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Detection is back, baby\!

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This commit is contained in:
Joseph Redmon
2015-02-10 19:41:03 -08:00
parent 979d02126b
commit 0f645836f1
24 changed files with 745 additions and 116 deletions
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61
src/network.c
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@ -8,6 +8,7 @@
#include "crop_layer.h"
#include "connected_layer.h"
#include "convolutional_layer.h"
#include "deconvolutional_layer.h"
#include "maxpool_layer.h"
#include "cost_layer.h"
#include "normalization_layer.h"
@ -20,6 +21,8 @@ char *get_layer_string(LAYER_TYPE a)
switch(a){
case CONVOLUTIONAL:
return "convolutional";
case DECONVOLUTIONAL:
return "deconvolutional";
case CONNECTED:
return "connected";
case MAXPOOL:
@ -68,6 +71,11 @@ void forward_network(network net, float *input, float *truth, int train)
forward_convolutional_layer(layer, input);
input = layer.output;
}
else if(net.types[i] == DECONVOLUTIONAL){
deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
forward_deconvolutional_layer(layer, input);
input = layer.output;
}
else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
forward_connected_layer(layer, input);
@ -122,14 +130,9 @@ void update_network(network net)
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
update_convolutional_layer(layer);
}
else if(net.types[i] == MAXPOOL){
//maxpool_layer layer = *(maxpool_layer *)net.layers[i];
}
else if(net.types[i] == SOFTMAX){
//maxpool_layer layer = *(maxpool_layer *)net.layers[i];
}
else if(net.types[i] == NORMALIZATION){
//maxpool_layer layer = *(maxpool_layer *)net.layers[i];
else if(net.types[i] == DECONVOLUTIONAL){
deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
update_deconvolutional_layer(layer);
}
else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
@ -143,6 +146,9 @@ float *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] == DECONVOLUTIONAL){
deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
return layer.output;
} else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return layer.output;
@ -178,6 +184,9 @@ float *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] == DECONVOLUTIONAL){
deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
return layer.delta;
} else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return layer.delta;
@ -247,9 +256,13 @@ void backward_network(network net, float *input)
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];
backward_convolutional_layer(layer, prev_input, prev_delta);
} else if(net.types[i] == DECONVOLUTIONAL){
deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
backward_deconvolutional_layer(layer, prev_input, prev_delta);
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
@ -377,6 +390,9 @@ void set_batch_network(network *net, int b)
if(net->types[i] == CONVOLUTIONAL){
convolutional_layer *layer = (convolutional_layer *)net->layers[i];
layer->batch = b;
}else if(net->types[i] == DECONVOLUTIONAL){
deconvolutional_layer *layer = (deconvolutional_layer *)net->layers[i];
layer->batch = b;
}
else if(net->types[i] == MAXPOOL){
maxpool_layer *layer = (maxpool_layer *)net->layers[i];
@ -415,6 +431,10 @@ int get_network_input_size_layer(network net, int i)
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
return layer.h*layer.w*layer.c;
}
if(net.types[i] == DECONVOLUTIONAL){
deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
return layer.h*layer.w*layer.c;
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return layer.h*layer.w*layer.c;
@ -448,6 +468,11 @@ int get_network_output_size_layer(network net, int i)
image output = get_convolutional_image(layer);
return output.h*output.w*output.c;
}
else if(net.types[i] == DECONVOLUTIONAL){
deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
image output = get_deconvolutional_image(layer);
return output.h*output.w*output.c;
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
image output = get_maxpool_image(layer);
@ -483,21 +508,31 @@ int resize_network(network net, int h, int w, int c)
for (i = 0; i < net.n; ++i){
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer *layer = (convolutional_layer *)net.layers[i];
resize_convolutional_layer(layer, h, w, c);
resize_convolutional_layer(layer, h, w);
image output = get_convolutional_image(*layer);
h = output.h;
w = output.w;
c = output.c;
} else if(net.types[i] == DECONVOLUTIONAL){
deconvolutional_layer *layer = (deconvolutional_layer *)net.layers[i];
resize_deconvolutional_layer(layer, h, w);
image output = get_deconvolutional_image(*layer);
h = output.h;
w = output.w;
c = output.c;
}else if(net.types[i] == MAXPOOL){
maxpool_layer *layer = (maxpool_layer *)net.layers[i];
resize_maxpool_layer(layer, h, w, c);
resize_maxpool_layer(layer, h, w);
image output = get_maxpool_image(*layer);
h = output.h;
w = output.w;
c = output.c;
}else if(net.types[i] == DROPOUT){
dropout_layer *layer = (dropout_layer *)net.layers[i];
resize_dropout_layer(layer, h*w*c);
}else if(net.types[i] == NORMALIZATION){
normalization_layer *layer = (normalization_layer *)net.layers[i];
resize_normalization_layer(layer, h, w, c);
resize_normalization_layer(layer, h, w);
image output = get_normalization_image(*layer);
h = output.h;
w = output.w;
@ -527,6 +562,10 @@ image get_network_image_layer(network net, int i)
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
return get_convolutional_image(layer);
}
else if(net.types[i] == DECONVOLUTIONAL){
deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
return get_deconvolutional_image(layer);
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
return get_maxpool_image(layer);