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/tag.c | 302 +++++++++++++++++++++++++-------------------------
1 files changed, 151 insertions(+), 151 deletions(-)
diff --git a/lib/detecter_tools/darknet/tag.c b/lib/detecter_tools/darknet/tag.c
index 0d5787a..d7e1349 100644
--- a/lib/detecter_tools/darknet/tag.c
+++ b/lib/detecter_tools/darknet/tag.c
@@ -1,151 +1,151 @@
-#include "network.h"
-#include "utils.h"
-#include "parser.h"
-
-void train_tag(char *cfgfile, char *weightfile, int clear)
-{
- 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);
- }
- if (clear) {
- *net.seen = 0;
- *net.cur_iteration = 0;
- }
- printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
- int imgs = 1024;
- list* plist = get_paths("tag/train.list");
- char **paths = (char **)list_to_array(plist);
- printf("%d\n", plist->size);
- int N = plist->size;
- clock_t time;
- pthread_t load_thread;
- data train;
- data buffer;
-
- load_args args = {0};
- args.w = net.w;
- args.h = net.h;
-
- args.min = net.w;
- args.max = net.max_crop;
- args.size = net.w;
-
- args.paths = paths;
- args.classes = net.outputs;
- args.n = imgs;
- args.m = N;
- args.d = &buffer;
- args.type = TAG_DATA;
-
- args.angle = net.angle;
- args.exposure = net.exposure;
- args.saturation = net.saturation;
- args.hue = net.hue;
-
- fprintf(stderr, "%d classes\n", net.outputs);
-
- load_thread = load_data_in_thread(args);
- int epoch = (*net.seen)/N;
- while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
- time=clock();
- pthread_join(load_thread, 0);
- train = buffer;
-
- load_thread = load_data_in_thread(args);
- 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, %.3f: %f, %f avg, %f rate, %lf seconds, %ld images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
- free_data(train);
- if(*net.seen/N > epoch){
- epoch = *net.seen/N;
- char buff[256];
- sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
- save_weights(net, buff);
- }
- if(get_current_batch(net)%100 == 0){
- char buff[256];
- sprintf(buff, "%s/%s.backup",backup_directory,base);
- save_weights(net, buff);
- }
- }
- char buff[256];
- sprintf(buff, "%s/%s.weights", backup_directory, base);
- save_weights(net, buff);
-
- pthread_join(load_thread, 0);
- free_data(buffer);
- free_network(net);
- free_ptrs((void**)paths, plist->size);
- free_list(plist);
- free(base);
-}
-
-void test_tag(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 = get_labels("data/tags.txt");
- clock_t time;
- int indexes[10];
- char buff[256];
- char *input = buff;
- int size = net.w;
- 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, 0, 0);
- image r = resize_min(im, size);
- resize_network(&net, r.w, r.h);
- printf("%d %d\n", r.w, r.h);
-
- float *X = r.data;
- time=clock();
- float *predictions = network_predict(net, X);
- top_predictions(net, 10, indexes);
- printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
- for(i = 0; i < 10; ++i){
- int index = indexes[i];
- printf("%.1f%%: %s\n", predictions[index]*100, names[index]);
- }
- if(r.data != im.data) free_image(r);
- free_image(im);
- if (filename) break;
- }
-}
-
-
-void run_tag(int argc, char **argv)
-{
- if(argc < 4){
- fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
- return;
- }
-
- int clear = find_arg(argc, argv, "-clear");
- char *cfg = argv[3];
- char *weights = (argc > 4) ? argv[4] : 0;
- char *filename = (argc > 5) ? argv[5] : 0;
- if(0==strcmp(argv[2], "train")) train_tag(cfg, weights, clear);
- else if(0==strcmp(argv[2], "test")) test_tag(cfg, weights, filename);
-}
+#include "network.h"
+#include "utils.h"
+#include "parser.h"
+
+void train_tag(char *cfgfile, char *weightfile, int clear)
+{
+ 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);
+ }
+ if (clear) {
+ *net.seen = 0;
+ *net.cur_iteration = 0;
+ }
+ printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
+ int imgs = 1024;
+ list* plist = get_paths("tag/train.list");
+ char **paths = (char **)list_to_array(plist);
+ printf("%d\n", plist->size);
+ int N = plist->size;
+ clock_t time;
+ pthread_t load_thread;
+ data train;
+ data buffer;
+
+ load_args args = {0};
+ args.w = net.w;
+ args.h = net.h;
+
+ args.min = net.w;
+ args.max = net.max_crop;
+ args.size = net.w;
+
+ args.paths = paths;
+ args.classes = net.outputs;
+ args.n = imgs;
+ args.m = N;
+ args.d = &buffer;
+ args.type = TAG_DATA;
+
+ args.angle = net.angle;
+ args.exposure = net.exposure;
+ args.saturation = net.saturation;
+ args.hue = net.hue;
+
+ fprintf(stderr, "%d classes\n", net.outputs);
+
+ load_thread = load_data_in_thread(args);
+ int epoch = (*net.seen)/N;
+ while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
+ time=clock();
+ pthread_join(load_thread, 0);
+ train = buffer;
+
+ load_thread = load_data_in_thread(args);
+ 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, %.3f: %f, %f avg, %f rate, %lf seconds, %ld images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
+ free_data(train);
+ if(*net.seen/N > epoch){
+ epoch = *net.seen/N;
+ char buff[256];
+ sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
+ save_weights(net, buff);
+ }
+ if(get_current_batch(net)%100 == 0){
+ char buff[256];
+ sprintf(buff, "%s/%s.backup",backup_directory,base);
+ save_weights(net, buff);
+ }
+ }
+ char buff[256];
+ sprintf(buff, "%s/%s.weights", backup_directory, base);
+ save_weights(net, buff);
+
+ pthread_join(load_thread, 0);
+ free_data(buffer);
+ free_network(net);
+ free_ptrs((void**)paths, plist->size);
+ free_list(plist);
+ free(base);
+}
+
+void test_tag(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 = get_labels("data/tags.txt");
+ clock_t time;
+ int indexes[10];
+ char buff[256];
+ char *input = buff;
+ int size = net.w;
+ 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, 0, 0);
+ image r = resize_min(im, size);
+ resize_network(&net, r.w, r.h);
+ printf("%d %d\n", r.w, r.h);
+
+ float *X = r.data;
+ time=clock();
+ float *predictions = network_predict(net, X);
+ top_predictions(net, 10, indexes);
+ printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
+ for(i = 0; i < 10; ++i){
+ int index = indexes[i];
+ printf("%.1f%%: %s\n", predictions[index]*100, names[index]);
+ }
+ if(r.data != im.data) free_image(r);
+ free_image(im);
+ if (filename) break;
+ }
+}
+
+
+void run_tag(int argc, char **argv)
+{
+ if(argc < 4){
+ fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
+ return;
+ }
+
+ int clear = find_arg(argc, argv, "-clear");
+ char *cfg = argv[3];
+ char *weights = (argc > 4) ? argv[4] : 0;
+ char *filename = (argc > 5) ? argv[5] : 0;
+ if(0==strcmp(argv[2], "train")) train_tag(cfg, weights, clear);
+ else if(0==strcmp(argv[2], "test")) test_tag(cfg, weights, filename);
+}
--
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