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Parsing, image loading, lots of stuff

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Joseph Redmon
2013-11-13 10:50:38 -08:00
parent d7286c2732
commit 2db9fbef2b
29 changed files with 1295 additions and 278 deletions
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154
src/network.c
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@ -1,5 +1,7 @@
#include <stdio.h>
#include "network.h"
#include "image.h"
#include "data.h"
#include "connected_layer.h"
#include "convolutional_layer.h"
@ -14,27 +16,24 @@ network make_network(int n)
return net;
}
void run_network(image input, network net)
void forward_network(network net, double *input)
{
int i;
double *input_d = input.data;
for(i = 0; i < net.n; ++i){
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
run_convolutional_layer(input, layer);
forward_convolutional_layer(layer, input);
input = layer.output;
input_d = layer.output.data;
}
else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
run_connected_layer(input_d, layer);
input_d = layer.output;
forward_connected_layer(layer, input);
input = layer.output;
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
run_maxpool_layer(input, layer);
forward_maxpool_layer(layer, input);
input = layer.output;
input_d = layer.output.data;
}
}
}
@ -52,74 +51,112 @@ void update_network(network net, double step)
}
else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
update_connected_layer(layer, step);
update_connected_layer(layer, step, .3, 0);
}
}
}
void learn_network(image input, network net)
double *get_network_output_layer(network net, int i)
{
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
return layer.output;
} else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return layer.output;
} else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
return layer.output;
}
return 0;
}
double *get_network_output(network net)
{
return get_network_output_layer(net, net.n-1);
}
double *get_network_delta_layer(network net, int i)
{
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
return layer.delta;
} else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return layer.delta;
} else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
return layer.delta;
}
return 0;
}
double *get_network_delta(network net)
{
return get_network_delta_layer(net, net.n-1);
}
void learn_network(network net, double *input)
{
int i;
image prev;
double *prev_p;
double *prev_input;
double *prev_delta;
for(i = net.n-1; i >= 0; --i){
if(i == 0){
prev = input;
prev_p = prev.data;
} else if(net.types[i-1] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i-1];
prev = layer.output;
prev_p = prev.data;
} else if(net.types[i-1] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i-1];
prev = layer.output;
prev_p = prev.data;
} else if(net.types[i-1] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i-1];
prev_p = layer.output;
prev_input = input;
prev_delta = 0;
}else{
prev_input = get_network_output_layer(net, i-1);
prev_delta = get_network_delta_layer(net, i-1);
}
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
learn_convolutional_layer(prev, layer);
learn_convolutional_layer(layer, prev_input);
if(i != 0) backward_convolutional_layer(layer, prev_input, prev_delta);
}
else if(net.types[i] == MAXPOOL){
//maxpool_layer layer = *(maxpool_layer *)net.layers[i];
}
else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
learn_connected_layer(prev_p, layer);
learn_connected_layer(layer, prev_input);
if(i != 0) backward_connected_layer(layer, prev_input, prev_delta);
}
}
}
double *get_network_output_layer(network net, int i)
void train_network_batch(network net, batch b)
{
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
return layer.output.data;
int i,j;
int k = get_network_output_size(net);
int correct = 0;
for(i = 0; i < b.n; ++i){
forward_network(net, b.images[i].data);
image o = get_network_image(net);
double *output = get_network_output(net);
double *delta = get_network_delta(net);
for(j = 0; j < k; ++j){
//printf("%f %f\n", b.truth[i][j], output[j]);
delta[j] = b.truth[i][j]-output[j];
if(fabs(delta[j]) < .5) ++correct;
//printf("%f\n", output[j]);
}
learn_network(net, b.images[i].data);
update_network(net, .00001);
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return layer.output.data;
}
else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
return layer.output;
}
return 0;
printf("Accuracy: %f\n", (double)correct/b.n);
}
int get_network_output_size_layer(network net, int i)
{
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
return layer.output.h*layer.output.w*layer.output.c;
image output = get_convolutional_image(layer);
return output.h*output.w*output.c;
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return layer.output.h*layer.output.w*layer.output.c;
image output = get_maxpool_image(layer);
return output.h*output.w*output.c;
}
else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
@ -128,21 +165,21 @@ int get_network_output_size_layer(network net, int i)
return 0;
}
double *get_network_output(network net)
int get_network_output_size(network net)
{
int i = net.n-1;
return get_network_output_layer(net, i);
return get_network_output_size_layer(net, i);
}
image get_network_image_layer(network net, int i)
{
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
return layer.output;
return get_convolutional_image(layer);
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return layer.output;
return get_maxpool_image(layer);
}
return make_image(0,0,0);
}
@ -151,15 +188,20 @@ image get_network_image(network net)
{
int i;
for(i = net.n-1; i >= 0; --i){
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
return layer.output;
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return layer.output;
}
image m = get_network_image_layer(net, i);
if(m.h != 0) return m;
}
return make_image(1,1,1);
}
void visualize_network(network net)
{
int i;
for(i = 0; i < 1; ++i){
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
visualize_convolutional_layer(layer);
}
}
}