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/compare.c | 704 +++++++++++++++++++++++++++++-----------------------------
1 files changed, 352 insertions(+), 352 deletions(-)
diff --git a/lib/detecter_tools/darknet/compare.c b/lib/detecter_tools/darknet/compare.c
index 0e13193..62edabe 100644
--- a/lib/detecter_tools/darknet/compare.c
+++ b/lib/detecter_tools/darknet/compare.c
@@ -1,352 +1,352 @@
-#include <stdio.h>
-
-#include "network.h"
-#include "detection_layer.h"
-#include "cost_layer.h"
-#include "utils.h"
-#include "parser.h"
-#include "box.h"
-
-void train_compare(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;
- list *plist = get_paths("data/compare.train.list");
- char **paths = (char **)list_to_array(plist);
- int N = plist->size;
- printf("%d\n", N);
- clock_t time;
- pthread_t load_thread;
- data train;
- data buffer;
-
- load_args args = {0};
- args.w = net.w;
- args.h = net.h;
- args.paths = paths;
- args.classes = 20;
- args.n = imgs;
- args.m = N;
- args.d = &buffer;
- args.type = COMPARE_DATA;
-
- load_thread = load_data_in_thread(args);
- int epoch = *net.seen/N;
- int i = 0;
- while(1){
- ++i;
- 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("%.3f: %f, %f avg, %lf seconds, %ld images\n", (float)*net.seen/N, loss, avg_loss, sec(clock()-time), *net.seen);
- free_data(train);
- if(i%100 == 0){
- char buff[256];
- sprintf(buff, "%s/%s_%d_minor_%d.weights",backup_directory,base, epoch, i);
- save_weights(net, buff);
- }
- if(*net.seen/N > epoch){
- epoch = *net.seen/N;
- i = 0;
- char buff[256];
- sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
- save_weights(net, buff);
- if(epoch%22 == 0) net.learning_rate *= .1;
- }
- }
- pthread_join(load_thread, 0);
- free_data(buffer);
- free_network(net);
- free_ptrs((void**)paths, plist->size);
- free_list(plist);
- free(base);
-}
-
-void validate_compare(char *filename, char *weightfile)
-{
- int i = 0;
- network net = parse_network_cfg(filename);
- if(weightfile){
- load_weights(&net, weightfile);
- }
- srand(time(0));
-
- list *plist = get_paths("data/compare.val.list");
- //list *plist = get_paths("data/compare.val.old");
- char **paths = (char **)list_to_array(plist);
- int N = plist->size/2;
- free_list(plist);
-
- clock_t time;
- int correct = 0;
- int total = 0;
- int splits = 10;
- int num = (i+1)*N/splits - i*N/splits;
-
- data val, buffer;
-
- load_args args = {0};
- args.w = net.w;
- args.h = net.h;
- args.paths = paths;
- args.classes = 20;
- args.n = num;
- args.m = 0;
- args.d = &buffer;
- args.type = COMPARE_DATA;
-
- pthread_t load_thread = load_data_in_thread(args);
- for(i = 1; i <= splits; ++i){
- time=clock();
-
- pthread_join(load_thread, 0);
- val = buffer;
-
- num = (i+1)*N/splits - i*N/splits;
- char **part = paths+(i*N/splits);
- if(i != splits){
- args.paths = part;
- load_thread = load_data_in_thread(args);
- }
- printf("Loaded: %d images in %lf seconds\n", val.X.rows, sec(clock()-time));
-
- time=clock();
- matrix pred = network_predict_data(net, val);
- int j,k;
- for(j = 0; j < val.y.rows; ++j){
