| | |
| | | #include "network.h"
|
| | | #include "utils.h"
|
| | | #include "parser.h"
|
| | |
|
| | | void fix_data_captcha(data d, int mask)
|
| | | {
|
| | | matrix labels = d.y;
|
| | | int i, j;
|
| | | for(i = 0; i < d.y.rows; ++i){
|
| | | for(j = 0; j < d.y.cols; j += 2){
|
| | | if (mask){
|
| | | if(!labels.vals[i][j]){
|
| | | labels.vals[i][j] = SECRET_NUM;
|
| | | labels.vals[i][j+1] = SECRET_NUM;
|
| | | }else if(labels.vals[i][j+1]){
|
| | | labels.vals[i][j] = 0;
|
| | | }
|
| | | } else{
|
| | | if (labels.vals[i][j]) {
|
| | | labels.vals[i][j+1] = 0;
|
| | | } else {
|
| | | labels.vals[i][j+1] = 1;
|
| | | }
|
| | | }
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | void train_captcha(char *cfgfile, char *weightfile)
|
| | | {
|
| | | srand(time(0));
|
| | | float avg_loss = -1;
|
| | | char *base = basecfg(cfgfile);
|
| | | 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;
|
| | | int solved = 1;
|
| | | list *plist;
|
| | | char** labels = get_labels("data/captcha/reimgs.labels.list");
|
| | | if (solved){
|
| | | plist = get_paths("data/captcha/reimgs.solved.list");
|
| | | }else{
|
| | | plist = get_paths("data/captcha/reimgs.raw.list");
|
| | | }
|
| | | char **paths = (char **)list_to_array(plist);
|
| | | printf("%d\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.paths = paths;
|
| | | args.classes = 26;
|
| | | args.n = imgs;
|
| | | args.m = plist->size;
|
| | | args.labels = labels;
|
| | | args.d = &buffer;
|
| | | args.type = CLASSIFICATION_DATA;
|
| | |
|
| | | load_thread = load_data_in_thread(args);
|
| | | while(1){
|
| | | ++i;
|
| | | time=clock();
|
| | | pthread_join(load_thread, 0);
|
| | | train = buffer;
|
| | | fix_data_captcha(train, solved);
|
| | |
|
| | | /*
|
| | | image im = float_to_image(256, 256, 3, train.X.vals[114]);
|
| | | show_image(im, "training");
|
| | | cvWaitKey(0);
|
| | | */
|
| | |
|
| | | 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: %f, %f avg, %lf seconds, %ld images\n", i, loss, avg_loss, sec(clock()-time), *net.seen);
|
| | | free_data(train);
|
| | | if(i%100==0){
|
| | | char buff[256];
|
| | | sprintf(buff, "imagenet_backup/%s_%d.weights", base, i);
|
| | | save_weights(net, buff);
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | void test_captcha(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/captcha/reimgs.labels.list");
|
| | | char buff[256];
|
| | | char *input = buff;
|
| | | int indexes[26];
|
| | | 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, 26, indexes);
|
| | | //printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
|
| | | for(i = 0; i < 26; ++i){
|
| | | int index = indexes[i];
|
| | | if(i != 0) printf(", ");
|
| | | printf("%s %f", names[index], predictions[index]);
|
| | | }
|
| | | printf("\n");
|
| | | fflush(stdout);
|
| | | free_image(im);
|
| | | if (filename) break;
|
| | | }
|
| | | }
|
| | |
|
| | | void valid_captcha(char *cfgfile, char *weightfile, char *filename)
|
| | | {
|
| | | char** labels = get_labels("data/captcha/reimgs.labels.list");
|
| | | network net = parse_network_cfg(cfgfile);
|
| | | if(weightfile){
|
| | | load_weights(&net, weightfile);
|
| | | }
|
| | | list* plist = get_paths("data/captcha/reimgs.fg.list");
|
| | | char **paths = (char **)list_to_array(plist);
|
| | | int N = plist->size;
