From cd8a3dcb4ca42f22ad8f46a95e00977c92be6bbd Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Thu, 08 Feb 2018 23:22:42 +0000
Subject: [PATCH] Compile fixes
---
src/yolo.c | 186 +++++++++++-----------------------------------
1 files changed, 45 insertions(+), 141 deletions(-)
diff --git a/src/yolo.c b/src/yolo.c
index 2abfa13..e8b9e8b 100644
--- a/src/yolo.c
+++ b/src/yolo.c
@@ -4,52 +4,24 @@
#include "utils.h"
#include "parser.h"
#include "box.h"
+#include "demo.h"
#ifdef OPENCV
#include "opencv2/highgui/highgui_c.h"
+#include "opencv2/imgproc/imgproc_c.h"
+#include "opencv2/core/version.hpp"
+#ifndef CV_VERSION_EPOCH
+#include "opencv2/videoio/videoio_c.h"
+#endif
#endif
char *voc_names[] = {"aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"};
-void draw_yolo(image im, int num, float thresh, box *boxes, float **probs, char *label)
-{
- int classes = 20;
- int i;
-
- for(i = 0; i < num; ++i){
- int class = max_index(probs[i], classes);
- float prob = probs[i][class];
- if(prob > thresh){
- int width = pow(prob, 1./2.)*10;
- printf("%f %s\n", prob, voc_names[class]);
- float red = get_color(0,class,classes);
- float green = get_color(1,class,classes);
- float blue = get_color(2,class,classes);
- //red = green = blue = 0;
- box b = boxes[i];
-
- int left = (b.x-b.w/2.)*im.w;
- int right = (b.x+b.w/2.)*im.w;
- int top = (b.y-b.h/2.)*im.h;
- int bot = (b.y+b.h/2.)*im.h;
-
- if(left < 0) left = 0;
- if(right > im.w-1) right = im.w-1;
- if(top < 0) top = 0;
- if(bot > im.h-1) bot = im.h-1;
-
- draw_box_width(im, left, top, right, bot, width, red, green, blue);
- }
- }
- show_image(im, label);
-}
-
void train_yolo(char *cfgfile, char *weightfile)
{
- char *train_images = "data/voc.0712.trainval";
+ char *train_images = "/data/voc/train.txt";
char *backup_directory = "/home/pjreddie/backup/";
srand(time(0));
- data_seed = time(0);
char *base = basecfg(cfgfile);
printf("%s\n", base);
float avg_loss = -1;
@@ -85,6 +57,11 @@
args.d = &buffer;
args.type = REGION_DATA;
+ args.angle = net.angle;
+ args.exposure = net.exposure;
+ args.saturation = net.saturation;
+ args.hue = net.hue;
+
pthread_t load_thread = load_data_in_thread(args);
clock_t time;
//while(i*imgs < N*120){
@@ -97,21 +74,13 @@
printf("Loaded: %lf seconds\n", sec(clock()-time));
- /*
- image im = float_to_image(net.w, net.h, 3, train.X.vals[113]);
- image copy = copy_image(im);
- draw_yolo(copy, train.y.vals[113], 7, "truth");
- cvWaitKey(0);
- free_image(copy);
- */
-
time=clock();
float loss = train_network(net, train);
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);
- if(i%1000==0){
+ if(i%1000==0 || (i < 1000 && i%100 == 0)){
char buff[256];
sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i);
save_weights(net, buff);
@@ -123,34 +92,6 @@
save_weights(net, buff);
}
-void convert_yolo_detections(float *predictions, int classes, int num, int square, int side, int w, int h, float thresh, float **probs, box *boxes, int only_objectness)
-{
- int i,j,n;
- //int per_cell = 5*num+classes;
- for (i = 0; i < side*side; ++i){
- int row = i / side;
- int col = i % side;
- for(n = 0; n < num; ++n){
- int index = i*num + n;
- int p_index = side*side*classes + i*num + n;
- float scale = predictions[p_index];
- int box_index = side*side*(classes + num) + (i*num + n)*4;
- boxes[index].x = (predictions[box_index + 0] + col) / side * w;
- boxes[index].y = (predictions[box_index + 1] + row) / side * h;
- boxes[index].w = pow(predictions[box_index + 2], (square?2:1)) * w;
- boxes[index].h = pow(predictions[box_index + 3], (square?2:1)) * h;
