From a9e16d914a5e1247c4149d95afbe8f68ca846a53 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 23 Sep 2015 00:34:48 +0000
Subject: [PATCH] more writing stuff
---
src/detection_layer.c | 341 ++++++--------------------------------------------------
1 files changed, 41 insertions(+), 300 deletions(-)
diff --git a/src/detection_layer.c b/src/detection_layer.c
index af137c6..daeee04 100644
--- a/src/detection_layer.c
+++ b/src/detection_layer.c
@@ -2,6 +2,7 @@
#include "activations.h"
#include "softmax_layer.h"
#include "blas.h"
+#include "box.h"
#include "cuda.h"
#include "utils.h"
#include <stdio.h>
@@ -10,15 +11,15 @@
int get_detection_layer_locations(detection_layer l)
{
- return l.inputs / (l.classes+l.coords+l.rescore+l.background);
+ return l.inputs / (l.classes+l.coords+l.joint+(l.background || l.objectness));
}
int get_detection_layer_output_size(detection_layer l)
{
- return get_detection_layer_locations(l)*(l.background + l.classes + l.coords);
+ return get_detection_layer_locations(l)*((l.background || l.objectness) + l.classes + l.coords);
}
-detection_layer make_detection_layer(int batch, int inputs, int classes, int coords, int rescore, int background, int nuisance)
+detection_layer make_detection_layer(int batch, int inputs, int classes, int coords, int joint, int rescore, int background, int objectness)
{
detection_layer l = {0};
l.type = DETECTION;
@@ -28,17 +29,18 @@
l.classes = classes;
l.coords = coords;
l.rescore = rescore;
- l.nuisance = nuisance;
+ l.objectness = objectness;
+ l.background = background;
+ l.joint = joint;
l.cost = calloc(1, sizeof(float));
l.does_cost=1;
- l.background = background;
int outputs = get_detection_layer_output_size(l);
l.outputs = outputs;
l.output = calloc(batch*outputs, sizeof(float));
l.delta = calloc(batch*outputs, sizeof(float));
#ifdef GPU
- l.output_gpu = cuda_make_array(0, batch*outputs);
- l.delta_gpu = cuda_make_array(0, batch*outputs);
+ l.output_gpu = cuda_make_array(l.output, batch*outputs);
+ l.delta_gpu = cuda_make_array(l.delta, batch*outputs);
#endif
fprintf(stderr, "Detection Layer\n");
@@ -47,260 +49,6 @@
return l;
}
-void dark_zone(detection_layer l, int class, int start, network_state state)
-{
- int index = start+l.background+class;
- int size = l.classes+l.coords+l.background;
- int location = (index%(7*7*size)) / size ;
- int r = location / 7;
- int c = location % 7;
- int dr, dc;
- for(dr = -1; dr <= 1; ++dr){
- for(dc = -1; dc <= 1; ++dc){
- if(!(dr || dc)) continue;
- if((r + dr) > 6 || (r + dr) < 0) continue;
- if((c + dc) > 6 || (c + dc) < 0) continue;
- int di = (dr*7 + dc) * size;
- if(state.truth[index+di]) continue;
- l.output[index + di] = 0;
- //if(!state.truth[start+di]) continue;
- //l.output[start + di] = 1;
- }
- }
-}
-
-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;
-
- return di;
-}
-
-dbox dunion(box a, box b)
-{
- dbox du;
-
- dbox di = dintersect(a, b);
- du.dw = a.h - di.dw;
- du.dh = a.w - di.dh;
- du.dx = -di.dx;
- du.dy = -di.dy;
-
- return du;
-}
-
-dbox diou(box a, box b);
-
-void test_dunion()
-{
- box a = {0, 0, 1, 1};
- box dxa= {0+.0001, 0, 1, 1};
- box dya= {0, 0+.0001, 1, 1};
- box dwa= {0, 0, 1+.0001, 1};
- box dha= {0, 0, 1, 1+.0001};
-
- box b = {.5, .5, .2, .2};
- dbox di = dunion(a,b);
- printf("Union: %f %f %f %f\n", di.dx, di.dy, di.dw, di.dh);
- float inter = box_union(a, b);
