");
}
paths = (char **)list_to_array(plist);
pthread_t load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.w, net.h, side, side, background, &buffer);
@@ -95,12 +95,12 @@
train = buffer;
load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.w, net.h, side, side, background, &buffer);
-/*
- image im = float_to_image(net.w, net.h, 3, train.X.vals[114]);
- image copy = copy_image(im);
- draw_detection(copy, train.y.vals[114], 7);
- free_image(copy);
- */
+ /*
+ image im = float_to_image(net.w, net.h, 3, train.X.vals[114]);
+ image copy = copy_image(im);
+ draw_detection(copy, train.y.vals[114], 7);
+ free_image(copy);
+ */
printf("Loaded: %lf seconds\n", sec(clock()-time));
time=clock();
@@ -120,30 +120,30 @@
void predict_detections(network net, data d, float threshold, int offset, int classes, int nuisance, int background, int num_boxes, int per_box)
{
- matrix pred = network_predict_data(net, d);
- int j, k, class;
- for(j = 0; j < pred.rows; ++j){
- for(k = 0; k < pred.cols; k += per_box){
- float scale = 1.;
- int index = k/per_box;
- int row = index / num_boxes;
- int col = index % num_boxes;
- if (nuisance) scale = 1.-pred.vals[j][k];
- for (class = 0; class < classes; ++class){
- int ci = k+classes+background+nuisance;
- float y = (pred.vals[j][ci + 0] + row)/num_boxes;
- float x = (pred.vals[j][ci + 1] + col)/num_boxes;
- float h = pred.vals[j][ci + 2]; //* distance_from_edge(row, num_boxes);
- h = h*h;
- float w = pred.vals[j][ci + 3]; //* distance_from_edge(col, num_boxes);
- w = w*w;
- float prob = scale*pred.vals[j][k+class+background+nuisance];
- if(prob < threshold) continue;
- printf("%d %d %f %f %f %f %f\n", offset + j, class, prob, y, x, h, w);
- }
+ matrix pred = network_predict_data(net, d);
+ int j, k, class;
+ for(j = 0; j < pred.rows; ++j){
+ for(k = 0; k < pred.cols; k += per_box){
+ float scale = 1.;
+ int index = k/per_box;
+ int row = index / num_boxes;
+ int col = index % num_boxes;
+ if (nuisance) scale = 1.-pred.vals[j][k];
+ for (class = 0; class < classes; ++class){
+ int ci = k+classes+background+nuisance;
+ float y = (pred.vals[j][ci + 0] + row)/num_boxes;
+ float x = (pred.vals[j][ci + 1] + col)/num_boxes;
+ float h = pred.vals[j][ci + 2]; //* distance_from_edge(row, num_boxes);
+ h = h*h;
+ float w = pred.vals[j][ci + 3]; //* distance_from_edge(col, num_boxes);
+ w = w*w;
+ float prob = scale*pred.vals[j][k+class+background+nuisance];
+ if(prob < threshold) continue;
+ printf("%d %d %f %f %f %f %f\n", offset + j, class, prob, y, x, h, w);
}
}
- free_matrix(pred);
+ }
+ free_matrix(pred);
}
void validate_detection(char *cfgfile, char *weightfile)
diff --git a/src/detection_layer.c b/src/detection_layer.c
index 73b2862..7eaabb4 100644
--- a/src/detection_layer.c
+++ b/src/detection_layer.c
@@ -3,7 +3,9 @@
#include "softmax_layer.h"
#include "blas.h"
#include "cuda.h"
+#include "utils.h"
#include <stdio.h>
+#include <string.h>
#include <stdlib.h>
int get_detection_layer_locations(detection_layer layer)
@@ -26,6 +28,8 @@
layer->coords = coords;
layer->rescore = rescore;
layer->nuisance = nuisance;
+ layer->cost = calloc(1, sizeof(float));
+ layer->does_cost=1;
layer->background = background;
int outputs = get_detection_layer_output_size(*layer);
layer->output = calloc(batch*outputs, sizeof(float));
@@ -63,6 +67,169 @@
}
}
+typedef struct{
+ float dx, dy, dw, dh;
+} dbox;
+
+dbox derivative(box a, box b)
+{
+ dbox d;
+ d.dx = 0;
+ d.dw = 0;