- for(j = 0; j < classes; ++j){
- int class_index = i*classes;
- float prob = scale*predictions[class_index+j];
- probs[index][j] = (prob > thresh) ? prob : 0;
- }
- if(only_objectness){
- probs[index][0] = scale;
- }
- }
- }
-}
-
void print_yolo_detections(FILE **fps, char *id, box *boxes, float **probs, int total, int classes, int w, int h)
{
int i, j;
@@ -184,13 +125,12 @@
char *base = "results/comp4_det_test_";
//list *plist = get_paths("data/voc.2007.test");
- list *plist = get_paths("data/voc.2012.test");
+ list *plist = get_paths("/home/pjreddie/data/voc/2007_test.txt");
+ //list *plist = get_paths("data/voc.2012.test");
char **paths = (char **)list_to_array(plist);
layer l = net.layers[net.n-1];
int classes = l.classes;
- int square = l.sqrt;
- int side = l.side;
int j;
FILE **fps = calloc(classes, sizeof(FILE *));
@@ -199,9 +139,9 @@
snprintf(buff, 1024, "%s%s.txt", base, voc_names[j]);
fps[j] = fopen(buff, "w");
}
- box *boxes = calloc(side*side*l.n, sizeof(box));
- float **probs = calloc(side*side*l.n, sizeof(float *));
- for(j = 0; j < side*side*l.n; ++j) probs[j] = calloc(classes, sizeof(float *));
+ box *boxes = calloc(l.side*l.side*l.n, sizeof(box));
+ float **probs = calloc(l.side*l.side*l.n, sizeof(float *));
+ for(j = 0; j < l.side*l.side*l.n; ++j) probs[j] = calloc(classes, sizeof(float *));
int m = plist->size;
int i=0;
@@ -211,7 +151,7 @@
int nms = 1;
float iou_thresh = .5;
- int nthreads = 2;
+ int nthreads = 8;
image *val = calloc(nthreads, sizeof(image));
image *val_resized = calloc(nthreads, sizeof(image));
image *buf = calloc(nthreads, sizeof(image));
@@ -247,12 +187,12 @@
char *path = paths[i+t-nthreads];
char *id = basecfg(path);
float *X = val_resized[t].data;
- float *predictions = network_predict(net, X);
+ network_predict(net, X);
int w = val[t].w;
int h = val[t].h;
- convert_yolo_detections(predictions, classes, l.n, square, side, w, h, thresh, probs, boxes, 0);
- if (nms) do_nms_sort(boxes, probs, side*side*l.n, classes, iou_thresh);
- print_yolo_detections(fps, id, boxes, probs, side*side*l.n, classes, w, h);
+ get_detection_boxes(l, w, h, thresh, probs, boxes, 0);
+ if (nms) do_nms_sort(boxes, probs, l.side*l.side*l.n, classes, iou_thresh);
+ print_yolo_detections(fps, id, boxes, probs, l.side*l.side*l.n, classes, w, h);
free(id);
free_image(val[t]);
free_image(val_resized[t]);
@@ -277,7 +217,6 @@
layer l = net.layers[net.n-1];
int classes = l.classes;
- int square = l.sqrt;
int side = l.side;
int j, k;
@@ -295,9 +234,8 @@
int i=0;
float thresh = .001;
- int nms = 0;
float iou_thresh = .5;
- float nms_thresh = .5;
+ float nms = 0;
int total = 0;
int correct = 0;
@@ -309,14 +247,15 @@
image orig = load_image_color(path, 0, 0);
image sized = resize_image(orig, net.w, net.h);
char *id = basecfg(path);
- float *predictions = network_predict(net, sized.data);
- convert_yolo_detections(predictions, classes, l.n, square, side, 1, 1, thresh, probs, boxes, 1);
- if (nms) do_nms(boxes, probs, side*side*l.n, 1, nms_thresh);
+ network_predict(net, sized.data);
+ get_detection_boxes(l, orig.w, orig.h, thresh, probs, boxes, 1);
+ if (nms) do_nms(boxes, probs, side*side*l.n, 1, nms);
- char *labelpath = find_replace(path, "images", "labels");
- labelpath = find_replace(labelpath, "JPEGImages", "labels");
- labelpath = find_replace(labelpath, ".jpg", ".txt");
- labelpath = find_replace(labelpath, ".JPEG", ".txt");
+ char labelpath[4096];
+ find_replace(path, "images", "labels", labelpath);
+ find_replace(labelpath, "JPEGImages", "labels", labelpath);
