From fb9e0fe33681280112e4e33939c5844dba994dca Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 04 Mar 2015 22:56:38 +0000
Subject: [PATCH] Big changes to detection
---
src/detection_layer.c | 147 +++++++++++++++++++++++++++++++++----------------
1 files changed, 99 insertions(+), 48 deletions(-)
diff --git a/src/detection_layer.c b/src/detection_layer.c
index 6537079..bbc2e4f 100644
--- a/src/detection_layer.c
+++ b/src/detection_layer.c
@@ -1,72 +1,123 @@
-int detection_out_height(detection_layer layer)
+#include "detection_layer.h"
+#include "activations.h"
+#include "softmax_layer.h"
+#include "blas.h"
+#include "cuda.h"
+#include <stdio.h>
+#include <stdlib.h>
+
+int get_detection_layer_locations(detection_layer layer)
{
- return layer.size + layer.h*layer.stride;
+ return layer.inputs / (layer.classes+layer.coords+layer.rescore);
}
-int detection_out_width(detection_layer layer)
+int get_detection_layer_output_size(detection_layer layer)
{
- return layer.size + layer.w*layer.stride;
+ return get_detection_layer_locations(layer)*(layer.classes+layer.coords);
}
-detection_layer *make_detection_layer(int batch, int h, int w, int c, int n, int size, int stride, ACTIVATION activation)
+detection_layer *make_detection_layer(int batch, int inputs, int classes, int coords, int rescore)
{
- int i;
- size = 2*(size/2)+1; //HA! And you thought you'd use an even sized filter...
detection_layer *layer = calloc(1, sizeof(detection_layer));
- layer->h = h;
- layer->w = w;
- layer->c = c;
- layer->n = n;
+
layer->batch = batch;
- layer->stride = stride;
- layer->size = size;
- assert(c%n == 0);
+ layer->inputs = inputs;
+ layer->classes = classes;
+ layer->coords = coords;
+ layer->rescore = rescore;
+ int outputs = get_detection_layer_output_size(*layer);
+ layer->output = calloc(batch*outputs, sizeof(float));
+ layer->delta = calloc(batch*outputs, sizeof(float));
+ #ifdef GPU
+ layer->output_gpu = cuda_make_array(0, batch*outputs);
+ layer->delta_gpu = cuda_make_array(0, batch*outputs);
+ #endif
- layer->filters = calloc(c*size*size, sizeof(float));
- layer->filter_updates = calloc(c*size*size, sizeof(float));
- layer->filter_momentum = calloc(c*size*size, sizeof(float));
-
- float scale = 1./(size*size*c);
- for(i = 0; i < c*n*size*size; ++i) layer->filters[i] = scale*(rand_uniform());
-
- int out_h = detection_out_height(*layer);
- int out_w = detection_out_width(*layer);
-
- layer->output = calloc(layer->batch * out_h * out_w * n, sizeof(float));
- layer->delta = calloc(layer->batch * out_h * out_w * n, sizeof(float));
-
- layer->activation = activation;
-
- fprintf(stderr, "Convolutional Layer: %d x %d x %d image, %d filters -> %d x %d x %d image\n", h,w,c,n, out_h, out_w, n);
+ fprintf(stderr, "Detection Layer\n");
srand(0);
return layer;
}
-void forward_detection_layer(const detection_layer layer, float *in)
+void forward_detection_layer(const detection_layer layer, float *in, float *truth)
{
- int out_h = detection_out_height(layer);
- int out_w = detection_out_width(layer);
- int i,j,fh, fw,c;
- memset(layer.output, 0, layer->batch*layer->n*out_h*out_w*sizeof(float));
- for(c = 0; c < layer.c; ++c){
- for(i = 0; i < layer.h; ++i){
- for(j = 0; j < layer.w; ++j){
- float val = layer->input[j+(i + c*layer.h)*layer.w];
- for(fh = 0; fh < layer.size; ++fh){
- for(fw = 0; fw < layer.size; ++fw){
- int h = i*layer.stride + fh;
- int w = j*layer.stride + fw;
- layer.output[w+(h+c/n*out_h)*out_w] += val*layer->filters[fw+(fh+c*layer.size)*layer.size];
- }
- }
- }
+ 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 = (!truth || !truth[out_i + layer.classes - 1]);
+ float scale = 1;
+ if(layer.rescore) scale = in[in_i++];
+ for(j = 0; j < layer.classes; ++j){
+ layer.output[out_i++] = scale*in[in_i++];
}
+ softmax_array(layer.output + out_i - layer.classes, layer.classes, layer.output + out_i - layer.classes);
+ activate_array(layer.output+out_i, layer.coords, SIGMOID);
+ for(j = 0; j < layer.coords; ++j){
+ layer.output[out_i++] = mask*in[in_i++];
+ }
+ //printf("%d\n", mask);
+ //for(j = 0; j < layer.classes+layer.coords; ++j) printf("%f ", layer.output[i*(layer.classes+layer.coords)+j]);
+ //printf ("\n");
}
}
-void backward_detection_layer(const detection_layer layer, float *delta)
+void backward_detection_layer(const detection_layer layer, float *in, float *delta)
{
+ int locations = get_detection_layer_locations(layer);
+ int i,j;
+ int in_i = 0;
+ int out_i = 0;
+ for(i = 0; i < layer.batch*locations; ++i){
+ float scale = 1;
+ float latent_delta = 0;
+ if(layer.rescore) scale = in[in_i++];
+ for(j = 0; j < layer.classes; ++j){
+ latent_delta += in[in_i]*layer.delta[out_i];
+ delta[in_i++] = scale*layer.delta[out_i++];
+ }
+
+ for(j = 0; j < layer.coords; ++j){
+ delta[in_i++] = layer.delta[out_i++];
+ }
+ gradient_array(in + in_i - layer.coords, layer.coords, SIGMOID, layer.delta + out_i - layer.coords);
+ if(layer.rescore) delta[in_i-layer.coords-layer.classes-layer.rescore] = latent_delta;
+ }
}
+#ifdef GPU
+
+void forward_detection_layer_gpu(const detection_layer layer, float *in, float *truth)
+{
+ int outputs = get_detection_layer_output_size(layer);
+ float *in_cpu = calloc(layer.batch*layer.inputs, sizeof(float));
+ float *truth_cpu = 0;
+ if(truth){
+ truth_cpu = calloc(layer.batch*outputs, sizeof(float));
+ cuda_pull_array(truth, truth_cpu, layer.batch*outputs);
+ }
+ cuda_pull_array(in, in_cpu, layer.batch*layer.inputs);
+ forward_detection_layer(layer, in_cpu, truth_cpu);
+ cuda_push_array(layer.output_gpu, layer.output, layer.batch*outputs);
+ free(in_cpu);
+ if(truth_cpu) free(truth_cpu);
+}
+
+void backward_detection_layer_gpu(detection_layer layer, float *in, float *delta)
+{
+ int outputs = get_detection_layer_output_size(layer);
+
+ float *in_cpu = calloc(layer.batch*layer.inputs, sizeof(float));
+ float *delta_cpu = calloc(layer.batch*layer.inputs, sizeof(float));
+
+ cuda_pull_array(in, in_cpu, layer.batch*layer.inputs);
+ cuda_pull_array(layer.delta_gpu, layer.delta, layer.batch*outputs);
+ backward_detection_layer(layer, in_cpu, delta_cpu);
+ cuda_push_array(delta, delta_cpu, layer.batch*layer.inputs);
+
+ free(in_cpu);
+ free(delta_cpu);
+}
+#endif
--
Gitblit v1.10.0