|
| | | int outputs = net.outputs;
|
| | |
|
| | | set_batch_network(&net, 1);
|
| | | srand(2222222);
|
| | | int i, j;
|
| | | for(i = 0; i < N; ++i){
|
| | | if (i%100 == 0) fprintf(stderr, "%d\n", i);
|
| | | image im = load_image_color(paths[i], net.w, net.h);
|
| | | float *X = im.data;
|
| | | float *predictions = network_predict(net, X);
|
| | | //printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
|
| | | int truth = -1;
|
| | | for(j = 0; j < 13; ++j){
|
| | | if (strstr(paths[i], labels[j])) truth = j;
|
| | | }
|
| | | if (truth == -1){
|
| | | fprintf(stderr, "bad: %s\n", paths[i]);
|
| | | return;
|
| | | }
|
| | | printf("%d, ", truth);
|
| | | for(j = 0; j < outputs; ++j){
|
| | | if (j != 0) printf(", ");
|
| | | printf("%f", predictions[j]);
|
| | | }
|
| | | printf("\n");
|
| | | fflush(stdout);
|
| | | free_image(im);
|
| | | if (filename) break;
|
| | | }
|
| | | }
|
| | |
|
| | | /*
|
| | | void train_captcha(char *cfgfile, char *weightfile)
|
| | | {
|
| | | float avg_loss = -1;
|
| | | srand(time(0));
|
| | | char *base = basecfg(cfgfile);
|
| | | 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;
|
| | | list *plist = get_paths("/data/captcha/train.auto5");
|
| | | char **paths = (char **)list_to_array(plist);
|
| | | printf("%d\n", plist->size);
|
| | | clock_t time;
|
| | | while(1){
|
| | | ++i;
|
| | | time=clock();
|
| | | data train = load_data_captcha(paths, imgs, plist->size, 10, 200, 60);
|
| | | translate_data_rows(train, -128);
|
| | | scale_data_rows(train, 1./128);
|
| | | printf("Loaded: %lf seconds\n", sec(clock()-time));
|
| | | time=clock();
|
| | | float loss = train_network(net, train);
|
| | | net.seen += imgs;
|
| | | if(avg_loss == -1) avg_loss = loss;
|
| | | avg_loss = avg_loss*.9 + loss*.1;
|
| | | printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), net.seen);
|
| | | free_data(train);
|
| | | if(i%10==0){
|
| | | char buff[256];
|
| | | sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i);
|
| | | save_weights(net, buff);
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | void decode_captcha(char *cfgfile, char *weightfile)
|
| | | {
|
| | | setbuf(stdout, NULL);
|
| | | srand(time(0));
|
| | | network net = parse_network_cfg(cfgfile);
|
| | | set_batch_network(&net, 1);
|
| | | if(weightfile){
|
| | | load_weights(&net, weightfile);
|
| | | }
|
| | | char filename[256];
|
| | | while(1){
|
| | | printf("Enter filename: ");
|
| | | fgets(filename, 256, stdin);
|
| | | strtok(filename, "\n");
|
| | | image im = load_image_color(filename, 300, 57);
|
| | | scale_image(im, 1./255.);
|
| | | float *X = im.data;
|
| | | float *predictions = network_predict(net, X);
|
| | | image out = float_to_image(300, 57, 1, predictions);
|
| | | show_image(out, "decoded");
|
| | | #ifdef OPENCV
|
| | | cvWaitKey(0);
|
| | | #endif
|
| | | free_image(im);
|
| | | }
|
| | | }
|
| | |
|
| | | void encode_captcha(char *cfgfile, char *weightfile)
|
| | | {
|
| | | float avg_loss = -1;
|
| | | srand(time(0));
|
| | | char *base = basecfg(cfgfile);
|
| | | 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;
|
| | | list *plist = get_paths("/data/captcha/encode.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_captcha_encode(paths, imgs, plist->size, 300, 57);
|
| | | scale_data_rows(train, 1./255);
