diff --git a/Makefile b/Makefile
index eff05bcb3de42d08bdb6eb7d2cc8eb78763d8c95..66a851d87e09c7ddab8b5965a8890cb63df57028 100644
--- a/Makefile
+++ b/Makefile
@@ -1,5 +1,5 @@
-GPU=0
-OPENCV=0
+GPU=1
+OPENCV=1
DEBUG=0
ARCH= --gpu-architecture=compute_20 --gpu-code=compute_20
@@ -34,7 +34,7 @@ CFLAGS+= -DGPU
LDFLAGS+= -L/usr/local/cuda/lib64 -lcuda -lcudart -lcublas -lcurand
endif
-OBJ=gemm.o utils.o cuda.o deconvolutional_layer.o convolutional_layer.o list.o image.o activations.o im2col.o col2im.o blas.o crop_layer.o dropout_layer.o maxpool_layer.o softmax_layer.o data.o matrix.o network.o connected_layer.o cost_layer.o parser.o option_list.o darknet.o detection_layer.o imagenet.o captcha.o detection.o route_layer.o writing.o box.o nightmare.o normalization_layer.o avgpool_layer.o coco.o
+OBJ=gemm.o utils.o cuda.o deconvolutional_layer.o convolutional_layer.o list.o image.o activations.o im2col.o col2im.o blas.o crop_layer.o dropout_layer.o maxpool_layer.o softmax_layer.o data.o matrix.o network.o connected_layer.o cost_layer.o parser.o option_list.o darknet.o detection_layer.o imagenet.o captcha.o detection.o route_layer.o writing.o box.o nightmare.o normalization_layer.o avgpool_layer.o coco.o dice.o
ifeq ($(GPU), 1)
OBJ+=convolutional_kernels.o deconvolutional_kernels.o activation_kernels.o im2col_kernels.o col2im_kernels.o blas_kernels.o crop_layer_kernels.o dropout_layer_kernels.o maxpool_layer_kernels.o softmax_layer_kernels.o network_kernels.o avgpool_layer_kernels.o
endif
diff --git a/scripts/dice_label.sh b/scripts/dice_label.sh
new file mode 100644
index 0000000000000000000000000000000000000000..f19f8a49481b46d5a04dd18b1b05af8928b21957
--- /dev/null
+++ b/scripts/dice_label.sh
@@ -0,0 +1,20 @@
+mkdir -p images
+mkdir -p images/orig
+mkdir -p images/train
+mkdir -p images/val
+
+ffmpeg -i Face1.mp4 images/orig/face1_%6d.jpg
+ffmpeg -i Face2.mp4 images/orig/face2_%6d.jpg
+ffmpeg -i Face3.mp4 images/orig/face3_%6d.jpg
+ffmpeg -i Face4.mp4 images/orig/face4_%6d.jpg
+ffmpeg -i Face5.mp4 images/orig/face5_%6d.jpg
+ffmpeg -i Face6.mp4 images/orig/face6_%6d.jpg
+
+mogrify -resize 100x100^ -gravity center -crop 100x100+0+0 +repage images/orig/*
+
+ls images/orig/* | shuf | head -n 1000 | xargs mv -t images/val
+mv images/orig/* images/train
+
+find `pwd`/images/train > dice.train.list -name \*.jpg
+find `pwd`/images/val > dice.val.list -name \*.jpg
+
diff --git a/src/darknet.c b/src/darknet.c
index d7fb1f5c43be9edc1ec6db56d04318f868a8cde1..c03ba5b1f5c5a986584081dc33aa3114e4159b28 100644
--- a/src/darknet.c
+++ b/src/darknet.c
@@ -15,6 +15,7 @@ extern void run_coco(int argc, char **argv);
extern void run_writing(int argc, char **argv);
extern void run_captcha(int argc, char **argv);
extern void run_nightmare(int argc, char **argv);
+extern void run_dice(int argc, char **argv);
void change_rate(char *filename, float scale, float add)
{
@@ -115,6 +116,8 @@ int main(int argc, char **argv)
run_detection(argc, argv);
} else if (0 == strcmp(argv[1], "coco")){
run_coco(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], "test")){
diff --git a/src/dice.c b/src/dice.c
new file mode 100644
index 0000000000000000000000000000000000000000..3283fe9503b8b8d0e45a2f84e2941331bfc4a656
--- /dev/null
+++ b/src/dice.c
@@ -0,0 +1,118 @@
+#include "network.h"
+#include "utils.h"
+#include "parser.h"
+
+char *dice_labels[] = {"face1","face2","face3","face4","face5","face6"};
+
+void train_dice(char *cfgfile, char *weightfile)
+{
+ data_seed = time(0);
