| | |
| | | avg_loss = avg_loss*.9 + loss*.1; |
| | | |
| | | printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), i*imgs); |
| | | if((i-1)*imgs <= N && i*imgs > N){ |
| | | fprintf(stderr, "First stage done\n"); |
| | | net.learning_rate *= 10; |
| | | char buff[256]; |
| | | sprintf(buff, "%s/%s_first_stage.weights", backup_directory, base); |
| | | save_weights(net, buff); |
| | | } |
| | | |
| | | if((i-1)*imgs <= 80*N && i*imgs > N*80){ |
| | | fprintf(stderr, "Second stage done.\n"); |
| | | char buff[256]; |
| | | sprintf(buff, "%s/%s_second_stage.weights", backup_directory, base); |
| | | save_weights(net, buff); |
| | | } |
| | | if(i%1000==0){ |
| | | char buff[256]; |
| | | sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i); |
| | |
| | | set_batch_network(&net, 1); |
| | | srand(2222222); |
| | | clock_t time; |
| | | char input[256]; |
| | | char buff[256]; |
| | | char *input = buff; |
| | | while(1){ |
| | | if(filename){ |
| | | strncpy(input, filename, 256); |
| | | } else { |
| | | printf("Enter Image Path: "); |
| | | fflush(stdout); |
| | | fgets(input, 256, stdin); |
| | | input = fgets(input, 256, stdin); |
| | | if(!input) return; |
| | | strtok(input, "\n"); |
| | | } |
| | | image im = load_image_color(input,0,0); |