- for(k = 0; k < 20; ++k){
- if(val.y.vals[j][k*2] != val.y.vals[j][k*2+1]){
- ++total;
- if((val.y.vals[j][k*2] < val.y.vals[j][k*2+1]) == (pred.vals[j][k*2] < pred.vals[j][k*2+1])){
- ++correct;
- }
- }
- }
- }
- free_matrix(pred);
- printf("%d: Acc: %f, %lf seconds, %d images\n", i, (float)correct/total, sec(clock()-time), val.X.rows);
- free_data(val);
- }
-}
-
-typedef struct {
- network net;
- char *filename;
- int class_id;
- int classes;
- float elo;
- float *elos;
-} sortable_bbox;
-
-int total_compares = 0;
-int current_class_id = 0;
-
-int elo_comparator(const void*a, const void *b)
-{
- sortable_bbox box1 = *(sortable_bbox*)a;
- sortable_bbox box2 = *(sortable_bbox*)b;
- if(box1.elos[current_class_id] == box2.elos[current_class_id]) return 0;
- if(box1.elos[current_class_id] > box2.elos[current_class_id]) return -1;
- return 1;
-}
-
-int bbox_comparator(const void *a, const void *b)
-{
- ++total_compares;
- sortable_bbox box1 = *(sortable_bbox*)a;
- sortable_bbox box2 = *(sortable_bbox*)b;
- network net = box1.net;
- int class_id = box1.class_id;
-
- image im1 = load_image_color(box1.filename, net.w, net.h);
- image im2 = load_image_color(box2.filename, net.w, net.h);
- float* X = (float*)xcalloc(net.w * net.h * net.c, sizeof(float));
- memcpy(X, im1.data, im1.w*im1.h*im1.c*sizeof(float));
- memcpy(X+im1.w*im1.h*im1.c, im2.data, im2.w*im2.h*im2.c*sizeof(float));
- float *predictions = network_predict(net, X);
-
- free_image(im1);
- free_image(im2);
- free(X);
- if (predictions[class_id*2] > predictions[class_id*2+1]){
- return 1;
- }
- return -1;
-}
-
-void bbox_update(sortable_bbox *a, sortable_bbox *b, int class_id, int result)
-{
- int k = 32;
- float EA = 1./(1+pow(10, (b->elos[class_id] - a->elos[class_id])/400.));
- float EB = 1./(1+pow(10, (a->elos[class_id] - b->elos[class_id])/400.));
- float SA = result ? 1 : 0;
- float SB = result ? 0 : 1;
- a->elos[class_id] += k*(SA - EA);
- b->elos[class_id] += k*(SB - EB);
-}
-
-void bbox_fight(network net, sortable_bbox *a, sortable_bbox *b, int classes, int class_id)
-{
- image im1 = load_image_color(a->filename, net.w, net.h);
- image im2 = load_image_color(b->filename, net.w, net.h);
- float* X = (float*)xcalloc(net.w * net.h * net.c, sizeof(float));
- memcpy(X, im1.data, im1.w*im1.h*im1.c*sizeof(float));
- memcpy(X+im1.w*im1.h*im1.c, im2.data, im2.w*im2.h*im2.c*sizeof(float));
- float *predictions = network_predict(net, X);
- ++total_compares;
-
- int i;
- for(i = 0; i < classes; ++i){
- if(class_id < 0 || class_id == i){
- int result = predictions[i*2] > predictions[i*2+1];
- bbox_update(a, b, i, result);
- }
- }
-
- free_image(im1);
- free_image(im2);
- free(X);
-}
-
-void SortMaster3000(char *filename, char *weightfile)
-{
- int i = 0;
- network net = parse_network_cfg(filename);
- if(weightfile){
- load_weights(&net, weightfile);
- }
- srand(time(0));
- set_batch_network(&net, 1);
-
- list *plist = get_paths("data/compare.sort.list");
- //list *plist = get_paths("data/compare.val.old");
- char **paths = (char **)list_to_array(plist);
- int N = plist->size;
