Spaces:
Runtime error
Runtime error
| # Copyright (c) OpenMMLab. All rights reserved. | |
| # Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa | |
| # mmcv >= 2.0.1 | |
| # mmengine >= 0.8.0 | |
| from mmengine.config import read_base | |
| with read_base(): | |
| from .ssj_270_coco_instance import * | |
| from mmdet.datasets import MultiImageMixDataset | |
| from mmdet.datasets.transforms import CopyPaste | |
| # dataset settings | |
| dataset_type = CocoDataset | |
| data_root = 'data/coco/' | |
| image_size = (1024, 1024) | |
| # Example to use different file client | |
| # Method 1: simply set the data root and let the file I/O module | |
| # automatically infer from prefix (not support LMDB and Memcache yet) | |
| # data_root = 's3://openmmlab/datasets/detection/coco/' | |
| # Method 2: Use `backend_args`, `file_client_args` in versions before 3.0.0rc6 | |
| # backend_args = dict( | |
| # backend='petrel', | |
| # path_mapping=dict({ | |
| # './data/': 's3://openmmlab/datasets/detection/', | |
| # 'data/': 's3://openmmlab/datasets/detection/' | |
| # })) | |
| backend_args = None | |
| # Standard Scale Jittering (SSJ) resizes and crops an image | |
| # with a resize range of 0.8 to 1.25 of the original image size. | |
| load_pipeline = [ | |
| dict(type=LoadImageFromFile, backend_args=backend_args), | |
| dict(type=LoadAnnotations, with_bbox=True, with_mask=True), | |
| dict( | |
| type=RandomResize, | |
| scale=image_size, | |
| ratio_range=(0.8, 1.25), | |
| keep_ratio=True), | |
| dict( | |
| type='RandomCrop', | |
| crop_type='absolute_range', | |
| crop_size=image_size, | |
| recompute_bbox=True, | |
| allow_negative_crop=True), | |
| dict(type='FilterAnnotations', min_gt_bbox_wh=(1e-2, 1e-2)), | |
| dict(type=RandomFlip, prob=0.5), | |
| dict(type=Pad, size=image_size), | |
| ] | |
| train_pipeline = [ | |
| dict(type=CopyPaste, max_num_pasted=100), | |
| dict(type=PackDetInputs) | |
| ] | |
| train_dataloader.update( | |
| dict( | |
| type=MultiImageMixDataset, | |
| dataset=dict( | |
| type=dataset_type, | |
| data_root=data_root, | |
| ann_file='annotations/instances_train2017.json', | |
| data_prefix=dict(img='train2017/'), | |
| filter_cfg=dict(filter_empty_gt=True, min_size=32), | |
| pipeline=load_pipeline, | |
| backend_args=backend_args), | |
| pipeline=train_pipeline)) | |