From 168af40fe9a3cc81c6ee16b3e81f154780c36bdb Mon Sep 17 00:00:00 2001
From: Scheaven <xuepengqiang>
Date: 星期四, 03 六月 2021 15:03:27 +0800
Subject: [PATCH] up new v4
---
lib/detecter_tools/darknet/dice.c | 234 +++++++++++++++++++++++++++++-----------------------------
1 files changed, 117 insertions(+), 117 deletions(-)
diff --git a/lib/detecter_tools/darknet/dice.c b/lib/detecter_tools/darknet/dice.c
index 2dd3c0e..8a0393a 100644
--- a/lib/detecter_tools/darknet/dice.c
+++ b/lib/detecter_tools/darknet/dice.c
@@ -1,117 +1,117 @@
-#include "network.h"
-#include "utils.h"
-#include "parser.h"
-
-char *dice_labels[] = {"face1","face2","face3","face4","face5","face6"};
-
-void train_dice(char *cfgfile, char *weightfile)
-{
- srand(time(0));
- float avg_loss = -1;
- char *base = basecfg(cfgfile);
- char* backup_directory = "backup/";
- printf("%s\n", base);
- network net = parse_network_cfg(cfgfile);
- if(weightfile){
- load_weights(&net, weightfile);
- }
- printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
- int imgs = 1024;
- int i = *net.seen/imgs;
- char **labels = dice_labels;
- list *plist = get_paths("data/dice/dice.train.list");
- char **paths = (char **)list_to_array(plist);
- printf("%d\n", plist->size);
- clock_t time;
- while(1){
- ++i;
- time=clock();
- data train = load_data_old(paths, imgs, plist->size, labels, 6, net.w, net.h);
- printf("Loaded: %lf seconds\n", sec(clock()-time));
-
- time=clock();
- float loss = train_network(net, train);
- if(avg_loss == -1) avg_loss = loss;
- avg_loss = avg_loss*.9 + loss*.1;
- printf("%d: %f, %f avg, %lf seconds, %ld images\n", i, loss, avg_loss, sec(clock()-time), *net.seen);
- free_data(train);
- if((i % 100) == 0) net.learning_rate *= .1;
- if(i%100==0){
- char buff[256];
- sprintf(buff, "%s/%s_%d.weights",backup_directory,base, i);
- save_weights(net, buff);
- }
- }
-}
-
-void validate_dice(char *filename, char *weightfile)
-{
- network net = parse_network_cfg(filename);
- if(weightfile){
- load_weights(&net, weightfile);
- }
- srand(time(0));
-
- char **labels = dice_labels;
- list *plist = get_paths("data/dice/dice.val.list");
-
- char **paths = (char **)list_to_array(plist);
- int m = plist->size;
- free_list(plist);
-
- data val = load_data_old(paths, m, 0, labels, 6, net.w, net.h);
- float *acc = network_accuracies(net, val, 2);
- printf("Validation Accuracy: %f, %d images\n", acc[0], m);
- free_data(val);
-}
-
-void test_dice(char *cfgfile, char *weightfile, char *filename)
-{
- network net = parse_network_cfg(cfgfile);
- if(weightfile){
- load_weights(&net, weightfile);
- }
- set_batch_network(&net, 1);
- srand(2222222);
- int i = 0;
- char **names = dice_labels;
- char buff[256];
- char *input = buff;
- int indexes[6];
- while(1){
- if(filename){
- strncpy(input, filename, 256);
- }else{
- printf("Enter Image Path: ");
- fflush(stdout);
- input = fgets(input, 256, stdin);
- if(!input) return;
- strtok(input, "\n");
- }
- image im = load_image_color(input, net.w, net.h);
- float *X = im.data;
- float *predictions = network_predict(net, X);
- top_predictions(net, 6, indexes);
- for(i = 0; i < 6; ++i){
- int index = indexes[i];
- printf("%s: %f\n", names[index], predictions[index]);
- }
- free_image(im);
- if (filename) break;
- }
-}
-
-void run_dice(int argc, char **argv)
-{
- if(argc < 4){
- fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
- return;
