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changing data loading

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This commit is contained in:
Joseph Redmon
2015-08-24 18:27:42 -07:00
parent 3a99b8151f
commit 9d42f49a24
21 changed files with 1104 additions and 1231 deletions
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91
src/coco.c
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@ -15,41 +15,32 @@ char *coco_classes[] = {"person","bicycle","car","motorcycle","airplane","bus","
int coco_ids[] = {1,2,3,4,5,6,7,8,9,10,11,13,14,15,16,17,18,19,20,21,22,23,24,25,27,28,31,32,33,34,35,36,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,67,70,72,73,74,75,76,77,78,79,80,81,82,84,85,86,87,88,89,90};
void draw_coco(image im, float *box, int side, int objectness, char *label)
void draw_coco(image im, float *pred, int side, char *label)
{
int classes = 80;
int elems = 4+classes+objectness;
int classes = 81;
int elems = 4+classes;
int j;
int r, c;
for(r = 0; r < side; ++r){
for(c = 0; c < side; ++c){
j = (r*side + c) * elems;
float scale = 1;
if(objectness) scale = 1 - box[j++];
int class = max_index(box+j, classes);
if(scale * box[j+class] > 0.2){
int width = box[j+class]*5 + 1;
printf("%f %s\n", scale * box[j+class], coco_classes[class]);
int class = max_index(pred+j, classes);
if (class == 0) continue;
if (pred[j+class] > 0.2){
int width = pred[j+class]*5 + 1;
printf("%f %s\n", pred[j+class], coco_classes[class-1]);
float red = get_color(0,class,classes);
float green = get_color(1,class,classes);
float blue = get_color(2,class,classes);
j += classes;
float x = box[j+0];
float y = box[j+1];
x = (x+c)/side;
y = (y+r)/side;
float w = box[j+2]; //*maxwidth;
float h = box[j+3]; //*maxheight;
h = h*h;
w = w*w;
int left = (x-w/2)*im.w;
int right = (x+w/2)*im.w;
int top = (y-h/2)*im.h;
int bot = (y+h/2)*im.h;
draw_box_width(im, left, top, right, bot, width, red, green, blue);
box predict = {pred[j+0], pred[j+1], pred[j+2], pred[j+3]};
box anchor = {(c+.5)/side, (r+.5)/side, .5, .5};
box decode = decode_box(predict, anchor);
draw_bbox(im, decode, width, red, green, blue);
}
}
}
@ -69,39 +60,47 @@ void train_coco(char *cfgfile, char *weightfile)
if(weightfile){
load_weights(&net, weightfile);
}
detection_layer layer = get_network_detection_layer(net);
printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
int imgs = 128;
int i = net.seen/imgs;
data train, buffer;
int classes = layer.classes;
int background = layer.objectness;
int side = sqrt(get_detection_layer_locations(layer));
int classes = 81;
int side = 7;
char **paths;
list *plist = get_paths(train_images);
int N = plist->size;
char **paths = (char **)list_to_array(plist);
paths = (char **)list_to_array(plist);
pthread_t load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.w, net.h, side, side, background, &buffer);
load_args args = {0};
args.w = net.w;
args.h = net.h;
args.paths = paths;
args.n = imgs;
args.m = plist->size;
args.classes = classes;
args.num_boxes = side;
args.d = &buffer;
args.type = REGION_DATA;
pthread_t load_thread = load_data_in_thread(args);
clock_t time;
while(i*imgs < N*120){
i += 1;
time=clock();
pthread_join(load_thread, 0);
train = buffer;
load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.w, net.h, side, side, background, &buffer);
load_thread = load_data_in_thread(args);
printf("Loaded: %lf seconds\n", sec(clock()-time));
/*
image im = float_to_image(net.w, net.h, 3, train.X.vals[114]);
image copy = copy_image(im);
draw_coco(copy, train.y.vals[114], 7, layer.objectness, "truth");
cvWaitKey(0);
free_image(copy);
*/
/*
image im = float_to_image(net.w, net.h, 3, train.X.vals[114]);
image copy = copy_image(im);
draw_coco(copy, train.y.vals[114], 7, "truth");
cvWaitKey(0);
free_image(copy);
*/
time=clock();
float loss = train_network(net, train);
@ -220,6 +219,11 @@ void validate_coco(char *cfgfile, char *weightfile)
int nms = 1;
float iou_thresh = .5;
load_args args = {0};
args.w = net.w;
args.h = net.h;
args.type = IMAGE_DATA;
int nthreads = 8;
image *val = calloc(nthreads, sizeof(image));
image *val_resized = calloc(nthreads, sizeof(image));
@ -227,7 +231,10 @@ void validate_coco(char *cfgfile, char *weightfile)
image *buf_resized = calloc(nthreads, sizeof(image));
pthread_t *thr = calloc(nthreads, sizeof(pthread_t));
for(t = 0; t < nthreads; ++t){
thr[t] = load_image_thread(paths[i+t], &buf[t], &buf_resized[t], net.w, net.h);
args.path = paths[i+t];
args.im = &buf[t];
args.resized = &buf_resized[t];
thr[t] = load_data_in_thread(args);
}
time_t start = time(0);
for(i = nthreads; i < m+nthreads; i += nthreads){
@ -238,7 +245,10 @@ void validate_coco(char *cfgfile, char *weightfile)
val_resized[t] = buf_resized[t];
}
for(t = 0; t < nthreads && i+t < m; ++t){
thr[t] = load_image_thread(paths[i+t], &buf[t], &buf_resized[t], net.w, net.h);
args.path = paths[i+t];
args.im = &buf[t];
args.resized = &buf_resized[t];
thr[t] = load_data_in_thread(args);
}
for(t = 0; t < nthreads && i+t-nthreads < m; ++t){
char *path = paths[i+t-nthreads];
@ -267,7 +277,6 @@ void test_coco(char *cfgfile, char *weightfile, char *filename)
if(weightfile){
load_weights(&net, weightfile);
}
detection_layer layer = get_network_detection_layer(net);
set_batch_network(&net, 1);
srand(2222222);
clock_t time;
@ -287,7 +296,7 @@ void test_coco(char *cfgfile, char *weightfile, char *filename)
time=clock();
float *predictions = network_predict(net, X);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
draw_coco(im, predictions, 7, layer.objectness, "predictions");
draw_coco(im, predictions, 7, "predictions");
free_image(im);
free_image(sized);
#ifdef OPENCV