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# Copyright (c) OpenMMLab. All rights reserved. | |
import copy | |
import os | |
import os.path as osp | |
import shutil | |
from typing import List, Optional, Union | |
from mmocr.registry import (CFG_GENERATORS, DATA_DUMPERS, DATA_GATHERERS, | |
DATA_OBTAINERS, DATA_PACKERS, DATA_PARSERS) | |
from mmocr.utils.typing_utils import ConfigType, OptConfigType | |
class DatasetPreparer: | |
"""Base class of dataset preparer. | |
Dataset preparer is used to prepare dataset for MMOCR. It mainly consists | |
of three steps: | |
1. For each split: | |
- Obtain the dataset | |
- Download | |
- Extract | |
- Move/Rename | |
- Gather the dataset | |
- Parse the dataset | |
- Pack the dataset to MMOCR format | |
- Dump the dataset | |
2. Delete useless files | |
3. Generate the base config for this dataset | |
After all these steps, the original datasets have been prepared for | |
usage in MMOCR. Check out the dataset format used in MMOCR here: | |
https://mmocr.readthedocs.io/en/dev-1.x/user_guides/dataset_prepare.html | |
Args: | |
data_root (str): Root directory of data. | |
dataset_name (str): Dataset name. | |
task (str): Task type. Options are 'textdet', 'textrecog', | |
'textspotter', and 'kie'. Defaults to 'textdet'. | |
nproc (int): Number of parallel processes. Defaults to 4. | |
train_preparer (OptConfigType): cfg for train data prepare. It contains | |
the following keys: | |
- obtainer: cfg for data obtainer. | |
- gatherer: cfg for data gatherer. | |
- parser: cfg for data parser. | |
- packer: cfg for data packer. | |
- dumper: cfg for data dumper. | |
Defaults to None. | |
test_preparer (OptConfigType): cfg for test data prepare. Defaults to | |
None. | |
val_preparer (OptConfigType): cfg for val data prepare. Defaults to | |
None. | |
config_generator (OptConfigType): cfg for config generator. Defaults to | |
None. | |
delete (list[str], optional): List of files to be deleted. | |
Defaults to None. | |
""" | |
def __init__(self, | |
data_root: str, | |
dataset_name: str = '', | |
task: str = 'textdet', | |
nproc: int = 4, | |
train_preparer: OptConfigType = None, | |
test_preparer: OptConfigType = None, | |
val_preparer: OptConfigType = None, | |
config_generator: OptConfigType = None, | |
delete: Optional[List[str]] = None) -> None: | |
self.data_root = data_root | |
self.nproc = nproc | |
self.task = task | |
self.dataset_name = dataset_name | |
self.train_preparer = train_preparer | |
self.test_preparer = test_preparer | |
self.val_preparer = val_preparer | |
self.config_generator = config_generator | |
self.delete = delete | |
def run(self, splits: Union[str, List] = ['train', 'test', 'val']) -> None: | |
"""Prepare the dataset.""" | |
if isinstance(splits, str): | |
splits = [splits] | |
assert set(splits).issubset(set(['train', 'test', | |
'val'])), 'Invalid split name' | |
for split in splits: | |
self.loop(split, getattr(self, f'{split}_preparer')) | |
self.clean() | |
self.generate_config() | |
def from_file(cls, cfg: ConfigType) -> 'DatasetPreparer': | |
"""Create a DataPreparer from config file. | |
Args: | |
cfg (ConfigType): A config used for building runner. Keys of | |
``cfg`` can see :meth:`__init__`. | |
Returns: | |
Runner: A DatasetPreparer build from ``cfg``. | |
""" | |
cfg = copy.deepcopy(cfg) | |
data_preparer = cls( | |
data_root=cfg['data_root'], | |
dataset_name=cfg.get('dataset_name', ''), | |
task=cfg.get('task', 'textdet'), | |
nproc=cfg.get('nproc', 4), | |
train_preparer=cfg.get('train_preparer', None), | |
test_preparer=cfg.get('test_preparer', None), | |
val_preparer=cfg.get('val_preparer', None), | |
delete=cfg.get('delete', None), | |
config_generator=cfg.get('config_generator', None)) | |
return data_preparer | |
def loop(self, split: str, cfg: ConfigType) -> None: | |
"""Loop over the dataset. | |
Args: | |
split (str): The split of the dataset. | |
cfg (ConfigType): A config used for building obtainer, gatherer, | |
parser, packer and dumper. | |
""" | |
if cfg is None: | |
return | |
# build obtainer and run | |
obtainer = cfg.get('obtainer', None) | |
if obtainer: | |
print(f'Obtaining {split} Dataset...') | |
obtainer.setdefault('task', default=self.task) | |
obtainer.setdefault('data_root', default=self.data_root) | |
obtainer = DATA_OBTAINERS.build(obtainer) | |
obtainer() | |
# build gatherer | |
gatherer = cfg.get('gatherer', None) | |
parser = cfg.get('parser', None) | |
packer = cfg.get('packer', None) | |
dumper = cfg.get('dumper', None) | |
related = [gatherer, parser, packer, dumper] | |
if all(item is None for item in related): # no data process | |
return | |
if not all(item is not None for item in related): | |
raise ValueError('gatherer, parser, packer and dumper should be ' | |
'either all None or not None') | |
print(f'Gathering {split} Dataset...') | |
gatherer.setdefault('split', default=split) | |
gatherer.setdefault('data_root', default=self.data_root) | |
gatherer.setdefault('ann_dir', default='annotations') | |
gatherer.setdefault( | |
'img_dir', default=osp.join(f'{self.task}_imgs', split)) | |
gatherer = DATA_GATHERERS.build(gatherer) | |
img_paths, ann_paths = gatherer() | |
# build parser | |
print(f'Parsing {split} Images and Annotations...') | |
parser.setdefault('split', default=split) | |
parser.setdefault('nproc', default=self.nproc) | |
parser = DATA_PARSERS.build(parser) | |
# Convert dataset annotations to MMOCR format | |
samples = parser(img_paths, ann_paths) | |
# build packer | |
print(f'Packing {split} Annotations...') | |
packer.setdefault('split', default=split) | |
packer.setdefault('nproc', default=self.nproc) | |
packer.setdefault('data_root', default=self.data_root) | |
packer = DATA_PACKERS.build(packer) | |
samples = packer(samples) | |
# build dumper | |
print(f'Dumping {split} Annotations...') | |
# Dump annotation files | |
dumper.setdefault('task', default=self.task) | |
dumper.setdefault('split', default=split) | |
dumper.setdefault('data_root', default=self.data_root) | |
dumper = DATA_DUMPERS.build(dumper) | |
dumper(samples) | |
def generate_config(self): | |
if self.config_generator is None: | |
return | |
self.config_generator.setdefault( | |
'dataset_name', default=self.dataset_name) | |
self.config_generator.setdefault('data_root', default=self.data_root) | |
config_generator = CFG_GENERATORS.build(self.config_generator) | |
print('Generating base configs...') | |
config_generator() | |
def clean(self) -> None: | |
if self.delete is None: | |
return | |
for d in self.delete: | |
delete_file = osp.join(self.data_root, d) | |
if osp.exists(delete_file): | |
if osp.isdir(delete_file): | |
shutil.rmtree(delete_file) | |
else: | |
os.remove(delete_file) | |