Big changes to detection

Joseph Redmon

2015-03-04 fb9e0fe33681280112e4e33939c5844dba994dca

 src/network_kernels.cu

@@ -9,6 +9,7 @@

#include "crop_layer.h"
#include "connected_layer.h"
#include "detection_layer.h"
#include "convolutional_layer.h"
#include "deconvolutional_layer.h"
#include "maxpool_layer.h"
@@ -47,6 +48,11 @@
            forward_connected_layer_gpu(layer, input);
            input = layer.output_gpu;
        }
        else if(net.types[i] == DETECTION){
            detection_layer layer = *(detection_layer *)net.layers[i];
            forward_detection_layer_gpu(layer, input, truth);
            input = layer.output_gpu;
        }
        else if(net.types[i] == MAXPOOL){
            maxpool_layer layer = *(maxpool_layer *)net.layers[i];
            forward_maxpool_layer_gpu(layer, input);
@@ -73,7 +79,7 @@
    }
}

void backward_network_gpu(network net, float * input)
void backward_network_gpu(network net, float * input, float *truth)
{
    int i;
    float * prev_input;
@@ -103,6 +109,10 @@
            connected_layer layer = *(connected_layer *)net.layers[i];
            backward_connected_layer_gpu(layer, prev_input, prev_delta);
        }
        else if(net.types[i] == DETECTION){
            detection_layer layer = *(detection_layer *)net.layers[i];
            backward_detection_layer_gpu(layer, prev_input, prev_delta);
        }
        else if(net.types[i] == MAXPOOL){
            maxpool_layer layer = *(maxpool_layer *)net.layers[i];
            backward_maxpool_layer_gpu(layer, prev_delta);
@@ -148,6 +158,10 @@
        deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
        return layer.output_gpu;
    }
    else if(net.types[i] == DETECTION){
        detection_layer layer = *(detection_layer *)net.layers[i];
        return layer.output_gpu;
    }
    else if(net.types[i] == CONNECTED){
        connected_layer layer = *(connected_layer *)net.layers[i];
        return layer.output_gpu;
@@ -176,6 +190,10 @@
        convolutional_layer layer = *(convolutional_layer *)net.layers[i];
        return layer.delta_gpu;
    }
    else if(net.types[i] == DETECTION){
        detection_layer layer = *(detection_layer *)net.layers[i];
        return layer.delta_gpu;
    }
    else if(net.types[i] == DECONVOLUTIONAL){
        deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
        return layer.delta_gpu;
@@ -215,7 +233,7 @@
    forward_network_gpu(net, *net.input_gpu, *net.truth_gpu, 1);
  //printf("forw %f\n", sec(clock() - time));
  //time = clock();
    backward_network_gpu(net, *net.input_gpu);
    backward_network_gpu(net, *net.input_gpu, *net.truth_gpu);
  //printf("back %f\n", sec(clock() - time));
  //time = clock();
    update_network_gpu(net);
@@ -244,6 +262,12 @@
        cuda_pull_array(layer.output_gpu, layer.output, layer.outputs*layer.batch);
        return layer.output;
    }
    else if(net.types[i] == DETECTION){
        detection_layer layer = *(detection_layer *)net.layers[i];
        int outputs = get_detection_layer_output_size(layer);
        cuda_pull_array(layer.output_gpu, layer.output, outputs*layer.batch);
        return layer.output;
    }
    else if(net.types[i] == MAXPOOL){
        maxpool_layer layer = *(maxpool_layer *)net.layers[i];
        return layer.output;