|
| | | printf("Loaded: %lf seconds\n", sec(clock()-time));
|
| | | time=clock();
|
| | | float loss = train_network(net, train);
|
| | | net.seen += imgs;
|
| | | if(avg_loss == -1) avg_loss = loss;
|
| | | avg_loss = avg_loss*.9 + loss*.1;
|
| | | printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), net.seen);
|
| | | free_matrix(train.X);
|
| | | if(i%100==0){
|
| | | char buff[256];
|
| | | sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i);
|
| | | save_weights(net, buff);
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | void validate_captcha(char *cfgfile, char *weightfile)
|
| | | {
|
| | | srand(time(0));
|
| | | char *base = basecfg(cfgfile);
|
| | | printf("%s\n", base);
|
| | | network net = parse_network_cfg(cfgfile);
|
| | | if(weightfile){
|
| | | load_weights(&net, weightfile);
|
| | | }
|
| | | int numchars = 37;
|
| | | list *plist = get_paths("/data/captcha/solved.hard");
|
| | | char **paths = (char **)list_to_array(plist);
|
| | | int imgs = plist->size;
|
| | | data valid = load_data_captcha(paths, imgs, 0, 10, 200, 60);
|
| | | translate_data_rows(valid, -128);
|
| | | scale_data_rows(valid, 1./128);
|
| | | matrix pred = network_predict_data(net, valid);
|
| | | int i, k;
|
| | | int correct = 0;
|
| | | int total = 0;
|
| | | int accuracy = 0;
|
| | | for(i = 0; i < imgs; ++i){
|
| | | int allcorrect = 1;
|
| | | for(k = 0; k < 10; ++k){
|
| | | char truth = int_to_alphanum(max_index(valid.y.vals[i]+k*numchars, numchars));
|
| | | char prediction = int_to_alphanum(max_index(pred.vals[i]+k*numchars, numchars));
|
| | | if (truth != prediction) allcorrect=0;
|
| | | if (truth != '.' && truth == prediction) ++correct;
|
| | | if (truth != '.' || truth != prediction) ++total;
|
| | | }
|
| | | accuracy += allcorrect;
|
| | | }
|
| | | printf("Word Accuracy: %f, Char Accuracy %f\n", (float)accuracy/imgs, (float)correct/total);
|
| | | free_data(valid);
|
| | | }
|
| | |
|
| | | void test_captcha(char *cfgfile, char *weightfile)
|
| | | {
|
| | | setbuf(stdout, NULL);
|
| | | srand(time(0));
|
| | | //char *base = basecfg(cfgfile);
|
| | | //printf("%s\n", base);
|
| | | network net = parse_network_cfg(cfgfile);
|
| | | set_batch_network(&net, 1);
|
| | | if(weightfile){
|
| | | load_weights(&net, weightfile);
|
| | | }
|
| | | char filename[256];
|
| | | while(1){
|
| | | //printf("Enter filename: ");
|
| | | fgets(filename, 256, stdin);
|
| | | strtok(filename, "\n");
|
| | | image im = load_image_color(filename, 200, 60);
|
| | | translate_image(im, -128);
|
| | | scale_image(im, 1/128.);
|
| | | float *X = im.data;
|
| | | float *predictions = network_predict(net, X);
|
| | | print_letters(predictions, 10);
|
| | | free_image(im);
|
| | | }
|
| | | }
|
| | | */
|
| | | void run_captcha(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_captcha(cfg, weights);
|
| | | else if(0==strcmp(argv[2], "test")) test_captcha(cfg, weights, filename);
|
| | | else if(0==strcmp(argv[2], "valid")) valid_captcha(cfg, weights, filename);
|
| | | //if(0==strcmp(argv[2], "test")) test_captcha(cfg, weights);
|
| | | //else if(0==strcmp(argv[2], "encode")) encode_captcha(cfg, weights);
|
| | | //else if(0==strcmp(argv[2], "decode")) decode_captcha(cfg, weights);
|
| | | //else if(0==strcmp(argv[2], "valid")) validate_captcha(cfg, weights);