- free_list(plist);
- sortable_bbox* boxes = (sortable_bbox*)xcalloc(N, sizeof(sortable_bbox));
- printf("Sorting %d boxes...\n", N);
- for(i = 0; i < N; ++i){
- boxes[i].filename = paths[i];
- boxes[i].net = net;
- boxes[i].class_id = 7;
- boxes[i].elo = 1500;
- }
- clock_t time=clock();
- qsort(boxes, N, sizeof(sortable_bbox), bbox_comparator);
- for(i = 0; i < N; ++i){
- printf("%s\n", boxes[i].filename);
- }
- printf("Sorted in %d compares, %f secs\n", total_compares, sec(clock()-time));
-}
-
-void BattleRoyaleWithCheese(char *filename, char *weightfile)
-{
- int classes = 20;
- int i,j;
- network net = parse_network_cfg(filename);
- if(weightfile){
- load_weights(&net, weightfile);
- }
- srand(time(0));
- set_batch_network(&net, 1);
-
- list *plist = get_paths("data/compare.sort.list");
- //list *plist = get_paths("data/compare.small.list");
- //list *plist = get_paths("data/compare.cat.list");
- //list *plist = get_paths("data/compare.val.old");
- char **paths = (char **)list_to_array(plist);
- int N = plist->size;
- int total = N;
- free_list(plist);
- sortable_bbox* boxes = (sortable_bbox*)xcalloc(N, sizeof(sortable_bbox));
- printf("Battling %d boxes...\n", N);
- for(i = 0; i < N; ++i){
- boxes[i].filename = paths[i];
- boxes[i].net = net;
- boxes[i].classes = classes;
- boxes[i].elos = (float*)xcalloc(classes, sizeof(float));
- for(j = 0; j < classes; ++j){
- boxes[i].elos[j] = 1500;
- }
- }
- int round;
- clock_t time=clock();
- for(round = 1; round <= 4; ++round){
- clock_t round_time=clock();
- printf("Round: %d\n", round);
- shuffle(boxes, N, sizeof(sortable_bbox));
- for(i = 0; i < N/2; ++i){
- bbox_fight(net, boxes+i*2, boxes+i*2+1, classes, -1);
- }
- printf("Round: %f secs, %d remaining\n", sec(clock()-round_time), N);
- }
-
- int class_id;
-
- for (class_id = 0; class_id < classes; ++class_id){
-
- N = total;
- current_class_id = class_id;
- qsort(boxes, N, sizeof(sortable_bbox), elo_comparator);
- N /= 2;
-
- for(round = 1; round <= 100; ++round){
- clock_t round_time=clock();
- printf("Round: %d\n", round);
-
- sorta_shuffle(boxes, N, sizeof(sortable_bbox), 10);
- for(i = 0; i < N/2; ++i){
- bbox_fight(net, boxes+i*2, boxes+i*2+1, classes, class_id);
- }
- qsort(boxes, N, sizeof(sortable_bbox), elo_comparator);
- if(round <= 20) N = (N*9/10)/2*2;
-
- printf("Round: %f secs, %d remaining\n", sec(clock()-round_time), N);
- }
- char buff[256];
- sprintf(buff, "results/battle_%d.log", class_id);
- FILE *outfp = fopen(buff, "w");
- for(i = 0; i < N; ++i){
- fprintf(outfp, "%s %f\n", boxes[i].filename, boxes[i].elos[class_id]);
- }
- fclose(outfp);
- }
- printf("Tournament in %d compares, %f secs\n", total_compares, sec(clock()-time));
-}
-
-void run_compare(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], "train")) train_compare(cfg, weights);
- else if(0==strcmp(argv[2], "valid")) validate_compare(cfg, weights);
- else if(0==strcmp(argv[2], "sort")) SortMaster3000(cfg, weights);
- else if(0==strcmp(argv[2], "battle")) BattleRoyaleWithCheese(cfg, weights);
- /*