- float xinter = box_union(dxa, b);
- float yinter = box_union(dya, b);
- float winter = box_union(dwa, b);
- float hinter = box_union(dha, b);
- xinter = (xinter - inter)/(.0001);
- yinter = (yinter - inter)/(.0001);
- winter = (winter - inter)/(.0001);
- hinter = (hinter - inter)/(.0001);
- printf("Union Manual %f %f %f %f\n", xinter, yinter, winter, hinter);
-}
-void test_dintersect()
-{
- box a = {0, 0, 1, 1};
- box dxa= {0+.0001, 0, 1, 1};
- box dya= {0, 0+.0001, 1, 1};
- box dwa= {0, 0, 1+.0001, 1};
- box dha= {0, 0, 1, 1+.0001};
-
- box b = {.5, .5, .2, .2};
- dbox di = dintersect(a,b);
- printf("Inter: %f %f %f %f\n", di.dx, di.dy, di.dw, di.dh);
- float inter = box_intersection(a, b);
- float xinter = box_intersection(dxa, b);
- float yinter = box_intersection(dya, b);
- float winter = box_intersection(dwa, b);
- float hinter = box_intersection(dha, b);
- xinter = (xinter - inter)/(.0001);
- yinter = (yinter - inter)/(.0001);
- winter = (winter - inter)/(.0001);
- hinter = (hinter - inter)/(.0001);
- printf("Inter Manual %f %f %f %f\n", xinter, yinter, winter, hinter);
-}
-
-void test_box()
-{
- test_dintersect();
- test_dunion();
- box a = {0, 0, 1, 1};
- box dxa= {0+.00001, 0, 1, 1};
- box dya= {0, 0+.00001, 1, 1};
- box dwa= {0, 0, 1+.00001, 1};
- box dha= {0, 0, 1, 1+.00001};
-
- box b = {.5, 0, .2, .2};
-
- float iou = box_iou(a,b);
- iou = (1-iou)*(1-iou);
- printf("%f\n", iou);
- dbox d = diou(a, b);
- printf("%f %f %f %f\n", d.dx, d.dy, d.dw, d.dh);
-
- float xiou = box_iou(dxa, b);
- float yiou = box_iou(dya, b);
- float wiou = box_iou(dwa, b);
- float hiou = box_iou(dha, b);
- xiou = ((1-xiou)*(1-xiou) - iou)/(.00001);
- yiou = ((1-yiou)*(1-yiou) - iou)/(.00001);
- wiou = ((1-wiou)*(1-wiou) - iou)/(.00001);
- hiou = ((1-hiou)*(1-hiou) - iou)/(.00001);
- printf("manual %f %f %f %f\n", xiou, yiou, wiou, hiou);
- /*
-
- 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;
- }
- }
- */
-}
-
-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 || 1) {
- 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 forward_detection_layer(const detection_layer l, network_state state)
{
int in_i = 0;
@@ -308,10 +56,10 @@
int locations = get_detection_layer_locations(l);
int i,j;
for(i = 0; i < l.batch*locations; ++i){
- int mask = (!state.truth || state.truth[out_i + l.background + l.classes + 2]);
+ int mask = (!state.truth || state.truth[out_i + (l.background || l.objectness) + l.classes + 2]);
float scale = 1;
- if(l.rescore) scale = state.input[in_i++];
- else if(l.nuisance){
+ if(l.joint) scale = state.input[in_i++];
+ else if(l.objectness){
l.output[out_i++] = 1-state.input[in_i++];
scale = mask;
}
@@ -320,7 +68,7 @@
for(j = 0; j < l.classes; ++j){
l.output[out_i++] = scale*state.input[in_i++];
}
- if(l.nuisance){
+ if(l.objectness){
}else if(l.background){
softmax_array(l.output + out_i - l.classes-l.background, l.classes+l.background, l.output + out_i - l.classes-l.background);
@@ -337,11 +85,12 @@
int size = get_detection_layer_output_size(l) * l.batch;
memset(l.delta, 0, size * sizeof(float));
for (i = 0; i < l.batch*locations; ++i) {
- int classes = l.nuisance+l.classes;
+ int classes = (l.objectness || l.background)+l.classes;
int offset = i*(classes+l.coords);
for (j = offset; j < offset+classes; ++j) {
*(l.cost) += pow(state.truth[j] - l.output[j], 2);
l.delta[j] = state.truth[j] - l.output[j];