+ float l1 = a.x - a.w/2;
+ float l2 = b.x - b.w/2;
+ if (l1 > l2){
+ d.dx -= 1;
+ d.dw += .5;
+ }
+ float r1 = a.x + a.w/2;
+ float r2 = b.x + b.w/2;
+ if(r1 < r2){
+ d.dx += 1;
+ d.dw += .5;
+ }
+ if (l1 > r2) {
+ d.dx = -1;
+ d.dw = 0;
+ }
+ if (r1 < l2){
+ d.dx = 1;
+ d.dw = 0;
+ }
+
+ d.dy = 0;
+ d.dh = 0;
+ float t1 = a.y - a.h/2;
+ float t2 = b.y - b.h/2;
+ if (t1 > t2){
+ d.dy -= 1;
+ d.dh += .5;
+ }
+ float b1 = a.y + a.h/2;
+ float b2 = b.y + b.h/2;
+ if(b1 < b2){
+ d.dy += 1;
+ d.dh += .5;
+ }
+ if (t1 > b2) {
+ d.dy = -1;
+ d.dh = 0;
+ }
+ if (b1 < t2){
+ d.dy = 1;
+ d.dh = 0;
+ }
+ return d;
+}
+
+float overlap(float x1, float w1, float x2, float w2)
+{
+ float l1 = x1 - w1/2;
+ float l2 = x2 - w2/2;
+ float left = l1 > l2 ? l1 : l2;
+ float r1 = x1 + w1/2;
+ float r2 = x2 + w2/2;
+ float right = r1 < r2 ? r1 : r2;
+ return right - left;
+}
+
+float box_intersection(box a, box b)
+{
+ float w = overlap(a.x, a.w, b.x, b.w);
+ float h = overlap(a.y, a.h, b.y, b.h);
+ if(w < 0 || h < 0) return 0;
+ float area = w*h;
+ return area;
+}
+
+float box_union(box a, box b)
+{
+ float i = box_intersection(a, b);
+ float u = a.w*a.h + b.w*b.h - i;
+ return u;
+}
+
+float box_iou(box a, box b)
+{
+ return box_intersection(a, b)/box_union(a, b);
+}
+
+dbox dintersect(box a, box b)
+{
+ float w = overlap(a.x, a.w, b.x, b.w);
+ float h = overlap(a.y, a.h, b.y, b.h);
+ dbox dover = derivative(a, b);
+ dbox di;
+
+ di.dw = dover.dw*h;
+ di.dx = dover.dx*h;
+ di.dh = dover.dh*w;
+ di.dy = dover.dy*w;
+ if(h < 0 || w < 0){
+ di.dx = dover.dx;
+ di.dy = dover.dy;
+ }
+ return di;
+}
+
+dbox dunion(box a, box b)
+{
+ dbox du = {0,0,0,0};;
+ float w = overlap(a.x, a.w, b.x, b.w);
+ float h = overlap(a.y, a.h, b.y, b.h);
+ if(w > 0 && h > 0){
+ dbox di = dintersect(a, b);
+ du.dw = h - di.dw;
+ du.dh = w - di.dw;
+ du.dx = -di.dx;
+ du.dy = -di.dy;
+ }
+ return du;
+}
+
+dbox diou(box a, box b)
+{
+ float u = box_union(a,b);
+ float i = box_intersection(a,b);
+ dbox di = dintersect(a,b);
+ dbox du = dunion(a,b);
+ dbox dd = {0,0,0,0};
+ if(i < 0) {
+ dd.dx = b.x - a.x;
+ dd.dy = b.y - a.y;
+ dd.dw = b.w - a.w;
+ dd.dh = b.h - a.h;
+ return dd;
+ }
+ dd.dx = 2*pow((1-(i/u)),1)*(di.dx*u - du.dx*i)/(u*u);
+ dd.dy = 2*pow((1-(i/u)),1)*(di.dy*u - du.dy*i)/(u*u);
+ dd.dw = 2*pow((1-(i/u)),1)*(di.dw*u - du.dw*i)/(u*u);
+ dd.dh = 2*pow((1-(i/u)),1)*(di.dh*u - du.dh*i)/(u*u);
+ return dd;
+}
+
+void test_box()
+{
+ box a = {1, 1, 1, 1};
+ box b = {0, 0, .5, .2};
+ int count = 0;
+ while(count++ < 300){
+ dbox d = diou(a, b);
+ printf("%f %f %f %f\n", a.x, a.y, a.w, a.h);
+ a.x += .1*d.dx;
+ a.w += .1*d.dw;
+ a.y += .1*d.dy;
+ a.h += .1*d.dh;
+ printf("inter: %f\n", box_intersection(a, b));
+ printf("union: %f\n", box_union(a, b));
+ printf("IOU: %f\n", box_iou(a, b));
+ if(d.dx==0 && d.dw==0 && d.dy==0 && d.dh==0) {
+ printf("break!!!\n");
+ break;
+ }
+ }
+}
+
void forward_detection_layer(const detection_layer layer, network_state state)
{
int in_i = 0;
@@ -92,31 +259,63 @@
layer.output[out_i++] = mask*state.input[in_i++];
}
}
- /*
- int count = 0;
- for(i = 0; i < layer.batch*locations; ++i){
- for(j = 0; j < layer.classes+layer.background; ++j){
- printf("%f, ", layer.output[count++]);
- }
- printf("\n");
- for(j = 0; j < layer.coords; ++j){
- printf("%f, ", layer.output[count++]);
- }
- printf("\n");
- }
- */
- /*
- if(layer.background || 1){
+ if(layer.does_cost){
+ *(layer.cost) = 0;
