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19 | 19 | parser.add_argument('--valroot', required=True, help='path to dataset')
|
20 | 20 | parser.add_argument('--workers', type=int, help='number of data loading workers', default=2)
|
21 | 21 | parser.add_argument('--batchSize', type=int, default=64, help='input batch size')
|
22 |
| -parser.add_argument('--imgH', type=int, default=64, help='the height / width of the input image to network') |
23 |
| -parser.add_argument('--nh', type=int, default=100, help='size of the lstm hidden state') |
| 22 | +parser.add_argument('--imgH', type=int, default=32, help='the height / width of the input image to network') |
| 23 | +parser.add_argument('--nh', type=int, default=256, help='size of the lstm hidden state') |
24 | 24 | parser.add_argument('--niter', type=int, default=25, help='number of epochs to train for')
|
25 |
| -parser.add_argument('--lr', type=float, default=1, help='learning rate for Critic, default=0.00005') |
| 25 | +parser.add_argument('--lr', type=float, default=0.01, help='learning rate for Critic, default=0.00005') |
26 | 26 | parser.add_argument('--beta1', type=float, default=0.5, help='beta1 for adam. default=0.5')
|
27 | 27 | parser.add_argument('--cuda', action='store_true', help='enables cuda')
|
28 | 28 | parser.add_argument('--ngpu', type=int, default=1, help='number of GPUs to use')
|
29 | 29 | parser.add_argument('--crnn', default='', help="path to crnn (to continue training)")
|
30 | 30 | parser.add_argument('--alphabet', type=str, default='0123456789abcdefghijklmnopqrstuvwxyz')
|
31 |
| -parser.add_argument('--Diters', type=int, default=5, help='number of D iters per each G iter') |
32 | 31 | parser.add_argument('--experiment', default=None, help='Where to store samples and models')
|
33 | 32 | parser.add_argument('--displayInterval', type=int, default=500, help='Interval to be displayed')
|
34 | 33 | parser.add_argument('--n_test_disp', type=int, default=10, help='Number of samples to display when test')
|
|
42 | 41 | print(opt)
|
43 | 42 |
|
44 | 43 | if opt.experiment is None:
|
45 |
| - opt.experiment = 'samples' |
| 44 | + opt.experiment = 'expr' |
46 | 45 | os.system('mkdir {0}'.format(opt.experiment))
|
47 | 46 |
|
48 | 47 | opt.manualSeed = random.randint(1, 10000) # fix seed
|
@@ -160,7 +159,7 @@ def val(net, dataset, criterion, max_iter=100):
|
160 | 159 | if pred == target.lower():
|
161 | 160 | n_correct += 1
|
162 | 161 |
|
163 |
| - raw_preds = converter.decode(preds.data, preds_size.data, raw=True) |
| 162 | + raw_preds = converter.decode(preds.data, preds_size.data, raw=True)[:opt.n_test_disp] |
164 | 163 | for raw_pred, pred, gt in zip(raw_preds, sim_preds, cpu_texts):
|
165 | 164 | print('%-20s => %-20s, gt: %-20s' % (raw_pred, pred, gt))
|
166 | 165 |
|
|
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