- else if(0==strcmp(argv[2], "train")) train_coco(cfg, weights);
- else if(0==strcmp(argv[2], "extract")) extract_boxes(cfg, weights);
- else if(0==strcmp(argv[2], "valid")) validate_recall(cfg, weights);
- */
-}
+#include <stdio.h>
+
+#include "network.h"
+#include "detection_layer.h"
+#include "cost_layer.h"
+#include "utils.h"
+#include "parser.h"
+#include "box.h"
+
+void train_compare(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;
+ list *plist = get_paths("data/compare.train.list");
+ char **paths = (char **)list_to_array(plist);
+ int N = plist->size;
+ printf("%d\n", N);
+ clock_t time;
+ pthread_t load_thread;
+ data train;
+ data buffer;
+
+ load_args args = {0};
+ args.w = net.w;
+ args.h = net.h;
+ args.paths = paths;
+ args.classes = 20;
+ args.n = imgs;
+ args.m = N;
+ args.d = &buffer;
+ args.type = COMPARE_DATA;
+
+ load_thread = load_data_in_thread(args);
+ int epoch = *net.seen/N;
+ int i = 0;
+ while(1){
+ ++i;
+ 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("%.3f: %f, %f avg, %lf seconds, %ld images\n", (float)*net.seen/N, loss, avg_loss, sec(clock()-time), *net.seen);
+ free_data(train);
+ if(i%100 == 0){
+ char buff[256];
+ sprintf(buff, "%s/%s_%d_minor_%d.weights",backup_directory,base, epoch, i);
+ save_weights(net, buff);
+ }
+ if(*net.seen/N > epoch){
+ epoch = *net.seen/N;
+ i = 0;
+ char buff[256];
+ sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
+ save_weights(net, buff);
+ if(epoch%22 == 0) net.learning_rate *= .1;
+ }
+ }
+ pthread_join(load_thread, 0);
+ free_data(buffer);
+ free_network(net);
+ free_ptrs((void**)paths, plist->size);
+ free_list(plist);
+ free(base);
+}
+
+void validate_compare(char *filename, char *weightfile)
+{
+ int i = 0;
+ network net = parse_network_cfg(filename);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ srand(time(0));
+
+ list *plist = get_paths("data/compare.val.list");
+ //list *plist = get_paths("data/compare.val.old");
+ char **paths = (char **)list_to_array(plist);
+ int N = plist->size/2;
+ free_list(plist);
+
+ clock_t time;
+ int correct = 0;
+ int total = 0;
+ int splits = 10;
+ int num = (i+1)*N/splits - i*N/splits;
+
+ data val, buffer;
+
+ load_args args = {0};
+ args.w = net.w;
+ args.h = net.h;
+ args.paths = paths;
+ args.classes = 20;
+ args.n = num;
+ args.m = 0;
+ args.d = &buffer;
+ args.type = COMPARE_DATA;
+
+ pthread_t load_thread = load_data_in_thread(args);
+ for(i = 1; i <= splits; ++i){
+ time=clock();
+
+ pthread_join(load_thread, 0);
+ val = buffer;
+
+ num = (i+1)*N/splits - i*N/splits;
+ char **part = paths+(i*N/splits);
+ if(i != splits){
+ args.paths = part;
+ load_thread = load_data_in_thread(args);
+ }
+ printf("Loaded: %d images in %lf seconds\n", val.X.rows, sec(clock()-time));
+
+ time=clock();
+ matrix pred = network_predict_data(net, val);
+ int j,k;
+ for(j = 0; j < val.y.rows; ++j){
+ for(k = 0; k < 20; ++k){
+ if(val.y.vals[j][k*2] != val.y.vals[j][k*2+1]){
+ ++total;
+ if((val.y.vals[j][k*2] < val.y.vals[j][k*2+1]) == (pred.vals[j][k*2] < pred.vals[j][k*2+1])){
+ ++correct;
+ }
+ }
+ }
+ }
+ free_matrix(pred);