+ int size = get_detection_layer_output_size(layer) * layer.batch;
+ memset(layer.delta, 0, size * sizeof(float));
for(i = 0; i < layer.batch*locations; ++i){
- int index = i*(layer.classes+layer.coords+layer.background);
- for(j= 0; j < layer.classes; ++j){
- if(state.truth[index+j+layer.background]){
- //dark_zone(layer, j, index, state);
- }
+ int classes = layer.nuisance+layer.classes;
+ int offset = i*(classes+layer.coords);
+ for(j = offset; j < offset+classes; ++j){
+ *(layer.cost) += pow(state.truth[j] - layer.output[j], 2);
+ layer.delta[j] = state.truth[j] - layer.output[j];
}
+ box truth;
+ truth.x = state.truth[j+0];
+ truth.y = state.truth[j+1];
+ truth.w = state.truth[j+2];
+ truth.h = state.truth[j+3];
+ box out;
+ out.x = layer.output[j+0];
+ out.y = layer.output[j+1];
+ out.w = layer.output[j+2];
+ out.h = layer.output[j+3];
+ if(!(truth.w*truth.h)) continue;
+ float iou = box_iou(truth, out);
+ //printf("iou: %f\n", iou);
+ *(layer.cost) += pow((1-iou), 2);
+ dbox d = diou(out, truth);
+ layer.delta[j+0] = d.dx;
+ layer.delta[j+1] = d.dy;
+ layer.delta[j+2] = d.dw;
+ layer.delta[j+3] = d.dh;
}
}
- */
+ /*
+ int count = 0;
+ for(i = 0; i < layer.batch*locations; ++i){
+ for(j = 0; j < layer.classes+layer.background; ++j){
+ printf("%f, ", layer.output[count++]);
+ }
+ printf("\n");
+ for(j = 0; j < layer.coords; ++j){
+ printf("%f, ", layer.output[count++]);
+ }
+ printf("\n");
+ }
+ */
+ /*
+ if(layer.background || 1){
+ for(i = 0; i < layer.batch*locations; ++i){
+ int index = i*(layer.classes+layer.coords+layer.background);
+ for(j= 0; j < layer.classes; ++j){
+ if(state.truth[index+j+layer.background]){
+//dark_zone(layer, j, index, state);
+}
+}
+}
+}
+ */
}
void backward_detection_layer(const detection_layer layer, network_state state)
@@ -164,6 +363,7 @@
cpu_state.input = in_cpu;
forward_detection_layer(layer, cpu_state);
cuda_push_array(layer.output_gpu, layer.output, layer.batch*outputs);
+ cuda_push_array(layer.delta_gpu, layer.delta, layer.batch*outputs);
free(cpu_state.input);
if(cpu_state.truth) free(cpu_state.truth);
}
diff --git a/src/detection_layer.h b/src/detection_layer.h
index a56cb25..0aa5f66 100644
--- a/src/detection_layer.h
+++ b/src/detection_layer.h
@@ -11,6 +11,8 @@
int background;
int rescore;
int nuisance;
+ int does_cost;
+ float *cost;
float *output;
float *delta;
#ifdef GPU
diff --git a/src/imagenet.c b/src/imagenet.c
index 906dbd4..3f88b36 100644
--- a/src/imagenet.c
+++ b/src/imagenet.c
@@ -47,7 +47,7 @@
printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), net.seen);
free_data(train);
//if(i%100 == 0 && net.learning_rate > .00001) net.learning_rate *= .97;
- if(i%100==0){
+ if(i%1000==0){
char buff[256];
sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i);
save_weights(net, buff);
diff --git a/src/network.c b/src/network.c
index 5571076..3247a31 100644
--- a/src/network.c
+++ b/src/network.c
@@ -186,6 +186,9 @@
if(net.types[net.n-1] == COST){
return ((cost_layer *)net.layers[net.n-1])->output[0];
}
+ if(net.types[net.n-1] == DETECTION){
+ return ((detection_layer *)net.layers[net.n-1])->cost[0];
+ }
return 0;
}
diff --git a/src/utils.h b/src/utils.h
index 578abc3..0db16de 100644
--- a/src/utils.h
+++ b/src/utils.h
@@ -36,5 +36,9 @@
float mag_array(float *a, int n);
float **one_hot_encode(float *a, int n, int k);
float sec(clock_t clocks);
+
+typedef struct{
+ float x, y, w, h;
+} box;
#endif
--
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