mirror of
https://github.com/pjreddie/darknet.git
synced 2023-08-10 21:13:14 +03:00
idk man
This commit is contained in:
parent
c53e03348c
commit
fed6d6e31d
8
Makefile
8
Makefile
@ -1,5 +1,5 @@
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GPU=1
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OPENCV=1
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GPU=0
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OPENCV=0
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DEBUG=0
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ARCH= --gpu-architecture=compute_20 --gpu-code=compute_20
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@ -12,7 +12,7 @@ CC=gcc
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NVCC=nvcc
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OPTS=-Ofast
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LDFLAGS= -lm -pthread -lstdc++
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COMMON= -I/usr/local/cuda/include/
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COMMON=
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CFLAGS=-Wall -Wfatal-errors
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ifeq ($(DEBUG), 1)
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@ -29,7 +29,7 @@ COMMON+= `pkg-config --cflags opencv`
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endif
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ifeq ($(GPU), 1)
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COMMON+= -DGPU
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COMMON+= -DGPU -I/usr/local/cuda/include/
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CFLAGS+= -DGPU
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LDFLAGS+= -L/usr/local/cuda/lib64 -lcuda -lcudart -lcublas -lcurand
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endif
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@ -1,5 +1,5 @@
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[net]
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batch=256
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batch=128
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subdivisions=1
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height=256
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width=256
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@ -8,10 +8,10 @@ momentum=0.9
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decay=0.0005
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learning_rate=0.01
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policy=step
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scale=.1
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step=100000
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max_batches=400000
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policy=sigmoid
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gamma=.00002
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step=400000
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max_batches=800000
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[crop]
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crop_height=224
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@ -206,4 +206,5 @@ coords=4
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rescore=0
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joint=0
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objectness=1
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background=0
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10
src/box.c
10
src/box.c
@ -2,6 +2,16 @@
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#include <stdio.h>
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#include <math.h>
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box float_to_box(float *f)
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{
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box b;
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b.x = f[0];
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b.y = f[1];
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b.w = f[2];
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b.h = f[3];
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return b;
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}
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dbox derivative(box a, box b)
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{
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dbox d;
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@ -9,6 +9,7 @@ typedef struct{
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float dx, dy, dw, dh;
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} dbox;
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box float_to_box(float *f);
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float box_iou(box a, box b);
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float box_rmse(box a, box b);
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dbox diou(box a, box b);
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@ -241,7 +241,8 @@ void BattleRoyaleWithCheese(char *filename, char *weightfile)
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srand(time(0));
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set_batch_network(&net, 1);
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list *plist = get_paths("data/compare.sort.list");
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//list *plist = get_paths("data/compare.sort.list");
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list *plist = get_paths("data/compare.cat.list");
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//list *plist = get_paths("data/compare.val.old");
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char **paths = (char **)list_to_array(plist);
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int N = plist->size;
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@ -256,15 +257,16 @@ void BattleRoyaleWithCheese(char *filename, char *weightfile)
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}
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int round;
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clock_t time=clock();
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for(round = 1; round <= 40; ++round){
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for(round = 1; round <= 500; ++round){
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clock_t round_time=clock();
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printf("Round: %d\n", round);
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qsort(boxes, N, sizeof(sortable_bbox), elo_comparator);
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sorta_shuffle(boxes, N, sizeof(sortable_bbox), 10);
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shuffle(boxes, N, sizeof(sortable_bbox));
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for(i = 0; i < N/2; ++i){
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bbox_fight(boxes+i*2, boxes+i*2+1);
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}
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if(round >= 4){
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if(round >= 4 && 0){
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qsort(boxes, N, sizeof(sortable_bbox), elo_comparator);
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if(round == 4){
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N = N/2;
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@ -275,9 +277,11 @@ void BattleRoyaleWithCheese(char *filename, char *weightfile)
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printf("Round: %f secs, %d remaining\n", sec(clock()-round_time), N);
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}
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qsort(boxes, N, sizeof(sortable_bbox), elo_comparator);
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FILE *outfp = fopen("results/battle.log", "w");
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for(i = 0; i < N; ++i){
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printf("%s %f\n", boxes[i].filename, boxes[i].elo);
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fprintf(outfp, "%s %f\n", boxes[i].filename, boxes[i].elo);
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}
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fclose(outfp);
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printf("Tournament in %d compares, %f secs\n", total_compares, sec(clock()-time));
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}
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@ -60,6 +60,11 @@ typedef struct {
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float beta;
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float kappa;
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float coord_scale;
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float object_scale;
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float noobject_scale;
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float class_scale;
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int dontload;
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float probability;
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12
src/parser.c
12
src/parser.c
@ -182,10 +182,14 @@ region_layer parse_region(list *options, size_params params)
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int num = option_find_int(options, "num", 1);
