From 9d42f49a240136a8cd643cdc1f98230d4f22b05e Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Tue, 25 Aug 2015 01:27:42 +0000
Subject: [PATCH] changing data loading
---
src/coco.c | 91 +++++++++++++++++++++++++--------------------
1 files changed, 50 insertions(+), 41 deletions(-)
diff --git a/src/coco.c b/src/coco.c
index 66fddf5..d2a108a 100644
--- a/src/coco.c
+++ b/src/coco.c
@@ -15,41 +15,32 @@
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 @@
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 @@
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 @@
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 @@
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 @@
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 @@
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
--
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