+ printf("%d: Acc: %f, %lf seconds, %d images\n", i, (float)correct/total, sec(clock()-time), val.X.rows);
+ free_data(val);
+ }
+}
+
+typedef struct {
+ network net;
+ char *filename;
+ int class_id;
+ int classes;
+ float elo;
+ float *elos;
+} sortable_bbox;
+
+int total_compares = 0;
+int current_class_id = 0;
+
+int elo_comparator(const void*a, const void *b)
+{
+ sortable_bbox box1 = *(sortable_bbox*)a;
+ sortable_bbox box2 = *(sortable_bbox*)b;
+ if(box1.elos[current_class_id] == box2.elos[current_class_id]) return 0;
+ if(box1.elos[current_class_id] > box2.elos[current_class_id]) return -1;
+ return 1;
+}
+
+int bbox_comparator(const void *a, const void *b)
+{
+ ++total_compares;
+ sortable_bbox box1 = *(sortable_bbox*)a;
+ sortable_bbox box2 = *(sortable_bbox*)b;
+ network net = box1.net;
+ int class_id = box1.class_id;
+
+ image im1 = load_image_color(box1.filename, net.w, net.h);
+ image im2 = load_image_color(box2.filename, net.w, net.h);
+ float* X = (float*)xcalloc(net.w * net.h * net.c, sizeof(float));
+ memcpy(X, im1.data, im1.w*im1.h*im1.c*sizeof(float));
+ memcpy(X+im1.w*im1.h*im1.c, im2.data, im2.w*im2.h*im2.c*sizeof(float));
+ float *predictions = network_predict(net, X);
+
+ free_image(im1);
+ free_image(im2);
+ free(X);
+ if (predictions[class_id*2] > predictions[class_id*2+1]){
+ return 1;
+ }
+ return -1;
+}
+
+void bbox_update(sortable_bbox *a, sortable_bbox *b, int class_id, int result)
+{
+ int k = 32;
+ float EA = 1./(1+pow(10, (b->elos[class_id] - a->elos[class_id])/400.));
+ float EB = 1./(1+pow(10, (a->elos[class_id] - b->elos[class_id])/400.));
+ float SA = result ? 1 : 0;
+ float SB = result ? 0 : 1;
+ a->elos[class_id] += k*(SA - EA);
+ b->elos[class_id] += k*(SB - EB);
+}
+
+void bbox_fight(network net, sortable_bbox *a, sortable_bbox *b, int classes, int class_id)
+{
+ image im1 = load_image_color(a->filename, net.w, net.h);
+ image im2 = load_image_color(b->filename, net.w, net.h);
+ float* X = (float*)xcalloc(net.w * net.h * net.c, sizeof(float));
+ memcpy(X, im1.data, im1.w*im1.h*im1.c*sizeof(float));
+ memcpy(X+im1.w*im1.h*im1.c, im2.data, im2.w*im2.h*im2.c*sizeof(float));
+ float *predictions = network_predict(net, X);
+ ++total_compares;
+
+ int i;
+ for(i = 0; i < classes; ++i){
+ if(class_id < 0 || class_id == i){
+ int result = predictions[i*2] > predictions[i*2+1];
+ bbox_update(a, b, i, result);
+ }
+ }
+
+ free_image(im1);
+ free_image(im2);
+ free(X);
+}
+
+void SortMaster3000(char *filename, char *weightfile)
+{
+ int i = 0;
+ network net = parse_network_cfg(filename);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ srand(time(0));
+ set_batch_network(&net, 1);
+
+ list *plist = get_paths("data/compare.sort.list");
+ //list *plist = get_paths("data/compare.val.old");
+ char **paths = (char **)list_to_array(plist);
+ int N = plist->size;
+ free_list(plist);
+ sortable_bbox* boxes = (sortable_bbox*)xcalloc(N, sizeof(sortable_bbox));
+ printf("Sorting %d boxes...\n", N);
+ for(i = 0; i < N; ++i){
+ boxes[i].filename = paths[i];
+ boxes[i].net = net;
+ boxes[i].class_id = 7;