|
| | | }
|
| | | #include "network.h" |
| | | #include "utils.h" |
| | | #include "parser.h" |
| | | |
| | | void fix_data_captcha(data d, int mask) |
| | | { |
| | | matrix labels = d.y; |
| | | int i, j; |
| | | for(i = 0; i < d.y.rows; ++i){ |
| | | for(j = 0; j < d.y.cols; j += 2){ |
| | | if (mask){ |
| | | if(!labels.vals[i][j]){ |
| | | labels.vals[i][j] = SECRET_NUM; |
| | | labels.vals[i][j+1] = SECRET_NUM; |
| | | }else if(labels.vals[i][j+1]){ |
| | | labels.vals[i][j] = 0; |
| | | } |
| | | } else{ |
| | | if (labels.vals[i][j]) { |
| | | labels.vals[i][j+1] = 0; |
| | | } else { |
| | | labels.vals[i][j+1] = 1; |
| | | } |
| | | } |
| | | } |
| | | } |
| | | } |
| | | |
| | | void train_captcha(char *cfgfile, char *weightfile) |
| | | { |
| | | srand(time(0)); |
| | | float avg_loss = -1; |
| | | char *base = basecfg(cfgfile); |
| | | 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; |
| | | int solved = 1; |
| | | list *plist; |
| | | char** labels = get_labels("data/captcha/reimgs.labels.list"); |
| | | if (solved){ |
| | | plist = get_paths("data/captcha/reimgs.solved.list"); |
| | | }else{ |
| | | plist = get_paths("data/captcha/reimgs.raw.list"); |
| | | } |
| | | char **paths = (char **)list_to_array(plist); |
| | | printf("%d\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.paths = paths; |
| | | args.classes = 26; |
| | | args.n = imgs; |
| | | args.m = plist->size; |
| | | args.labels = labels; |
| | | args.d = &buffer; |
| | | args.type = CLASSIFICATION_DATA; |
| | | |
| | | load_thread = load_data_in_thread(args); |
| | | while(1){ |
| | | ++i; |
| | | time=clock(); |
| | | pthread_join(load_thread, 0); |
| | | train = buffer; |
| | | fix_data_captcha(train, solved); |
| | | |
| | | /* |
| | | image im = float_to_image(256, 256, 3, train.X.vals[114]); |
| | | show_image(im, "training"); |
| | | cvWaitKey(0); |
| | | */ |
| | | |
| | | 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: %f, %f avg, %lf seconds, %ld images\n", i, loss, avg_loss, sec(clock()-time), *net.seen); |
| | | free_data(train); |
| | | if(i%100==0){ |
| | | char buff[256]; |
| | | sprintf(buff, "imagenet_backup/%s_%d.weights", base, i); |
| | | save_weights(net, buff); |
| | | } |
| | | } |
| | | } |
| | | |
| | | void test_captcha(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/captcha/reimgs.labels.list"); |
| | | char buff[256]; |
| | | char *input = buff; |
| | | int indexes[26]; |
| | | 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, 26, indexes); |
| | | //printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time)); |
| | | for(i = 0; i < 26; ++i){ |
| | | int index = indexes[i]; |
| | | if(i != 0) printf(", "); |
| | | printf("%s %f", names[index], predictions[index]); |
| | | } |
| | | printf("\n"); |
| | | fflush(stdout); |
| | | free_image(im); |
| | | if (filename) break; |
| | | } |
| | | } |
| | | |
| | | void valid_captcha(char *cfgfile, char *weightfile, char *filename) |
| | | { |
| | | char** labels = get_labels("data/captcha/reimgs.labels.list"); |
| | | network net = parse_network_cfg(cfgfile); |
| | | if(weightfile){ |
| | | load_weights(&net, weightfile); |
| | | } |
| | | list* plist = get_paths("data/captcha/reimgs.fg.list"); |
| | | char **paths = (char **)list_to_array(plist); |
| | | int N = plist->size; |