- }
-
- char *cfg = argv[3];
- char *weights = (argc > 4) ? argv[4] : 0;
- char *filename = (argc > 5) ? argv[5]: 0;
- if(0==strcmp(argv[2], "test")) test_dice(cfg, weights, filename);
- else if(0==strcmp(argv[2], "train")) train_dice(cfg, weights);
- else if(0==strcmp(argv[2], "valid")) validate_dice(cfg, weights);
-}
+#include "network.h"
+#include "utils.h"
+#include "parser.h"
+
+char *dice_labels[] = {"face1","face2","face3","face4","face5","face6"};
+
+void train_dice(char *cfgfile, char *weightfile)
+{
+ srand(time(0));
+ float avg_loss = -1;
+ char *base = basecfg(cfgfile);
+ char* backup_directory = "backup/";
+ printf("%s\n", base);
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
+ int imgs = 1024;
+ int i = *net.seen/imgs;
+ char **labels = dice_labels;
+ list *plist = get_paths("data/dice/dice.train.list");
+ char **paths = (char **)list_to_array(plist);
+ printf("%d\n", plist->size);
+ clock_t time;
+ while(1){
+ ++i;
+ time=clock();
+ data train = load_data_old(paths, imgs, plist->size, labels, 6, net.w, net.h);
+ printf("Loaded: %lf seconds\n", sec(clock()-time));
+
+ time=clock();
+ float loss = train_network(net, train);
+ if(avg_loss == -1) avg_loss = loss;
+ avg_loss = avg_loss*.9 + loss*.1;
+ printf("%d: %f, %f avg, %lf seconds, %ld images\n", i, loss, avg_loss, sec(clock()-time), *net.seen);
+ free_data(train);
+ if((i % 100) == 0) net.learning_rate *= .1;
+ if(i%100==0){
+ char buff[256];
+ sprintf(buff, "%s/%s_%d.weights",backup_directory,base, i);
+ save_weights(net, buff);
+ }
+ }
+}
+
+void validate_dice(char *filename, char *weightfile)
+{
+ network net = parse_network_cfg(filename);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ srand(time(0));
+
+ char **labels = dice_labels;
+ list *plist = get_paths("data/dice/dice.val.list");
+
+ char **paths = (char **)list_to_array(plist);
+ int m = plist->size;
+ free_list(plist);
+
+ data val = load_data_old(paths, m, 0, labels, 6, net.w, net.h);
+ float *acc = network_accuracies(net, val, 2);
+ printf("Validation Accuracy: %f, %d images\n", acc[0], m);
+ free_data(val);
+}
+
+void test_dice(char *cfgfile, char *weightfile, char *filename)
+{
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ set_batch_network(&net, 1);
+ srand(2222222);
+ int i = 0;
+ char **names = dice_labels;
+ char buff[256];
+ char *input = buff;
+ int indexes[6];
+ while(1){
+ if(filename){
+ strncpy(input, filename, 256);
+ }else{
+ printf("Enter Image Path: ");
+ fflush(stdout);
+ input = fgets(input, 256, stdin);
+ if(!input) return;
+ strtok(input, "\n");
+ }
+ image im = load_image_color(input, net.w, net.h);
+ float *X = im.data;
+ float *predictions = network_predict(net, X);
+ top_predictions(net, 6, indexes);
+ for(i = 0; i < 6; ++i){
+ int index = indexes[i];
+ printf("%s: %f\n", names[index], predictions[index]);
+ }
+ free_image(im);
+ if (filename) break;
+ }
+}
+
+void run_dice(int argc, char **argv)
+{
+ if(argc < 4){
+ fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
+ return;
+ }
+
+ char *cfg = argv[3];
+ char *weights = (argc > 4) ? argv[4] : 0;
+ char *filename = (argc > 5) ? argv[5]: 0;
+ if(0==strcmp(argv[2], "test")) test_dice(cfg, weights, filename);
+ else if(0==strcmp(argv[2], "train")) train_dice(cfg, weights);
+ else if(0==strcmp(argv[2], "valid")) validate_dice(cfg, weights);
+}
--
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