+ boxes[i].elo = 1500;
+ }
+ clock_t time=clock();
+ qsort(boxes, N, sizeof(sortable_bbox), bbox_comparator);
+ for(i = 0; i < N; ++i){
+ printf("%s\n", boxes[i].filename);
+ }
+ printf("Sorted in %d compares, %f secs\n", total_compares, sec(clock()-time));
+}
+
+void BattleRoyaleWithCheese(char *filename, char *weightfile)
+{
+ int classes = 20;
+ int i,j;
+ network net = parse_network_cfg(filename);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ srand(time(0));
+ set_batch_network(&net, 1);
+
+ list *plist = get_paths("data/compare.sort.list");
+ //list *plist = get_paths("data/compare.small.list");
+ //list *plist = get_paths("data/compare.cat.list");
+ //list *plist = get_paths("data/compare.val.old");
+ char **paths = (char **)list_to_array(plist);
+ int N = plist->size;
+ int total = N;
+ free_list(plist);
+ sortable_bbox* boxes = (sortable_bbox*)xcalloc(N, sizeof(sortable_bbox));
+ printf("Battling %d boxes...\n", N);
+ for(i = 0; i < N; ++i){
+ boxes[i].filename = paths[i];
+ boxes[i].net = net;
+ boxes[i].classes = classes;
+ boxes[i].elos = (float*)xcalloc(classes, sizeof(float));
+ for(j = 0; j < classes; ++j){
+ boxes[i].elos[j] = 1500;
+ }
+ }
+ int round;
+ clock_t time=clock();
+ for(round = 1; round <= 4; ++round){
+ clock_t round_time=clock();
+ printf("Round: %d\n", round);
+ shuffle(boxes, N, sizeof(sortable_bbox));
+ for(i = 0; i < N/2; ++i){
+ bbox_fight(net, boxes+i*2, boxes+i*2+1, classes, -1);
+ }
+ printf("Round: %f secs, %d remaining\n", sec(clock()-round_time), N);
+ }
+
+ int class_id;
+
+ for (class_id = 0; class_id < classes; ++class_id){
+
+ N = total;
+ current_class_id = class_id;
+ qsort(boxes, N, sizeof(sortable_bbox), elo_comparator);
+ N /= 2;
+
+ for(round = 1; round <= 100; ++round){
+ clock_t round_time=clock();
+ printf("Round: %d\n", round);
+
+ sorta_shuffle(boxes, N, sizeof(sortable_bbox), 10);
+ for(i = 0; i < N/2; ++i){
+ bbox_fight(net, boxes+i*2, boxes+i*2+1, classes, class_id);
+ }
+ qsort(boxes, N, sizeof(sortable_bbox), elo_comparator);
+ if(round <= 20) N = (N*9/10)/2*2;
+
+ printf("Round: %f secs, %d remaining\n", sec(clock()-round_time), N);
+ }
+ char buff[256];
+ sprintf(buff, "results/battle_%d.log", class_id);
+ FILE *outfp = fopen(buff, "w");
+ for(i = 0; i < N; ++i){
+ fprintf(outfp, "%s %f\n", boxes[i].filename, boxes[i].elos[class_id]);
+ }
+ fclose(outfp);
+ }
+ printf("Tournament in %d compares, %f secs\n", total_compares, sec(clock()-time));
+}
+
+void run_compare(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], "train")) train_compare(cfg, weights);
+ else if(0==strcmp(argv[2], "valid")) validate_compare(cfg, weights);
+ else if(0==strcmp(argv[2], "sort")) SortMaster3000(cfg, weights);
+ else if(0==strcmp(argv[2], "battle")) BattleRoyaleWithCheese(cfg, weights);
+ /*
+ else if(0==strcmp(argv[2], "train")) train_coco(cfg, weights);
+ else if(0==strcmp(argv[2], "extract")) extract_boxes(cfg, weights);
+ else if(0==strcmp(argv[2], "valid")) validate_recall(cfg, weights);
+ */
+}
--
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