mindocr/mindocr/data

• Guideline for Data Module
• • Code Structure
  • How to add your own dataset class
  • How to add your own data transformation

Guideline for Data Module

Code Structure

├── README.md
├── __init__.py
├── base_dataset.py  				# base dataset class with __getitem__
├── builder.py					# API for create dataset and loader
├── det_dataset.py				# general text detection dataset class
├── rec_dataset.py				# general rec detection dataset class
├── rec_lmdb_dataset.py				# LMDB dataset class
└── transforms
    ├── det_transforms.py			# processing and augmentation ops (callabel classes) especially for detection tasks
    ├── general_transforms.py			# general processing and augmentation ops (callabel classes)
    ├── modelzoo_transforms.py			# transformations adopted from modelzoo
    ├── rec_transforms.py			# processing and augmentation ops (callabel classes) especially for recognition tasks
    └── transforms_factory.py			# API for create and run transforms

How to add your own dataset class

1. Inherit from BaseDataset class

2. Rewrite the following file and annotation parsing functions in BaseDataset.

   def load_data_list(self, label_file: Union[str, List[str]], sample_ratio: Union[float, List] = 1.0, shuffle: bool = False, **kwargs) -> List[dict]

   def _parse_annotation(self, data_line: str) -> Union[dict, List[dict]]

How to add your own data transformation

Please refer to Guideline for Developing Your Transformation