From 729ce43e6ec45cfdb58e06e227428a0f81c5de0f Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Fri, 10 Jun 2016 00:20:31 +0000
Subject: [PATCH] stuff
---
src/darknet.c | 44 ++++++++++++++++++++++++++++++++++++++++----
1 files changed, 40 insertions(+), 4 deletions(-)
diff --git a/src/darknet.c b/src/darknet.c
index 938609e..a9b2433 100644
--- a/src/darknet.c
+++ b/src/darknet.c
@@ -6,6 +6,7 @@
#include "utils.h"
#include "cuda.h"
#include "blas.h"
+#include "connected_layer.h"
#ifdef OPENCV
#include "opencv2/highgui/highgui_c.h"
@@ -21,6 +22,11 @@
extern void run_compare(int argc, char **argv);
extern void run_classifier(int argc, char **argv);
extern void run_char_rnn(int argc, char **argv);
+extern void run_vid_rnn(int argc, char **argv);
+extern void run_tag(int argc, char **argv);
+extern void run_cifar(int argc, char **argv);
+extern void run_go(int argc, char **argv);
+extern void run_art(int argc, char **argv);
void change_rate(char *filename, float scale, float add)
{
@@ -168,16 +174,35 @@
{
gpu_index = -1;
network net = parse_network_cfg(cfgfile);
- if(weightfile){
+ if (weightfile) {
load_weights(&net, weightfile);
}
int i;
- for(i = 0; i < net.n; ++i){
+ for (i = 0; i < net.n; ++i) {
layer l = net.layers[i];
- if(l.type == CONVOLUTIONAL){
+ if (l.type == CONVOLUTIONAL && l.batch_normalize) {
denormalize_convolutional_layer(l);
net.layers[i].batch_normalize=0;
}
+ if (l.type == CONNECTED && l.batch_normalize) {
+ denormalize_connected_layer(l);
+ net.layers[i].batch_normalize=0;
+ }
+ if (l.type == GRU && l.batch_normalize) {
+ denormalize_connected_layer(*l.input_z_layer);
+ denormalize_connected_layer(*l.input_r_layer);
+ denormalize_connected_layer(*l.input_h_layer);
+ denormalize_connected_layer(*l.state_z_layer);
+ denormalize_connected_layer(*l.state_r_layer);
+ denormalize_connected_layer(*l.state_h_layer);
+ l.input_z_layer->batch_normalize = 0;
+ l.input_r_layer->batch_normalize = 0;
+ l.input_h_layer->batch_normalize = 0;
+ l.state_z_layer->batch_normalize = 0;
+ l.state_r_layer->batch_normalize = 0;
+ l.state_h_layer->batch_normalize = 0;
+ net.layers[i].batch_normalize=0;
+ }
}
save_weights(net, outfile);
}
@@ -206,7 +231,6 @@
gpu_index = find_int_arg(argc, argv, "-i", 0);
if(find_arg(argc, argv, "-nogpu")) {
gpu_index = -1;
- printf("nogpu\n");
}
#ifndef GPU
@@ -224,18 +248,30 @@
average(argc, argv);
} else if (0 == strcmp(argv[1], "yolo")){
run_yolo(argc, argv);
+ } else if (0 == strcmp(argv[1], "cifar")){
+ run_cifar(argc, argv);
+ } else if (0 == strcmp(argv[1], "go")){
+ run_go(argc, argv);
} else if (0 == strcmp(argv[1], "rnn")){
run_char_rnn(argc, argv);
+ } else if (0 == strcmp(argv[1], "vid")){
+ run_vid_rnn(argc, argv);
} else if (0 == strcmp(argv[1], "coco")){
run_coco(argc, argv);
} else if (0 == strcmp(argv[1], "classifier")){
run_classifier(argc, argv);
+ } else if (0 == strcmp(argv[1], "art")){
+ run_art(argc, argv);
+ } else if (0 == strcmp(argv[1], "tag")){
+ run_tag(argc, argv);
} else if (0 == strcmp(argv[1], "compare")){
run_compare(argc, argv);
} else if (0 == strcmp(argv[1], "dice")){
run_dice(argc, argv);
} else if (0 == strcmp(argv[1], "writing")){
run_writing(argc, argv);
+ } else if (0 == strcmp(argv[1], "3d")){
+ composite_3d(argv[2], argv[3], argv[4]);
} else if (0 == strcmp(argv[1], "test")){
test_resize(argv[2]);
} else if (0 == strcmp(argv[1], "captcha")){
--
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