+ srand(time(0));
+ float avg_loss = -1;
+ char *base = basecfg(cfgfile);
+ char *backup_directory = "/home/pjreddie/backup/";
+ printf("%s\n", base);
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
+ int imgs = 1024;
+ int i = net.seen/imgs;
+ char **labels = dice_labels;
+ list *plist = get_paths("data/dice/dice.train.list");
+ char **paths = (char **)list_to_array(plist);
+ printf("%d\n", plist->size);
+ clock_t time;
+ while(1){
+ ++i;
+ time=clock();
+ data train = load_data(paths, imgs, plist->size, labels, 6, net.w, net.h);
+ printf("Loaded: %lf seconds\n", sec(clock()-time));
+
+ time=clock();
+ float loss = train_network(net, train);
+ net.seen += imgs;
+ if(avg_loss == -1) avg_loss = loss;
+ avg_loss = avg_loss*.9 + loss*.1;
+ printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), net.seen);
+ free_data(train);
+ if((i % 100) == 0) net.learning_rate *= .1;
+ if(i%100==0){
+ char buff[256];
+ sprintf(buff, "%s/%s_%d.weights",backup_directory,base, i);
+ save_weights(net, buff);
+ }
+ }
+}
+
+void validate_dice(char *filename, char *weightfile)
+{
+ network net = parse_network_cfg(filename);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ srand(time(0));
+
+ char **labels = dice_labels;
+ list *plist = get_paths("data/dice/dice.val.list");
+
+ char **paths = (char **)list_to_array(plist);
+ int m = plist->size;
+ free_list(plist);
+
+ data val = load_data(paths, m, 0, labels, 6, net.w, net.h);
+ float *acc = network_accuracies(net, val);
+ printf("Validation Accuracy: %f, %d images\n", acc[0], m);
+ free_data(val);
+}
+
+void test_dice(char *cfgfile, char *weightfile, char *filename)
+{
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ set_batch_network(&net, 1);
+ srand(2222222);
+ int i = 0;
+ char **names = dice_labels;
+ char input[256];
+ int indexes[6];
+ while(1){
+ if(filename){
+ strncpy(input, filename, 256);
+ }else{
+ printf("Enter Image Path: ");
+ fflush(stdout);
+ fgets(input, 256, stdin);
+ strtok(input, "\n");
+ }
+ image im = load_image_color(input, net.w, net.h);
+ float *X = im.data;
+ float *predictions = network_predict(net, X);
+ top_predictions(net, 6, indexes);
+ for(i = 0; i < 6; ++i){
+ int index = indexes[i];
+ printf("%s: %f\n", names[index], predictions[index]);
+ }
+ free_image(im);
+ if (filename) break;
+ }
+}
+
+void run_dice(int argc, char **argv)
+{
+ if(argc < 4){
+ fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
+ return;
+ }
+
+ char *cfg = argv[3];
+ char *weights = (argc > 4) ? argv[4] : 0;
+ char *filename = (argc > 5) ? argv[5]: 0;
+ if(0==strcmp(argv[2], "test")) test_dice(cfg, weights, filename);
+ else if(0==strcmp(argv[2], "train")) train_dice(cfg, weights);
+ else if(0==strcmp(argv[2], "valid")) validate_dice(cfg, weights);
+}
+
diff --git a/src/imagenet.c b/src/imagenet.c
index 96e74d0ab9873bc489f627fe910b20b3f5eff28d..499a8d3a8d0725f0c4fba19f75ce30103c66c020 100644
--- a/src/imagenet.c
+++ b/src/imagenet.c
@@ -8,6 +8,7 @@ void train_imagenet(char *cfgfile, char *weightfile)
srand(time(0));
float avg_loss = -1;
char *base = basecfg(cfgfile);
+ char *backup_directory = "/home/pjreddie/backup/";
printf("%s\n", base);
network net = parse_network_cfg(cfgfile);
if(weightfile){
@@ -50,7 +51,7 @@ void train_imagenet(char *cfgfile, char *weightfile)
if((i % 30000) == 0) net.learning_rate *= .1;
if(i%1000==0){
char buff[256];
- sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i);
+ sprintf(buff, "%s/%s_%d.weights",backup_directory,base, i);
save_weights(net, buff);
}
}