Files
modelscope/modelscope/msdatasets/dataset_cls/custom_datasets/builder.py
xingjun.wxj e02a260c93 Refactor the task_datasets module
Refactor the task_datasets module:

1. Add new module modelscope.msdatasets.dataset_cls.custom_datasets.
2. Add new function: modelscope.msdatasets.ms_dataset.MsDataset.to_custom_dataset().
2. Add calling to_custom_dataset() func in MsDataset.load() to adapt new custom_datasets module.
3. Refactor the pipeline for loading custom dataset: 
	1) Only use MsDataset.load() function to load the custom datasets.
	2) Combine MsDataset.load() with class EpochBasedTrainer.
4. Add new entry func for building datasets in EpochBasedTrainer: see modelscope.trainers.trainer.EpochBasedTrainer.build_dataset()
5. Add new func to build the custom dataset from model configuration, see: modelscope.trainers.trainer.EpochBasedTrainer.build_dataset_from_cfg()
6. Add new registry function for building custom datasets, see: modelscope.msdatasets.dataset_cls.custom_datasets.builder.build_custom_dataset()
7. Refine the class SiameseUIETrainer to adapt the new custom_datasets module.
8. Add class TorchCustomDataset as a superclass for custom datasets classes.
9. To move modules/classes/functions:
	1) Move module msdatasets.audio to custom_datasets
	2) Move module msdatasets.cv to custom_datasets
	3) Move module bad_image_detecting to custom_datasets
	4) Move module damoyolo to custom_datasets
	5) Move module face_2d_keypoints to custom_datasets
	6) Move module hand_2d_keypoints to custom_datasets
	7) Move module human_wholebody_keypoint to custom_datasets
	8) Move module image_classification to custom_datasets
	9) Move module image_inpainting to custom_datasets
	10) Move module image_portrait_enhancement to custom_datasets
	11) Move module image_quality_assessment_degradation to custom_datasets
	12) Move module image_quality_assmessment_mos to custom_datasets
	13) Move class LanguageGuidedVideoSummarizationDataset to custom_datasets
	14) Move class MGeoRankingDataset to custom_datasets
	15) Move module movie_scene_segmentation custom_datasets
	16) Move module object_detection to custom_datasets
	17) Move module referring_video_object_segmentation to custom_datasets
	18) Move module sidd_image_denoising to custom_datasets
	19) Move module video_frame_interpolation to custom_datasets
	20) Move module video_stabilization to custom_datasets
	21) Move module video_super_resolution to custom_datasets
	22) Move class GoproImageDeblurringDataset to custom_datasets
	23) Move class EasyCVBaseDataset to custom_datasets
	24) Move class ImageInstanceSegmentationCocoDataset to custom_datasets
	25) Move class RedsImageDeblurringDataset to custom_datasets
	26) Move class TextRankingDataset to custom_datasets
	27) Move class VecoDataset to custom_datasets
	28) Move class VideoSummarizationDataset to custom_datasets
10. To delete modules/functions/classes:
	1) Del module task_datasets
	2) Del to_task_dataset() in EpochBasedTrainer
	3) Del build_dataset() in EpochBasedTrainer and renew a same name function.
11. Rename class Datasets to CustomDatasets in metainfo.py

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/11872747
2023-03-10 09:03:32 +08:00

22 lines
791 B
Python

# Copyright (c) Alibaba, Inc. and its affiliates.
from modelscope.utils.config import ConfigDict
from modelscope.utils.registry import Registry, build_from_cfg
CUSTOM_DATASETS = Registry('custom_datasets')
def build_custom_dataset(cfg: ConfigDict,
task_name: str,
default_args: dict = None):
""" Build custom dataset for user-define dataset given model config and task name.
Args:
cfg (:obj:`ConfigDict`): config dict for model object.
task_name (str, optional): task name, refer to
:obj:`Tasks` for more details
default_args (dict, optional): Default initialization arguments.
"""
return build_from_cfg(
cfg, CUSTOM_DATASETS, group_key=task_name, default_args=default_args)