新增ocr训练代码

train/keras-train/trainbatch.py

@@ -15,7 +15,7 @@ train_loader = torch.utils.data.DataLoader(
 
 testSize = 64
 test_loader = torch.utils.data.DataLoader(
-    train_dataset, batch_size=testSize,
+    test_dataset, batch_size=testSize,
     shuffle=True, sampler=sampler,
     num_workers=int(workers),
     collate_fn=dataset.alignCollate(imgH=imgH, imgW=imgW, keep_ratio=keep_ratio))

train/pytorch-train/crnn_main.py

@@ -20,8 +20,8 @@ import models.crnn as crnn
 #alphabet += u''.join(list(set(newChars) - set(alphabet)))
 
 parser = argparse.ArgumentParser()
-parser.add_argument('--trainroot', help='path to dataset',default='../trainval/data')
-parser.add_argument('--valroot', help='path to dataset',default='../trainval/data')
+parser.add_argument('--trainroot', help='path to dataset',default='../data/lmdb/train')
+parser.add_argument('--valroot', help='path to dataset',default='../data/lmdb/val')
 parser.add_argument('--workers', type=int, help='number of data loading workers', default=4)
 parser.add_argument('--batchSize', type=int, default=128, help='input batch size')
 parser.add_argument('--imgH', type=int, default=32, help='the height of the input image to network')