| | | int outputs = net.outputs; |
| | | |
| | | set_batch_network(&net, 1); |
| | | srand(2222222); |
| | | int i, j; |
| | | for(i = 0; i < N; ++i){ |
| | | if (i%100 == 0) fprintf(stderr, "%d\n", i); |
| | | image im = load_image_color(paths[i], net.w, net.h); |
| | | float *X = im.data; |
| | | float *predictions = network_predict(net, X); |
| | | //printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time)); |
| | | int truth = -1; |
| | | for(j = 0; j < 13; ++j){ |
| | | if (strstr(paths[i], labels[j])) truth = j; |
| | | } |
| | | if (truth == -1){ |
| | | fprintf(stderr, "bad: %s\n", paths[i]); |
| | | return; |
| | | } |
| | | printf("%d, ", truth); |
| | | for(j = 0; j < outputs; ++j){ |
| | | if (j != 0) printf(", "); |
| | | printf("%f", predictions[j]); |
| | | } |
| | | printf("\n"); |
| | | fflush(stdout); |
| | | free_image(im); |
| | | if (filename) break; |
| | | } |
| | | } |
| | | |
| | | /* |
| | | void train_captcha(char *cfgfile, char *weightfile) |
| | | { |
| | | float avg_loss = -1; |
| | | srand(time(0)); |
| | | char *base = basecfg(cfgfile); |
| | | 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; |
| | | list *plist = get_paths("/data/captcha/train.auto5"); |
| | | char **paths = (char **)list_to_array(plist); |
| | | printf("%d\n", plist->size); |
| | | clock_t time; |
| | | while(1){ |
| | | ++i; |
| | | time=clock(); |
| | | data train = load_data_captcha(paths, imgs, plist->size, 10, 200, 60); |
| | | translate_data_rows(train, -128); |
| | | scale_data_rows(train, 1./128); |
| | | printf("Loaded: %lf seconds\n", sec(clock()-time)); |
| | | time=clock(); |
| | | float loss = train_network(net, train); |
| | | net.seen += imgs; |
| | | if(avg_loss == -1) avg_loss = loss; |
| | | avg_loss = avg_loss*.9 + loss*.1; |
| | | printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), net.seen); |
| | | free_data(train); |
| | | if(i%10==0){ |
| | | char buff[256]; |
| | | sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i); |
| | | save_weights(net, buff); |
| | | } |
| | | } |
| | | } |
| | | |
| | | void decode_captcha(char *cfgfile, char *weightfile) |
| | | { |
| | | setbuf(stdout, NULL); |
| | | srand(time(0)); |
| | | network net = parse_network_cfg(cfgfile); |
| | | set_batch_network(&net, 1); |
| | | if(weightfile){ |
| | | load_weights(&net, weightfile); |
| | | } |
| | | char filename[256]; |
| | | while(1){ |
| | | printf("Enter filename: "); |
| | | fgets(filename, 256, stdin); |
| | | strtok(filename, "\n"); |
| | | image im = load_image_color(filename, 300, 57); |
| | | scale_image(im, 1./255.); |
| | | float *X = im.data; |
| | | float *predictions = network_predict(net, X); |
| | | image out = float_to_image(300, 57, 1, predictions); |
| | | show_image(out, "decoded"); |
| | | #ifdef OPENCV |
| | | cvWaitKey(0); |
| | | #endif |
| | | free_image(im); |
| | | } |
| | | } |
| | | |
| | | void encode_captcha(char *cfgfile, char *weightfile) |
| | | { |
| | | float avg_loss = -1; |
| | | srand(time(0)); |
| | | char *base = basecfg(cfgfile); |
| | | 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; |
| | | list *plist = get_paths("/data/captcha/encode.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_captcha_encode(paths, imgs, plist->size, 300, 57); |
| | | scale_data_rows(train, 1./255); |