+ find_replace(labelpath, ".jpg", ".txt", labelpath);
+ find_replace(labelpath, ".JPEG", ".txt", labelpath);
int num_labels = 0;
box_label *truth = read_boxes(labelpath, &num_labels);
@@ -350,7 +289,7 @@
void test_yolo(char *cfgfile, char *weightfile, char *filename, float thresh)
{
-
+ image **alphabet = load_alphabet();
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
@@ -362,7 +301,7 @@
char buff[256];
char *input = buff;
int j;
- float nms=.5;
+ float nms=.4;
box *boxes = calloc(l.side*l.side*l.n, sizeof(box));
float **probs = calloc(l.side*l.side*l.n, sizeof(float *));
for(j = 0; j < l.side*l.side*l.n; ++j) probs[j] = calloc(l.classes, sizeof(float *));
@@ -380,13 +319,15 @@
image sized = resize_image(im, net.w, net.h);
float *X = sized.data;
time=clock();
- float *predictions = network_predict(net, X);
+ network_predict(net, X);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
- convert_yolo_detections(predictions, l.classes, l.n, l.sqrt, l.side, 1, 1, thresh, probs, boxes, 0);
+ get_detection_boxes(l, 1, 1, thresh, probs, boxes, 0);
if (nms) do_nms_sort(boxes, probs, l.side*l.side*l.n, l.classes, nms);
- draw_yolo(im, l.side*l.side*l.n, thresh, boxes, probs, "predictions");
+ //draw_detections(im, l.side*l.side*l.n, thresh, boxes, probs, voc_names, alphabet, 20);
+ draw_detections(im, l.side*l.side*l.n, thresh, boxes, probs, voc_names, alphabet, 20);
+ save_image(im, "predictions");
+ show_image(im, "predictions");
- show_image(sized, "resized");
free_image(im);
free_image(sized);
#ifdef OPENCV
@@ -397,50 +338,13 @@
}
}
-/*
-#ifdef OPENCV
-image ipl_to_image(IplImage* src);
-#include "opencv2/highgui/highgui_c.h"
-#include "opencv2/imgproc/imgproc_c.h"
-
-void demo_swag(char *cfgfile, char *weightfile, float thresh)
-{
-network net = parse_network_cfg(cfgfile);
-if(weightfile){
-load_weights(&net, weightfile);
-}
-detection_layer layer = net.layers[net.n-1];
-CvCapture *capture = cvCaptureFromCAM(-1);
-set_batch_network(&net, 1);
-srand(2222222);
-while(1){
-IplImage* frame = cvQueryFrame(capture);
-image im = ipl_to_image(frame);
-cvReleaseImage(&frame);
-rgbgr_image(im);
-
-image sized = resize_image(im, net.w, net.h);
-float *X = sized.data;
-float *predictions = network_predict(net, X);
-draw_swag(im, predictions, layer.side, layer.n, "predictions", thresh);
-free_image(im);
-free_image(sized);
-cvWaitKey(10);
-}
-}
-#else
-void demo_swag(char *cfgfile, char *weightfile, float thresh){}
-#endif
- */
-
-void demo_yolo(char *cfgfile, char *weightfile, float thresh);
-#ifndef GPU
-void demo_yolo(char *cfgfile, char *weightfile, float thresh){}
-#endif
-
void run_yolo(int argc, char **argv)
{
+ char *out_filename = find_char_arg(argc, argv, "-out_filename", 0);
+ char *prefix = find_char_arg(argc, argv, "-prefix", 0);
float thresh = find_float_arg(argc, argv, "-thresh", .2);
+ int cam_index = find_int_arg(argc, argv, "-c", 0);
+ int frame_skip = find_int_arg(argc, argv, "-s", 0);
if(argc < 4){
fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
return;
@@ -453,5 +357,5 @@
else if(0==strcmp(argv[2], "train")) train_yolo(cfg, weights);
else if(0==strcmp(argv[2], "valid")) validate_yolo(cfg, weights);
else if(0==strcmp(argv[2], "recall")) validate_yolo_recall(cfg, weights);
- else if(0==strcmp(argv[2], "demo")) demo_yolo(cfg, weights, thresh);
+ else if(0==strcmp(argv[2], "demo")) demo(cfg, weights, thresh, cam_index, filename, voc_names, 20, frame_skip, prefix, out_filename);
}
--
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