From cfc5fedbb6df2471493b1ec162d0024485618211 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Tue, 10 Jul 2018 20:29:15 +0000
Subject: [PATCH] Just used spaces for indents instead of Tabs
---
src/yolo_layer.c | 140 +++++++++++++++++++++++-----------------------
1 files changed, 70 insertions(+), 70 deletions(-)
diff --git a/src/yolo_layer.c b/src/yolo_layer.c
index f79bc41..f0bc073 100644
--- a/src/yolo_layer.c
+++ b/src/yolo_layer.c
@@ -38,8 +38,8 @@
l.bias_updates = calloc(n*2, sizeof(float));
l.outputs = h*w*n*(classes + 4 + 1);
l.inputs = l.outputs;
- l.max_boxes = max_boxes;
- l.truths = l.max_boxes*(4 + 1); // 90*(4 + 1);
+ l.max_boxes = max_boxes;
+ l.truths = l.max_boxes*(4 + 1); // 90*(4 + 1);
l.delta = calloc(batch*l.outputs, sizeof(float));
l.output = calloc(batch*l.outputs, sizeof(float));
for(i = 0; i < total*2; ++i){
@@ -117,33 +117,33 @@
if(avg_cat) *avg_cat += output[index + stride*class_id];
return;
}
- // Focal loss
- 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
+ // Focal loss
+ 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
- int ti = index + stride*class_id;
- float pt = output[ti] + 0.000000000000001F;
- // 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
+ int ti = index + stride*class_id;
+ float pt = output[ti] + 0.000000000000001F;
+ // 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]);
+ for (n = 0; n < classes; ++n) {
+ delta[index + stride*n] = (((n == class_id) ? 1 : 0) - output[index + stride*n]);
- delta[index + stride*n] *= alpha*grad;
+ delta[index + stride*n] *= alpha*grad;
- if (n == class_id) *avg_cat += output[index + stride*n];
- }
- }
- else {
- // default
- for (n = 0; n < classes; ++n) {
- delta[index + stride*n] = ((n == class_id) ? 1 : 0) - output[index + stride*n];
- if (n == class_id && avg_cat) *avg_cat += output[index + stride*n];
- }
- }
+ if (n == class_id) *avg_cat += output[index + stride*n];
+ }
+ }
+ else {
+ // default
+ for (n = 0; n < classes; ++n) {
+ delta[index + stride*n] = ((n == class_id) ? 1 : 0) - output[index + stride*n];
+ if (n == class_id && avg_cat) *avg_cat += output[index + stride*n];
+ }
+ }
}
static int entry_index(layer l, int batch, int location, int entry)
@@ -155,12 +155,12 @@
static box float_to_box_stride(float *f, int stride)
{
- box b = { 0 };
- b.x = f[0];
- b.y = f[1 * stride];
- b.w = f[2 * stride];
- b.h = f[3 * stride];
- return b;
+ box b = { 0 };
+ b.x = f[0];
+ b.y = f[1 * stride];
+ b.w = f[2 * stride];
+ b.h = f[3 * stride];
+ return b;
}
void forward_yolo_layer(const layer l, network_state state)
@@ -200,12 +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
- }
+ 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) {
@@ -234,8 +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
+ 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;
@@ -291,20 +291,20 @@
int i;
int new_w=0;
int new_h=0;
- if (letter) {
- if (((float)netw / w) < ((float)neth / h)) {
- new_w = netw;
- new_h = (h * netw) / w;
- }
- else {
- new_h = neth;
- new_w = (w * neth) / h;
- }
- }
- else {
- new_w = netw;
- new_h = neth;
- }
+ if (letter) {
+ if (((float)netw / w) < ((float)neth / h)) {
+ new_w = netw;
+ new_h = (h * netw) / w;
+ }
+ else {
+ new_h = neth;
+ new_w = (w * neth) / h;
+ }
+ }
+ else {
+ new_w = netw;
+ new_h = neth;
+ }
for (i = 0; i < n; ++i){
box b = dets[i].bbox;
b.x = (b.x - (netw - new_w)/2./netw) / ((float)new_w/netw);
@@ -411,25 +411,25 @@
}
//cuda_pull_array(l.output_gpu, state.input, l.batch*l.inputs);
- float *in_cpu = calloc(l.batch*l.inputs, sizeof(float));
- cuda_pull_array(l.output_gpu, in_cpu, l.batch*l.inputs);
- float *truth_cpu = 0;
- if (state.truth) {
- int num_truth = l.batch*l.truths;
- truth_cpu = calloc(num_truth, sizeof(float));
- cuda_pull_array(state.truth, truth_cpu, num_truth);
- }
- network_state cpu_state = state;
- cpu_state.net = state.net;
- cpu_state.index = state.index;
- cpu_state.train = state.train;
- cpu_state.truth = truth_cpu;
- cpu_state.input = in_cpu;
- forward_yolo_layer(l, cpu_state);
+ float *in_cpu = calloc(l.batch*l.inputs, sizeof(float));
+ cuda_pull_array(l.output_gpu, in_cpu, l.batch*l.inputs);
+ float *truth_cpu = 0;
+ if (state.truth) {
+ int num_truth = l.batch*l.truths;
+ truth_cpu = calloc(num_truth, sizeof(float));
+ cuda_pull_array(state.truth, truth_cpu, num_truth);
+ }
+ network_state cpu_state = state;
+ cpu_state.net = state.net;
+ cpu_state.index = state.index;
+ cpu_state.train = state.train;
+ cpu_state.truth = truth_cpu;
+ cpu_state.input = in_cpu;
+ forward_yolo_layer(l, cpu_state);
//forward_yolo_layer(l, state);
cuda_push_array(l.delta_gpu, l.delta, l.batch*l.outputs);
- free(in_cpu);
- if (cpu_state.truth) free(cpu_state.truth);
+ free(in_cpu);
+ if (cpu_state.truth) free(cpu_state.truth);
}
void backward_yolo_layer_gpu(const layer l, network_state state)
--
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