| | | printf("Loaded: %lf seconds\n", sec(clock()-time)); |
| | | time=clock(); |
| | | float loss = train_network(net, train); |
| | | net.seen += imgs; |
| | | if(avg_loss == -1) avg_loss = loss; |
| | | avg_loss = avg_loss*.9 + loss*.1; |
| | | printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), net.seen); |
| | | free_matrix(train.X); |
| | | if(i%100==0){ |
| | | char buff[256]; |
| | | sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i); |
| | | save_weights(net, buff); |
| | | } |
| | | } |
| | | } |
| | | |
| | | void validate_captcha(char *cfgfile, char *weightfile) |
| | | { |
| | | srand(time(0)); |
| | | char *base = basecfg(cfgfile); |
| | | printf("%s\n", base); |
| | | network net = parse_network_cfg(cfgfile); |
| | | if(weightfile){ |
| | | load_weights(&net, weightfile); |
| | | } |
| | | int numchars = 37; |
| | | list *plist = get_paths("/data/captcha/solved.hard"); |
| | | char **paths = (char **)list_to_array(plist); |
| | | int imgs = plist->size; |
| | | data valid = load_data_captcha(paths, imgs, 0, 10, 200, 60); |
| | | translate_data_rows(valid, -128); |
| | | scale_data_rows(valid, 1./128); |
| | | matrix pred = network_predict_data(net, valid); |
| | | int i, k; |
| | | int correct = 0; |
| | | int total = 0; |
| | | int accuracy = 0; |
| | | for(i = 0; i < imgs; ++i){ |
| | | int allcorrect = 1; |
| | | for(k = 0; k < 10; ++k){ |
| | | char truth = int_to_alphanum(max_index(valid.y.vals[i]+k*numchars, numchars)); |
| | | char prediction = int_to_alphanum(max_index(pred.vals[i]+k*numchars, numchars)); |
| | | if (truth != prediction) allcorrect=0; |
| | | if (truth != '.' && truth == prediction) ++correct; |
| | | if (truth != '.' || truth != prediction) ++total; |
| | | } |
| | | accuracy += allcorrect; |
| | | } |
| | | printf("Word Accuracy: %f, Char Accuracy %f\n", (float)accuracy/imgs, (float)correct/total); |
| | | free_data(valid); |
| | | } |
| | | |
| | | void test_captcha(char *cfgfile, char *weightfile) |
| | | { |
| | | setbuf(stdout, NULL); |
| | | srand(time(0)); |
| | | //char *base = basecfg(cfgfile); |
| | | //printf("%s\n", base); |
| | | network net = parse_network_cfg(cfgfile); |
| | | set_batch_network(&net, 1); |
| | | if(weightfile){ |
| | | load_weights(&net, weightfile); |
| | | } |
| | | char filename[256]; |
| | | while(1){ |
| | | //printf("Enter filename: "); |
| | | fgets(filename, 256, stdin); |
| | | strtok(filename, "\n"); |
| | | image im = load_image_color(filename, 200, 60); |
| | | translate_image(im, -128); |
| | | scale_image(im, 1/128.); |
| | | float *X = im.data; |
| | | float *predictions = network_predict(net, X); |
| | | print_letters(predictions, 10); |
| | | free_image(im); |
| | | } |
| | | } |
| | | */ |
| | | void run_captcha(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_captcha(cfg, weights); |
| | | else if(0==strcmp(argv[2], "test")) test_captcha(cfg, weights, filename); |
| | | else if(0==strcmp(argv[2], "valid")) valid_captcha(cfg, weights, filename); |
| | | //if(0==strcmp(argv[2], "test")) test_captcha(cfg, weights); |
| | | //else if(0==strcmp(argv[2], "encode")) encode_captcha(cfg, weights); |
| | | //else if(0==strcmp(argv[2], "decode")) decode_captcha(cfg, weights); |
| | | //else if(0==strcmp(argv[2], "valid")) validate_captcha(cfg, weights); |
| | | } |