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Code Issues Projects Releases Wiki Activity

Better VOC handling and resizing

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This commit is contained in:
Joseph Redmon
2014-03-12 21:57:34 -07:00
parent 15e86996d6
commit 2ea63c0e99
21 changed files with 288 additions and 173 deletions
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18
src/parser.c
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@ -52,6 +52,7 @@ convolutional_layer *parse_convolutional(list *options, network net, int count)
h = option_find_int(options, "height",1);
w = option_find_int(options, "width",1);
c = option_find_int(options, "channels",1);
net.batch = option_find_int(options, "batch",1);
}else{
image m = get_network_image_layer(net, count-1);
h = m.h;
@ -59,7 +60,7 @@ convolutional_layer *parse_convolutional(list *options, network net, int count)
c = m.c;
if(h == 0) error("Layer before convolutional layer must output image.");
}
convolutional_layer *layer = make_convolutional_layer(h,w,c,n,size,stride, activation);
convolutional_layer *layer = make_convolutional_layer(net.batch,h,w,c,n,size,stride, activation);
char *data = option_find_str(options, "data", 0);
if(data){
char *curr = data;
@ -90,10 +91,11 @@ connected_layer *parse_connected(list *options, network net, int count)
ACTIVATION activation = get_activation(activation_s);
if(count == 0){
input = option_find_int(options, "input",1);
net.batch = option_find_int(options, "batch",1);
}else{
input = get_network_output_size_layer(net, count-1);
}
connected_layer *layer = make_connected_layer(input, output, activation);
connected_layer *layer = make_connected_layer(net.batch, input, output, activation);
char *data = option_find_str(options, "data", 0);
if(data){
char *curr = data;
@ -120,10 +122,11 @@ softmax_layer *parse_softmax(list *options, network net, int count)
int input;
if(count == 0){
input = option_find_int(options, "input",1);
net.batch = option_find_int(options, "batch",1);
}else{
input = get_network_output_size_layer(net, count-1);
}
softmax_layer *layer = make_softmax_layer(input);
softmax_layer *layer = make_softmax_layer(net.batch, input);
option_unused(options);
return layer;
}
@ -136,6 +139,7 @@ maxpool_layer *parse_maxpool(list *options, network net, int count)
h = option_find_int(options, "height",1);
w = option_find_int(options, "width",1);
c = option_find_int(options, "channels",1);
net.batch = option_find_int(options, "batch",1);
}else{
image m = get_network_image_layer(net, count-1);
h = m.h;
@ -143,7 +147,7 @@ maxpool_layer *parse_maxpool(list *options, network net, int count)
c = m.c;
if(h == 0) error("Layer before convolutional layer must output image.");
}
maxpool_layer *layer = make_maxpool_layer(h,w,c,stride);
maxpool_layer *layer = make_maxpool_layer(net.batch,h,w,c,stride);
option_unused(options);
return layer;
}
@ -151,7 +155,7 @@ maxpool_layer *parse_maxpool(list *options, network net, int count)
network parse_network_cfg(char *filename)
{
list *sections = read_cfg(filename);
network net = make_network(sections->size);
network net = make_network(sections->size, 0);
node *n = sections->front;
int count = 0;
@ -162,18 +166,22 @@ network parse_network_cfg(char *filename)
convolutional_layer *layer = parse_convolutional(options, net, count);
net.types[count] = CONVOLUTIONAL;
net.layers[count] = layer;
net.batch = layer->batch;
}else if(is_connected(s)){
connected_layer *layer = parse_connected(options, net, count);
net.types[count] = CONNECTED;
net.layers[count] = layer;
net.batch = layer->batch;
}else if(is_softmax(s)){
softmax_layer *layer = parse_softmax(options, net, count);
net.types[count] = SOFTMAX;
net.layers[count] = layer;
net.batch = layer->batch;
}else if(is_maxpool(s)){
maxpool_layer *layer = parse_maxpool(options, net, count);
net.types[count] = MAXPOOL;
net.layers[count] = layer;
net.batch = layer->batch;
}else{
fprintf(stderr, "Type not recognized: %s\n", s->type);
}