From 9a01e6ccb7a74ff77e99060cf18acd6cfdb74b8e Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Fri, 11 Nov 2016 16:48:40 +0000
Subject: [PATCH] :fire: crush. crush. admit. :fire:

---
 src/detector.c |  165 ++++++++++++++++++++++++++++++++++++++++++++-----------
 1 files changed, 132 insertions(+), 33 deletions(-)

diff --git a/src/detector.c b/src/detector.c
index e020be5..f18ae51 100644
--- a/src/detector.c
+++ b/src/detector.c
@@ -10,8 +10,9 @@
 #ifdef OPENCV
 #include "opencv2/highgui/highgui_c.h"
 #endif
+static 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 train_detector(char *datacfg, char *cfgfile, char *weightfile, int clear)
+void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear)
 {
     list *options = read_data_cfg(datacfg);
     char *train_images = option_find_str(options, "train", "data/train.list");
@@ -21,14 +22,28 @@
     char *base = basecfg(cfgfile);
     printf("%s\n", base);
     float avg_loss = -1;
-    network net = parse_network_cfg(cfgfile);
-    if(weightfile){
-        load_weights(&net, weightfile);
+    network *nets = calloc(ngpus, sizeof(network));
+
+    srand(time(0));
+    int seed = rand();
+    int i;
+    for(i = 0; i < ngpus; ++i){
+        srand(seed);
+#ifdef GPU
+        cuda_set_device(gpus[i]);
+#endif
+        nets[i] = parse_network_cfg(cfgfile);
+        if(weightfile){
+            load_weights(&nets[i], weightfile);
+        }
+        if(clear) *nets[i].seen = 0;
+        nets[i].learning_rate *= ngpus;
     }
-    if(clear) *net.seen = 0;
+    srand(time(0));
+    network net = nets[0];
+
+    int imgs = net.batch * net.subdivisions * ngpus;
     printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
-    int imgs = net.batch*net.subdivisions;
-    int i = *net.seen/imgs;
     data train, buffer;
 
     layer l = net.layers[net.n - 1];
@@ -62,37 +77,46 @@
     clock_t time;
     //while(i*imgs < N*120){
     while(get_current_batch(net) < net.max_batches){
-        i += 1;
         time=clock();
         pthread_join(load_thread, 0);
         train = buffer;
         load_thread = load_data(args);
 
-/*
-        int k;
-        for(k = 0; k < l.max_boxes; ++k){
-            box b = float_to_box(train.y.vals[10] + 1 + k*5);
-            if(!b.x) break;
-            printf("loaded: %f %f %f %f\n", b.x, b.y, b.w, b.h);
-        }
-        image im = float_to_image(448, 448, 3, train.X.vals[10]);
-        int k;
-        for(k = 0; k < l.max_boxes; ++k){
-            box b = float_to_box(train.y.vals[10] + 1 + k*5);
-            printf("%d %d %d %d\n", truth.x, truth.y, truth.w, truth.h);
-            draw_bbox(im, b, 8, 1,0,0);
-        }
-        save_image(im, "truth11");
-*/
+        /*
+           int k;
+           for(k = 0; k < l.max_boxes; ++k){
+           box b = float_to_box(train.y.vals[10] + 1 + k*5);
+           if(!b.x) break;
+           printf("loaded: %f %f %f %f\n", b.x, b.y, b.w, b.h);
+           }
+           image im = float_to_image(448, 448, 3, train.X.vals[10]);
+           int k;
+           for(k = 0; k < l.max_boxes; ++k){
+           box b = float_to_box(train.y.vals[10] + 1 + k*5);
+           printf("%d %d %d %d\n", truth.x, truth.y, truth.w, truth.h);
+           draw_bbox(im, b, 8, 1,0,0);
+           }
+           save_image(im, "truth11");
+         */
 
         printf("Loaded: %lf seconds\n", sec(clock()-time));
 
         time=clock();
-        float loss = train_network(net, train);
+        float loss = 0;
+#ifdef GPU
+        if(ngpus == 1){
+            loss = train_network(net, train);
+        } else {
+            loss = train_networks(nets, ngpus, train, 4);
+        }
+#else
+        loss = train_network(net, train);
+#endif
         if (avg_loss < 0) avg_loss = loss;
         avg_loss = avg_loss*.9 + loss*.1;
 
-        printf("%d: %f, %f avg, %f rate, %lf seconds, %d images\n", i, loss, avg_loss, get_current_rate(net), sec(clock()-time), i*imgs);
+        i = get_current_batch(net);
+        printf("%d: %f, %f avg, %f rate, %lf seconds, %d images\n", get_current_batch(net), loss, avg_loss, get_current_rate(net), sec(clock()-time), i*imgs);
         if(i%1000==0 || (i < 1000 && i%100 == 0)){
             char buff[256];
             sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i);
@@ -105,6 +129,39 @@
     save_weights(net, buff);
 }
 