+ if(l.background && j == offset) l.delta[j] *= .1;
}
box truth;
@@ -349,6 +98,7 @@
truth.y = state.truth[j+1]/7;
truth.w = pow(state.truth[j+2], 2);
truth.h = pow(state.truth[j+3], 2);
+
box out;
out.x = l.output[j+0]/7;
out.y = l.output[j+1]/7;
@@ -359,35 +109,24 @@
float iou = box_iou(out, truth);
avg_iou += iou;
++count;
- dbox delta = diou(out, truth);
-
- l.delta[j+0] = 10 * delta.dx/7;
- l.delta[j+1] = 10 * delta.dy/7;
- l.delta[j+2] = 10 * delta.dw * 2 * sqrt(out.w);
- l.delta[j+3] = 10 * delta.dh * 2 * sqrt(out.h);
-
*(l.cost) += pow((1-iou), 2);
- if(0){
- l.delta[j+0] = (state.truth[j+0] - l.output[j+0]);
- l.delta[j+1] = (state.truth[j+1] - l.output[j+1]);
- l.delta[j+2] = (state.truth[j+2] - l.output[j+2]);
- l.delta[j+3] = (state.truth[j+3] - l.output[j+3]);
- }else{
- l.delta[j+0] = 4 * (state.truth[j+0] - l.output[j+0]) / 7;
- l.delta[j+1] = 4 * (state.truth[j+1] - l.output[j+1]) / 7;
- l.delta[j+2] = 4 * (state.truth[j+2] - l.output[j+2]);
- l.delta[j+3] = 4 * (state.truth[j+3] - l.output[j+3]);
- }
- if(0){
- for (j = offset; j < offset+classes; ++j) {
- if(state.truth[j]) state.truth[j] = iou;
- l.delta[j] = state.truth[j] - l.output[j];
+ l.delta[j+0] = 4 * (state.truth[j+0] - l.output[j+0]);
+ l.delta[j+1] = 4 * (state.truth[j+1] - l.output[j+1]);
+ l.delta[j+2] = 4 * (state.truth[j+2] - l.output[j+2]);
+ l.delta[j+3] = 4 * (state.truth[j+3] - l.output[j+3]);
+ if(l.rescore){
+ if(l.objectness){
+ state.truth[offset] = iou;
+ l.delta[offset] = state.truth[offset] - l.output[offset];
+ }
+ else{
+ for (j = offset; j < offset+classes; ++j) {
+ if(state.truth[j]) state.truth[j] = iou;
+ l.delta[j] = state.truth[j] - l.output[j];
+ }
}
}
-
- /*
- */
}
printf("Avg IOU: %f\n", avg_iou/count);
}
@@ -402,21 +141,21 @@
for(i = 0; i < l.batch*locations; ++i){
float scale = 1;
float latent_delta = 0;
- if(l.rescore) scale = state.input[in_i++];
- else if (l.nuisance) state.delta[in_i++] = -l.delta[out_i++];
- else if (l.background) state.delta[in_i++] = scale*l.delta[out_i++];
+ if(l.joint) scale = state.input[in_i++];
+ else if (l.objectness) state.delta[in_i++] += -l.delta[out_i++];
+ else if (l.background) state.delta[in_i++] += scale*l.delta[out_i++];
for(j = 0; j < l.classes; ++j){
latent_delta += state.input[in_i]*l.delta[out_i];
- state.delta[in_i++] = scale*l.delta[out_i++];
+ state.delta[in_i++] += scale*l.delta[out_i++];
}
- if (l.nuisance) {
+ if (l.objectness) {
}else if (l.background) gradient_array(l.output + out_i, l.coords, LOGISTIC, l.delta + out_i);
- for(j = 0; j < l.coords; ++j){
- state.delta[in_i++] = l.delta[out_i++];
+ for (j = 0; j < l.coords; ++j){
+ state.delta[in_i++] += l.delta[out_i++];
}
- if(l.rescore) state.delta[in_i-l.coords-l.classes-l.rescore-l.background] = latent_delta;
+ if(l.joint) state.delta[in_i-l.coords-l.classes-l.joint] += latent_delta;
}
}
@@ -460,11 +199,13 @@
cpu_state.truth = truth_cpu;
cpu_state.delta = delta_cpu;
- cuda_pull_array(state.input, in_cpu, l.batch*l.inputs);
+ cuda_pull_array(state.input, in_cpu, l.batch*l.inputs);
+ cuda_pull_array(state.delta, delta_cpu, l.batch*l.inputs);
cuda_pull_array(l.delta_gpu, l.delta, l.batch*outputs);
backward_detection_layer(l, cpu_state);
cuda_push_array(state.delta, delta_cpu, l.batch*l.inputs);
+ if (truth_cpu) free(truth_cpu);
free(in_cpu);
free(delta_cpu);
}
--
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