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int side = option_find_int(options, "side", 7);
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region_layer layer = make_region_layer(params.batch, params.inputs, num, side, classes, coords, rescore);
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int softmax = option_find_int(options, "softmax", 0);
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int sqrt = option_find_int(options, "sqrt", 0);
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layer.softmax = softmax;
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layer.sqrt = sqrt;
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layer.softmax = option_find_int(options, "softmax", 0);
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layer.sqrt = option_find_int(options, "sqrt", 0);
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layer.coord_scale = option_find_float(options, "coord_scale", 1);
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layer.object_scale = option_find_float(options, "object_scale", 1);
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layer.noobject_scale = option_find_float(options, "noobject_scale", 1);
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layer.class_scale = option_find_float(options, "class_scale", 1);
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return layer;
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}
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@ -44,15 +44,20 @@ void forward_region_layer(const region_layer l, network_state state)
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int locations = l.side*l.side;
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int i,j;
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memcpy(l.output, state.input, l.outputs*l.batch*sizeof(float));
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for(i = 0; i < l.batch*locations; ++i){
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int index = i*((1+l.coords)*l.n + l.classes);
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if(l.softmax){
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activate_array(l.output + index, l.n*(1+l.coords), LOGISTIC);
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int offset = l.n*(1+l.coords);
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softmax_array(l.output + index + offset, l.classes,
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l.output + index + offset);
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int b;
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if (l.softmax){
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for(b = 0; b < l.batch; ++b){
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int index = b*l.inputs;
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for (i = 0; i < locations; ++i) {
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int offset = i*l.classes;
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softmax_array(l.output + index + offset, l.classes,
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l.output + index + offset);
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}
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int offset = locations*l.classes;
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activate_array(l.output + index + offset, locations*l.n*(1+l.coords), LOGISTIC);
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}
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}
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if(state.train){
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float avg_iou = 0;
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float avg_cat = 0;
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@ -62,94 +67,91 @@ void forward_region_layer(const region_layer l, network_state state)
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*(l.cost) = 0;
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int size = l.inputs * l.batch;
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memset(l.delta, 0, size * sizeof(float));
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for (i = 0; i < l.batch*locations; ++i) {
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int index = i*((1+l.coords)*l.n + l.classes);
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for(j = 0; j < l.n; ++j){
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int prob_index = index + j*(1 + l.coords);
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l.delta[prob_index] = (1./l.n)*(0-l.output[prob_index]);
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if(l.softmax){
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l.delta[prob_index] = 1./(l.n*l.side)*(0-l.output[prob_index]);
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}
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*(l.cost) += (1./l.n)*pow(l.output[prob_index], 2);
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//printf("%f\n", l.output[prob_index]);
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avg_anyobj += l.output[prob_index];
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}
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int truth_index = i*(1 + l.coords + l.classes);
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int best_index = -1;
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float best_iou = 0;
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float best_rmse = 4;
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int bg = !state.truth[truth_index];
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if(bg) {
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continue;
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}
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int class_index = index + l.n*(1+l.coords);
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for(j = 0; j < l.classes; ++j) {
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l.delta[class_index+j] = state.truth[truth_index+1+j] - l.output[class_index+j];
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*(l.cost) += pow(state.truth[truth_index+1+j] - l.output[class_index+j], 2);
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if(state.truth[truth_index + 1 + j]) avg_cat += l.output[class_index+j];
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}
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truth_index += l.classes + 1;
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box truth = {state.truth[truth_index+0], state.truth[truth_index+1], state.truth[truth_index+2], state.truth[truth_index+3]};
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truth.x /= l.side;
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truth.y /= l.side;
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for(j = 0; j < l.n; ++j){
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int out_index = index + j*(1+l.coords);
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box out = {l.output[out_index+1], l.output[out_index+2], l.output[out_index+3], l.output[out_index+4]};
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out.x /= l.side;
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out.y /= l.side;
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if (l.sqrt){
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out.w = out.w*out.w;
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out.h = out.h*out.h;
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for (b = 0; b < l.batch; ++b){
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int index = b*l.inputs;
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for (i = 0; i < locations; ++i) {
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int truth_index = (b*locations + i)*(1+l.coords+l.classes);
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int is_obj = state.truth[truth_index];
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for (j = 0; j < l.n; ++j) {
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int p_index = index + locations*l.classes + i*l.n + j;
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l.delta[p_index] = l.noobject_scale*(0 - l.output[p_index]);
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*(l.cost) += l.noobject_scale*pow(l.output[p_index], 2);
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avg_anyobj += l.output[p_index];
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}
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float iou = box_iou(out, truth);
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float rmse = box_rmse(out, truth);
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if(best_iou > 0 || iou > 0){
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if(iou > best_iou){
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best_iou = iou;
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best_index = j;
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int best_index = -1;
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float best_iou = 0;
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float best_rmse = 4;
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if (!is_obj) continue;
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int class_index = index + i*l.classes;
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for(j = 0; j < l.classes; ++j) {
