From db0397cfaaf488364e3d2e1669dfefae2ee6ea73 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 14 Dec 2015 19:57:10 +0000
Subject: [PATCH] shortcut layers, msr networks
---
src/coco_kernels.cu | 40 ++++++++++++++++++++++++++++++++--------
1 files changed, 32 insertions(+), 8 deletions(-)
diff --git a/src/coco_kernels.cu b/src/coco_kernels.cu
index 2ec0915..0a5f840 100644
--- a/src/coco_kernels.cu
+++ b/src/coco_kernels.cu
@@ -20,7 +20,7 @@
extern "C" void convert_coco_detections(float *predictions, int classes, int num, int square, int side, int w, int h, float thresh, float **probs, box *boxes, int only_objectness);
extern "C" char *coco_classes[];
-extern "C" image *coco_labels;
+extern "C" image coco_labels[];
static float **probs;
static box *boxes;
@@ -32,6 +32,13 @@
static image disp ;
static cv::VideoCapture cap;
static float fps = 0;
+static float demo_thresh = 0;
+
+static const int frames = 3;
+static float *predictions[frames];
+static int demo_index = 0;
+static image images[frames];
+static float *avg;
void *fetch_in_thread_coco(void *ptr)
{
@@ -47,24 +54,33 @@
void *detect_in_thread_coco(void *ptr)
{
float nms = .4;
- float thresh = .2;
detection_layer l = net.layers[net.n-1];
float *X = det_s.data;
- float *predictions = network_predict(net, X);
+ float *prediction = network_predict(net, X);
+
+ memcpy(predictions[demo_index], prediction, l.outputs*sizeof(float));
+ mean_arrays(predictions, frames, l.outputs, avg);
+
free_image(det_s);
- convert_coco_detections(predictions, l.classes, l.n, l.sqrt, l.side, 1, 1, thresh, probs, boxes, 0);
+ convert_coco_detections(avg, l.classes, l.n, l.sqrt, l.side, 1, 1, demo_thresh, probs, boxes, 0);
if (nms > 0) do_nms(boxes, probs, l.side*l.side*l.n, l.classes, nms);
printf("\033[2J");
printf("\033[1;1H");
printf("\nFPS:%.0f\n",fps);
printf("Objects:\n\n");
- draw_detections(det, l.side*l.side*l.n, thresh, boxes, probs, coco_classes, coco_labels, 80);
+
+ images[demo_index] = det;
+ det = images[(demo_index + frames/2 + 1)%frames];
+ demo_index = (demo_index + 1)%frames;
+
+ draw_detections(det, l.side*l.side*l.n, demo_thresh, boxes, probs, coco_classes, coco_labels, 80);
return 0;
}
-extern "C" void demo_coco(char *cfgfile, char *weightfile, float thresh, int cam_index)
+extern "C" void demo_coco(char *cfgfile, char *weightfile, float thresh, int cam_index, const char *filename)
{
+ demo_thresh = thresh;
printf("YOLO demo\n");
net = parse_network_cfg(cfgfile);
if(weightfile){
@@ -74,13 +90,21 @@
srand(2222222);
- cv::VideoCapture cam(cam_index);
- cap = cam;
+ if(filename){
+ cap.open(filename);
+ }else{
+ cap.open(cam_index);
+ }
+
if(!cap.isOpened()) error("Couldn't connect to webcam.\n");
detection_layer l = net.layers[net.n-1];
int j;
+ avg = (float *) calloc(l.outputs, sizeof(float));
+ for(j = 0; j < frames; ++j) predictions[j] = (float *) calloc(l.outputs, sizeof(float));
+ for(j = 0; j < frames; ++j) images[j] = make_image(1,1,3);
+
boxes = (box *)calloc(l.side*l.side*l.n, sizeof(box));
probs = (float **)calloc(l.side*l.side*l.n, sizeof(float *));
for(j = 0; j < l.side*l.side*l.n; ++j) probs[j] = (float *)calloc(l.classes, sizeof(float *));
--
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