X-Git-Url: https://www.fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=pysvrt.git;a=blobdiff_plain;f=cnn-svrt.py;h=d0704fff48c85fca80c5723c20cb369c0600a013;hp=ade87ceea78dba435a3f9982e2e55f1bb719357e;hb=4c77eebce3c3914a58c548c606d045efdae2284a;hpb=1ae0133746fd78a916ac540475c64a0e5fccd3e4 diff --git a/cnn-svrt.py b/cnn-svrt.py index ade87ce..d0704ff 100755 --- a/cnn-svrt.py +++ b/cnn-svrt.py @@ -85,6 +85,9 @@ parser.add_argument('--compress_vignettes', type = distutils.util.strtobool, default = 'True', help = 'Use lossless compression to reduce the memory footprint') +parser.add_argument('--save_test_mistakes', + type = distutils.util.strtobool, default = 'False') + parser.add_argument('--model', type = str, default = 'deepnet', help = 'What model to use') @@ -102,6 +105,10 @@ args = parser.parse_args() ###################################################################### log_file = open(args.log_file, 'a') +log_file.write('\n') +log_file.write('@@@@@@@@@@@@@@@@@@@ ' + time.ctime() + ' @@@@@@@@@@@@@@@@@@@\n') +log_file.write('\n') + pred_log_t = None last_tag_t = time.time() @@ -338,7 +345,7 @@ class DeepNet3(nn.Module): ###################################################################### -def nb_errors(model, data_set): +def nb_errors(model, data_set, mistake_filename_pattern = None): ne = 0 for b in range(0, data_set.nb_batches): input, target = data_set.get_batch(b) @@ -348,7 +355,14 @@ def nb_errors(model, data_set): for i in range(0, data_set.batch_size): if wta_prediction[i] != target[i]: ne = ne + 1 - + if mistake_filename_pattern is not None: + img = input[i].clone() + img.sub_(img.min()) + img.div_(img.max()) + k = b * data_set.batch_size + i + filename = mistake_filename_pattern.format(k, target[i]) + torchvision.utils.save_image(img, filename) + print(Fore.RED + 'Wrote ' + filename + Style.RESET_ALL) return ne ###################################################################### @@ -448,8 +462,6 @@ if args.nb_train_samples%args.batch_size > 0 or args.nb_test_samples%args.batch_ print('The number of samples must be a multiple of the batch size.') raise -log_string('############### start ###############') - if args.compress_vignettes: log_string('using_compressed_vignettes') VignetteSet = svrtset.CompressedVignetteSet @@ -550,7 +562,8 @@ for problem_number in map(int, args.problems.split(',')): args.nb_test_samples, args.batch_size, cuda = torch.cuda.is_available()) - nb_test_errors = nb_errors(model, test_set) + nb_test_errors = nb_errors(model, test_set, + mistake_filename_pattern = 'mistake_{:06d}_{:d}.png') log_string('test_error {:d} {:.02f}% {:d} {:d}'.format( problem_number,