From 1e9d1fcedf1a361bcdb384f15b5b14bdb526576d Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Sat, 30 Jun 2018 20:12:25 +0000
Subject: [PATCH] Fixed arch=compute_53,code=[sm_53,compute_53] for Jetson TX1
---
src/yolo_layer.c | 31 ++++++++++++++++++++-----------
1 files changed, 20 insertions(+), 11 deletions(-)
diff --git a/src/yolo_layer.c b/src/yolo_layer.c
index ad62426..f79bc41 100644
--- a/src/yolo_layer.c
+++ b/src/yolo_layer.c
@@ -55,7 +55,7 @@
l.delta_gpu = cuda_make_array(l.delta, batch*l.outputs);
#endif
- fprintf(stderr, "detection\n");
+ fprintf(stderr, "yolo\n");
srand(0);
return l;
@@ -112,7 +112,7 @@
void delta_yolo_class(float *output, float *delta, int index, int class_id, int classes, int stride, float *avg_cat, int focal_loss)
{
int n;
- if (delta[index]){
+ if (delta[index + stride*class_id]){
delta[index + stride*class_id] = 1 - output[index + stride*class_id];
if(avg_cat) *avg_cat += output[index + stride*class_id];
return;
@@ -121,12 +121,13 @@
if (focal_loss) {
// Focal Loss
float alpha = 0.5; // 0.25 or 0.5
- //float gamma = 2; // hardcoded in many places of the grad-formula
+ //float gamma = 2; // hardcoded in many places of the grad-formula
int ti = index + stride*class_id;
float pt = output[ti] + 0.000000000000001F;
- //float grad = -(1 - pt) * (2 * pt*logf(pt) + pt - 1); // http://blog.csdn.net/linmingan/article/details/77885832
- float grad = (1 - pt) * (2 * pt*logf(pt) + pt - 1); // https://github.com/unsky/focal-loss
+ // http://fooplot.com/#W3sidHlwZSI6MCwiZXEiOiItKDEteCkqKDIqeCpsb2coeCkreC0xKSIsImNvbG9yIjoiIzAwMDAwMCJ9LHsidHlwZSI6MTAwMH1d
+ float grad = -(1 - pt) * (2 * pt*logf(pt) + pt - 1); // http://blog.csdn.net/linmingan/article/details/77885832
+ //float grad = (1 - pt) * (2 * pt*logf(pt) + pt - 1); // https://github.com/unsky/focal-loss
for (n = 0; n < classes; ++n) {
delta[index + stride*n] = (((n == class_id) ? 1 : 0) - output[index + stride*n]);
@@ -199,6 +200,12 @@
int best_t = 0;
for(t = 0; t < l.max_boxes; ++t){
box truth = float_to_box_stride(state.truth + t*(4 + 1) + b*l.truths, 1);
+ int class_id = state.truth[t*(4 + 1) + b*l.truths + 4];
+ if (class_id >= l.classes) {
+ printf(" Warning: in txt-labels class_id=%d >= classes=%d in cfg-file. In txt-labels class_id should be [from 0 to %d] \n", class_id, l.classes, l.classes - 1);
+ getchar();
+ continue; // if label contains class_id more than number of classes in the cfg-file
+ }
if(!truth.x) break;
float iou = box_iou(pred, truth);
if (iou > best_iou) {
@@ -215,10 +222,10 @@
if (best_iou > l.truth_thresh) {
l.delta[obj_index] = 1 - l.output[obj_index];
- int class = state.truth[best_t*(4 + 1) + b*l.truths + 4];
- if (l.map) class = l.map[class];
+ int class_id = state.truth[best_t*(4 + 1) + b*l.truths + 4];
+ if (l.map) class_id = l.map[class_id];
int class_index = entry_index(l, b, n*l.w*l.h + j*l.w + i, 4 + 1);
- delta_yolo_class(l.output, l.delta, class_index, class, l.classes, l.w*l.h, 0, l.focal_loss);
+ delta_yolo_class(l.output, l.delta, class_index, class_id, l.classes, l.w*l.h, 0, l.focal_loss);
box truth = float_to_box_stride(state.truth + best_t*(4 + 1) + b*l.truths, 1);
delta_yolo_box(truth, l.output, l.biases, l.mask[n], box_index, i, j, l.w, l.h, state.net.w, state.net.h, l.delta, (2-truth.w*truth.h), l.w*l.h);
}
@@ -227,6 +234,8 @@
}
for(t = 0; t < l.max_boxes; ++t){
box truth = float_to_box_stride(state.truth + t*(4 + 1) + b*l.truths, 1);
+ int class_id = state.truth[t*(4 + 1) + b*l.truths + 4];
+ if (class_id >= l.classes) continue; // if label contains class_id more than number of classes in the cfg-file
if(!truth.x) break;
float best_iou = 0;
@@ -255,10 +264,10 @@
avg_obj += l.output[obj_index];
l.delta[obj_index] = 1 - l.output[obj_index];
- int class = state.truth[t*(4 + 1) + b*l.truths + 4];
- if (l.map) class = l.map[class];
+ int class_id = state.truth[t*(4 + 1) + b*l.truths + 4];
+ if (l.map) class_id = l.map[class_id];
int class_index = entry_index(l, b, mask_n*l.w*l.h + j*l.w + i, 4 + 1);
- delta_yolo_class(l.output, l.delta, class_index, class, l.classes, l.w*l.h, &avg_cat, l.focal_loss);
+ delta_yolo_class(l.output, l.delta, class_index, class_id, l.classes, l.w*l.h, &avg_cat, l.focal_loss);
++count;
++class_count;
--
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