From d97331b88ff3d50035b1e22c9d0eb671b61227e3 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 15 Apr 2015 07:32:32 +0000
Subject: [PATCH] level adjustment for images
---
src/detection_layer.c | 114 +++++++++++++++++++++++++++++++++++++--------------------
1 files changed, 74 insertions(+), 40 deletions(-)
diff --git a/src/detection_layer.c b/src/detection_layer.c
index 5ca7fa2..73b2862 100644
--- a/src/detection_layer.c
+++ b/src/detection_layer.c
@@ -8,23 +8,25 @@
int get_detection_layer_locations(detection_layer layer)
{
- return layer.inputs / (layer.classes+layer.coords+layer.rescore);
+ return layer.inputs / (layer.classes+layer.coords+layer.rescore+layer.background);
}
int get_detection_layer_output_size(detection_layer layer)
{
- return get_detection_layer_locations(layer)*(layer.classes+layer.coords);
+ return get_detection_layer_locations(layer)*(layer.background + layer.classes + layer.coords);
}
-detection_layer *make_detection_layer(int batch, int inputs, int classes, int coords, int rescore)
+detection_layer *make_detection_layer(int batch, int inputs, int classes, int coords, int rescore, int background, int nuisance)
{
detection_layer *layer = calloc(1, sizeof(detection_layer));
-
+
layer->batch = batch;
layer->inputs = inputs;
layer->classes = classes;
layer->coords = coords;
layer->rescore = rescore;
+ layer->nuisance = nuisance;
+ layer->background = background;
int outputs = get_detection_layer_output_size(*layer);
layer->output = calloc(batch*outputs, sizeof(float));
layer->delta = calloc(batch*outputs, sizeof(float));
@@ -39,38 +41,13 @@
return layer;
}
-
-void forward_detection_layer(const detection_layer layer, network_state state)
+void dark_zone(detection_layer layer, int class, int start, network_state state)
{
- int in_i = 0;
- int out_i = 0;
- int locations = get_detection_layer_locations(layer);
- int i,j;
- for(i = 0; i < layer.batch*locations; ++i){
- int mask = (!state.truth || state.truth[out_i + layer.classes + 2]);
- float scale = 1;
- if(layer.rescore) scale = state.input[in_i++];
- for(j = 0; j < layer.classes; ++j){
- layer.output[out_i++] = scale*state.input[in_i++];
- }
- if(!layer.rescore){
- softmax_array(layer.output + out_i - layer.classes, layer.classes, layer.output + out_i - layer.classes);
- activate_array(state.input+in_i, layer.coords, LOGISTIC);
- }
- for(j = 0; j < layer.coords; ++j){
- layer.output[out_i++] = mask*state.input[in_i++];
- }
- }
-}
-
-void dark_zone(detection_layer layer, int index, network_state state)
-{
- int size = layer.classes+layer.rescore+layer.coords;
+ int index = start+layer.background+class;
+ int size = layer.classes+layer.coords+layer.background;
int location = (index%(7*7*size)) / size ;
int r = location / 7;
int c = location % 7;
- int class = index%size;
- if(layer.rescore) --class;
int dr, dc;
for(dr = -1; dr <= 1; ++dr){
for(dc = -1; dc <= 1; ++dc){
@@ -79,11 +56,69 @@
if((c + dc) > 6 || (c + dc) < 0) continue;
int di = (dr*7 + dc) * size;
if(state.truth[index+di]) continue;
- layer.delta[index + di] = 0;
+ layer.output[index + di] = 0;
+ //if(!state.truth[start+di]) continue;
+ //layer.output[start + di] = 1;
}
}
}
+void forward_detection_layer(const detection_layer layer, network_state state)
+{
+ int in_i = 0;
+ int out_i = 0;
+ int locations = get_detection_layer_locations(layer);
+ int i,j;
+ for(i = 0; i < layer.batch*locations; ++i){
+ int mask = (!state.truth || state.truth[out_i + layer.background + layer.classes + 2]);
+ float scale = 1;
+ if(layer.rescore) scale = state.input[in_i++];
+ else if(layer.nuisance){
+ layer.output[out_i++] = 1-state.input[in_i++];
+ scale = mask;
+ }
+ else if(layer.background) layer.output[out_i++] = scale*state.input[in_i++];
+
+ for(j = 0; j < layer.classes; ++j){
+ layer.output[out_i++] = scale*state.input[in_i++];
+ }
+ if(layer.nuisance){
+
+ }else if(layer.background){
+ softmax_array(layer.output + out_i - layer.classes-layer.background, layer.classes+layer.background, layer.output + out_i - layer.classes-layer.background);
+ activate_array(state.input+in_i, layer.coords, LOGISTIC);
+ }
+ for(j = 0; j < layer.coords; ++j){
+ 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){
+ 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)
{
int locations = get_detection_layer_locations(layer);
@@ -94,21 +129,20 @@
float scale = 1;
float latent_delta = 0;
if(layer.rescore) scale = state.input[in_i++];
- if(!layer.rescore){
- for(j = 0; j < layer.classes-1; ++j){
- if(state.truth[out_i + j]) dark_zone(layer, out_i+j, state);
- }
- }
+ else if (layer.nuisance) state.delta[in_i++] = -layer.delta[out_i++];
+ else if (layer.background) state.delta[in_i++] = scale*layer.delta[out_i++];
for(j = 0; j < layer.classes; ++j){
latent_delta += state.input[in_i]*layer.delta[out_i];
state.delta[in_i++] = scale*layer.delta[out_i++];
}
- if (!layer.rescore) gradient_array(layer.output + out_i, layer.coords, LOGISTIC, layer.delta + out_i);
+ if (layer.nuisance) {
+
+ }else if (layer.background) gradient_array(layer.output + out_i, layer.coords, LOGISTIC, layer.delta + out_i);
for(j = 0; j < layer.coords; ++j){
state.delta[in_i++] = layer.delta[out_i++];
}
- if(layer.rescore) state.delta[in_i-layer.coords-layer.classes-layer.rescore] = latent_delta;
+ if(layer.rescore) state.delta[in_i-layer.coords-layer.classes-layer.rescore-layer.background] = latent_delta;
}
}
--
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