[Bug] Fix prepare icdar2013 dataset with lmdb flag

[hugotong6425]

Motivation

When I run

python tools/dataset_converters/prepare_dataset.py \
    icdar2013 \
    --task textrecog \
    --nproc 8 \
    --lmdb

with

# mmocr/dataset_zoo/icdar2013/textrecog.py

# This configuration prepares the ICDAR13 857 and 1015
# version, and uses ICDAR13 1015 version by default.
# You may uncomment the lines if you want to you the original version,
# which contains 1095 samples.
# You can check out the generated base config and use the 857
# version by using its corresponding config variables in your model.

data_root = 'data/icdar2013'
cache_path = 'data/cache'

train_preparer = dict(
    obtainer=dict(
        type='NaiveDataObtainer',
        cache_path=cache_path,
        files=[
            dict(
                url='https://rrc.cvc.uab.es/downloads/'
                'Challenge2_Training_Task3_Images_GT.zip',
                save_name='ic13_textrecog_train_img_gt.zip',
                md5='6f0dbc823645968030878df7543f40a4',
                content=['image'],
                mapping=[
                    # ['ic13_textrecog_train_img_gt/gt.txt',
                    # 'annotations/train.txt'],
                    ['ic13_textrecog_train_img_gt', 'textrecog_imgs/train']
                ]),
            dict(
                url='https://download.openmmlab.com/mmocr/data/1.x/recog/'
                'icdar_2013/train_labels.json',
                save_name='ic13_train_labels.json',
                md5='008fcd0056e72c4cf3064fb4d1fce81b',
                content=['annotation'],
                mapping=[['ic13_train_labels.json', 'textrecog_train.json']]),
        ]))

# Note that we offer two versions of test set annotations as follows.Please
# choose one of them to download and comment the other. By default, we use the
# second one.
# 1. The original official annotation, which contains 1095 test
# samples.

# Uncomment the test_preparer if you want to use the original 1095 version.

test_preparer = dict(
    obtainer=dict(
        type='NaiveDataObtainer',
        cache_path=cache_path,
        files=[
            dict(
                url='https://rrc.cvc.uab.es/downloads/'
                'Challenge2_Test_Task3_Images.zip',
                save_name='ic13_textrecog_test_img.zip',
                md5='3206778eebb3a5c5cc15c249010bf77f',
                split=['test'],
                content=['image'],
                mapping=[['ic13_textrecog_test_img',
                          'textrecog_imgs/test']]),
            dict(
                url='https://rrc.cvc.uab.es/downloads/'
                'Challenge2_Test_Task3_GT.txt',
                save_name='ic13_textrecog_test_gt.txt',
                md5='2634060ed8fe6e7a4a9b8d68785835a1',
                split=['test'],
                content=['annotation'],
                mapping=[[
                    'ic13_textrecog_test_gt.txt', 'annotations/test.txt'
                ]]),  # noqa
            # The 857 version further pruned words shorter than 3 characters.
            dict(
                url='https://download.openmmlab.com/mmocr/data/1.x/recog/'
                'icdar_2013/textrecog_test_857.json',
                save_name='textrecog_test_857.json',
                md5='3bed3985b0c51a989ad4006f6de8352b',
                split=['test'],
                content=['annotation'],
            ),
        ]),
    gatherer=dict(type='MonoGatherer', ann_name='test.txt'),
    parser=dict(
        type='ICDARTxtTextRecogAnnParser', separator=', ',
        format='img, text'),  # noqa
    packer=dict(type='TextRecogPacker'),
    dumper=dict(type='JsonDumper'),
)

I got an error

Traceback (most recent call last):
  File "tools/dataset_converters/prepare_dataset.py", line 153, in <module>
    main()
  File "tools/dataset_converters/prepare_dataset.py", line 147, in main
    cfg = force_lmdb(cfg)
  File "tools/dataset_converters/prepare_dataset.py", line 96, in force_lmdb
    raise ValueError(
ValueError: train split does not come with a dumper, so most likely the annotations are MMOCR-ready and do not need any adaptation, and it cannot be dumped in LMDB format.

Modification

Fix the above error.

Checklist

Before PR:

• [x] I have read and followed the workflow indicated in the CONTRIBUTING.md to create this PR.
• [x] Pre-commit or linting tools indicated in CONTRIBUTING.md are used to fix the potential lint issues.
• [ ] Bug fixes are covered by unit tests, the case that causes the bug should be added in the unit tests.
• [ ] New functionalities are covered by complete unit tests. If not, please add more unit test to ensure the correctness.
• [ ] The documentation has been modified accordingly, including docstring or example tutorials.

After PR:

• [x] If the modification has potential influence on downstream or other related projects, this PR should be tested with some of those projects.
• [x] CLA has been signed and all committers have signed the CLA in this PR.