+
+static int get_coco_image_id(char *filename)
+{
+    char *p = strrchr(filename, '_');
+    return atoi(p+1);
+}
+
+static void print_cocos(FILE *fp, char *image_path, box *boxes, float **probs, int num_boxes, int classes, int w, int h)
+{
+    int i, j;
+    int image_id = get_coco_image_id(image_path);
+    for(i = 0; i < num_boxes; ++i){
+        float xmin = boxes[i].x - boxes[i].w/2.;
+        float xmax = boxes[i].x + boxes[i].w/2.;
+        float ymin = boxes[i].y - boxes[i].h/2.;
+        float ymax = boxes[i].y + boxes[i].h/2.;
+
+        if (xmin < 0) xmin = 0;
+        if (ymin < 0) ymin = 0;
+        if (xmax > w) xmax = w;
+        if (ymax > h) ymax = h;
+
+        float bx = xmin;
+        float by = ymin;
+        float bw = xmax - xmin;
+        float bh = ymax - ymin;
+
+        for(j = 0; j < classes; ++j){
+            if (probs[i][j]) fprintf(fp, "{\"image_id\":%d, \"category_id\":%d, \"bbox\":[%f, %f, %f, %f], \"score\":%f},\n", image_id, coco_ids[j], bx, by, bw, bh, probs[i][j]);
+        }
+    }
+}
+
 void print_detector_detections(FILE **fps, char *id, box *boxes, float **probs, int total, int classes, int w, int h)
 {
     int i, j;
@@ -131,8 +188,19 @@
     list *options = read_data_cfg(datacfg);
     char *valid_images = option_find_str(options, "valid", "data/train.list");
     char *name_list = option_find_str(options, "names", "data/names.list");
+    char *prefix = option_find_str(options, "results", "results");
     char **names = get_labels(name_list);
 
+
+    char buff[1024];
+    int coco = option_find_int_quiet(options, "coco", 0);
+    FILE *coco_fp = 0;
+    if(coco){
+        snprintf(buff, 1024, "%s/coco_results.json", prefix);
+        coco_fp = fopen(buff, "w");
+        fprintf(coco_fp, "[\n");
+    }
+
     network net = parse_network_cfg(cfgfile);
     if(weightfile){
         load_weights(&net, weightfile);
@@ -141,7 +209,7 @@
     fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
     srand(time(0));
 
-    char *base = "results/comp4_det_test_";
+    char *base = "comp4_det_test_";
     list *plist = get_paths(valid_images);
     char **paths = (char **)list_to_array(plist);
 
@@ -151,8 +219,7 @@
     int j;
     FILE **fps = calloc(classes, sizeof(FILE *));
     for(j = 0; j < classes; ++j){
-        char buff[1024];
-        snprintf(buff, 1024, "%s%s.txt", base, names[j]);
+        snprintf(buff, 1024, "%s/%s%s.txt", prefix, base, names[j]);
         fps[j] = fopen(buff, "w");
     }
     box *boxes = calloc(l.w*l.h*l.n, sizeof(box));
@@ -207,7 +274,11 @@
             int h = val[t].h;
             get_region_boxes(l, w, h, thresh, probs, boxes, 0);
             if (nms) do_nms_sort(boxes, probs, l.w*l.h*l.n, classes, nms);
-            print_detector_detections(fps, id, boxes, probs, l.w*l.h*l.n, classes, w, h);
+            if(coco_fp){
+                print_cocos(coco_fp, path, boxes, probs, l.w*l.h*l.n, classes, w, h);
+            }else{
+                print_detector_detections(fps, id, boxes, probs, l.w*l.h*l.n, classes, w, h);
+            }
             free(id);
             free_image(val[t]);
             free_image(val_resized[t]);
@@ -216,6 +287,11 @@
     for(j = 0; j < classes; ++j){
         fclose(fps[j]);
     }
+    if(coco_fp){
+        fseek(coco_fp, -2, SEEK_CUR); 
+        fprintf(coco_fp, "\n]\n");
+        fclose(coco_fp);
+    }
     fprintf(stderr, "Total Detection Time: %f Seconds\n", (double)(time(0) - start));
 }
 
@@ -300,8 +376,8 @@
 void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh)
 {
     list *options = read_data_cfg(datacfg);
-        char *name_list = option_find_str(options, "names", "data/names.list");
-        char **names = get_labels(name_list);
+    char *name_list = option_find_str(options, "names", "data/names.list");
+    char **names = get_labels(name_list);
 
     image **alphabet = load_alphabet();
     network net = parse_network_cfg(cfgfile);
@@ -361,6 +437,29 @@
         fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
         return;
     }
+    char *gpu_list = find_char_arg(argc, argv, "-gpus", 0);
+    int *gpus = 0;
+    int gpu = 0;
+    int ngpus = 0;
+    if(gpu_list){
+        printf("%s\n", gpu_list);
+        int len = strlen(gpu_list);
+        ngpus = 1;
+        int i;
+        for(i = 0; i < len; ++i){
+            if (gpu_list[i] == ',') ++ngpus;
+        }
+        gpus = calloc(ngpus, sizeof(int));
+        for(i = 0; i < ngpus; ++i){
+            gpus[i] = atoi(gpu_list);
+            gpu_list = strchr(gpu_list, ',')+1;
+        }
+    } else {
+        gpu = gpu_index;
+        gpus = &gpu;
+        ngpus = 1;
+    }
+
     int clear = find_arg(argc, argv, "-clear");
 
     char *datacfg = argv[3];
@@ -368,7 +467,7 @@
     char *weights = (argc > 5) ? argv[5] : 0;
     char *filename = (argc > 6) ? argv[6]: 0;
     if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh);
-    else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, clear);
+    else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear);
     else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights);
     else if(0==strcmp(argv[2], "recall")) validate_detector_recall(cfg, weights);
     else if(0==strcmp(argv[2], "demo")) {

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