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l.delta[class_index+j] = l.class_scale * (state.truth[truth_index+1+j] - l.output[class_index+j]);
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*(l.cost) += l.class_scale * pow(state.truth[truth_index+1+j] - l.output[class_index+j], 2);
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if(state.truth[truth_index + 1 + j]) avg_cat += l.output[class_index+j];
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}
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box truth = float_to_box(state.truth + truth_index + 1 + l.classes);
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truth.x /= l.side;
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truth.y /= l.side;
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for(j = 0; j < l.n; ++j){
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int box_index = index + locations*(l.classes + l.n) + (i*l.n + j) * l.coords;
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box out = float_to_box(l.output + box_index);
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out.x /= l.side;
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out.y /= l.side;
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if (l.sqrt){
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out.w = out.w*out.w;
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out.h = out.h*out.h;
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}
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}else{
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if(rmse < best_rmse){
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best_rmse = rmse;
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best_index = j;
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float iou = box_iou(out, truth);
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float rmse = box_rmse(out, truth);
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if(best_iou > 0 || iou > 0){
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if(iou > best_iou){
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best_iou = iou;
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best_index = j;
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}
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}else{
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if(rmse < best_rmse){
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best_rmse = rmse;
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best_index = j;
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}
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}
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}
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}
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//printf("%d", best_index);
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int in_index = index + best_index*(1+l.coords);
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*(l.cost) -= pow(l.output[in_index], 2);
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*(l.cost) += pow(1-l.output[in_index], 2);
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avg_obj += l.output[in_index];
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l.delta[in_index+0] = (1.-l.output[in_index]);
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if(l.softmax){
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l.delta[in_index+0] = 5*(1.-l.output[in_index]);
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}
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//printf("%f\n", l.output[in_index]);
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int p_index = index + locations*l.classes + i*l.n + best_index;
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*(l.cost) -= l.noobject_scale * pow(l.output[p_index], 2);
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*(l.cost) += l.object_scale * pow(1-l.output[p_index], 2);
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avg_obj += l.output[p_index];
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l.delta[p_index+0] = l.object_scale * (1.-l.output[p_index]);
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l.delta[in_index+1] = 5*(state.truth[truth_index+0] - l.output[in_index+1]);
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l.delta[in_index+2] = 5*(state.truth[truth_index+1] - l.output[in_index+2]);
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if(l.sqrt){
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l.delta[in_index+3] = 5*(sqrt(state.truth[truth_index+2]) - l.output[in_index+3]);
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l.delta[in_index+4] = 5*(sqrt(state.truth[truth_index+3]) - l.output[in_index+4]);
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}else{
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l.delta[in_index+3] = 5*(state.truth[truth_index+2] - l.output[in_index+3]);
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l.delta[in_index+4] = 5*(state.truth[truth_index+3] - l.output[in_index+4]);
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}
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if(l.rescore){
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l.delta[p_index+0] = l.object_scale * (best_iou - l.output[p_index]);
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}
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*(l.cost) += pow(1-best_iou, 2);
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avg_iou += best_iou;
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++count;
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int box_index = index + locations*(l.classes + l.n) + (i*l.n + best_index) * l.coords;
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int tbox_index = truth_index + 1 + l.classes;
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l.delta[box_index+0] = l.coord_scale*(state.truth[tbox_index + 0] - l.output[box_index + 0]);
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l.delta[box_index+1] = l.coord_scale*(state.truth[tbox_index + 1] - l.output[box_index + 1]);
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l.delta[box_index+2] = l.coord_scale*(state.truth[tbox_index + 2] - l.output[box_index + 2]);
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l.delta[box_index+3] = l.coord_scale*(state.truth[tbox_index + 3] - l.output[box_index + 3]);
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if(l.sqrt){
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l.delta[box_index+2] = l.coord_scale*(sqrt(state.truth[tbox_index + 2]) - l.output[box_index + 2]);
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l.delta[box_index+3] = l.coord_scale*(sqrt(state.truth[tbox_index + 3]) - l.output[box_index + 3]);
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}
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*(l.cost) += pow(1-best_iou, 2);
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avg_iou += best_iou;
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++count;
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}
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if(l.softmax){
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gradient_array(l.output + index, l.n*(1+l.coords), LOGISTIC, l.delta + index);
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gradient_array(l.output + index + locations*l.classes, locations*l.n*(1+l.coords),
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LOGISTIC, l.delta + index + locations*l.classes);
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}
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}
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printf("Avg IOU: %f, Avg Cat Pred: %f, Avg Obj: %f, Avg Any: %f, count: %d\n", avg_iou/count, avg_cat/count, avg_obj/count, avg_anyobj/(l.batch*locations*l.n), count);
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printf("Region Avg IOU: %f, Avg Cat Pred: %f, Avg Obj: %f, Avg Any: %f, count: %d\n", avg_iou/count, avg_cat/count, avg_obj/count, avg_anyobj/(l.batch*locations*l.n), count);
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}
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}
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@ -279,7 +279,7 @@ void stbiw__write_hdr_scanline(FILE *f, int width, int comp, unsigned char *scra
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{
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unsigned char scanlineheader[4] = { 2, 2, 0, 0 };
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unsigned char rgbe[4];
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float linear[3];
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float linear[3] = {0};
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int x;
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scanlineheader[2] = (width&0xff00)>>8;
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@ -77,7 +77,7 @@ void train_swag(char *cfgfile, char *weightfile)
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int classes = l.classes;
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list *plist = get_paths(train_images);
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int N = plist->size;
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//int N = plist->size;
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char **paths = (char **)list_to_array(plist);
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load_args args = {0};
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