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on
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Running
on
Zero
| _base_ = [ | |
| '../_base_/models/faster-rcnn_r50_fpn.py', | |
| '../_base_/schedules/schedule_1x.py', | |
| '../_base_/default_runtime.py', | |
| ] | |
| model = dict(roi_head=dict(bbox_head=dict(num_classes=601))) | |
| # dsdl dataset settings | |
| # please visit our platform [OpenDataLab](https://opendatalab.com/) | |
| # to downloaded dsdl dataset. | |
| dataset_type = 'DSDLDetDataset' | |
| data_root = 'data/OpenImages' | |
| train_ann = 'dsdl/set-train/train.yaml' | |
| val_ann = 'dsdl/set-val/val.yaml' | |
| specific_key_path = dict( | |
| image_level_labels='./image_labels/*/label', | |
| Label='./objects/*/label', | |
| is_group_of='./objects/*/isgroupof', | |
| ) | |
| backend_args = dict( | |
| backend='petrel', | |
| path_mapping=dict({'data/': 's3://open_dataset_original/'})) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile', backend_args=backend_args), | |
| dict(type='LoadAnnotations', with_bbox=True), | |
| dict(type='Resize', scale=(1024, 800), keep_ratio=True), | |
| dict(type='RandomFlip', prob=0.5), | |
| dict(type='PackDetInputs') | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile', backend_args=backend_args), | |
| dict(type='Resize', scale=(1024, 800), keep_ratio=True), | |
| dict(type='LoadAnnotations', with_bbox=True), | |
| dict( | |
| type='PackDetInputs', | |
| meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', | |
| 'scale_factor', 'instances', 'image_level_labels')) | |
| ] | |
| train_dataloader = dict( | |
| sampler=dict(type='ClassAwareSampler', num_sample_class=1), | |
| dataset=dict( | |
| type=dataset_type, | |
| with_imagelevel_label=True, | |
| with_hierarchy=True, | |
| specific_key_path=specific_key_path, | |
| data_root=data_root, | |
| ann_file=train_ann, | |
| filter_cfg=dict(filter_empty_gt=True, min_size=32, bbox_min_size=32), | |
| pipeline=train_pipeline)) | |
| val_dataloader = dict( | |
| dataset=dict( | |
| type=dataset_type, | |
| with_imagelevel_label=True, | |
| with_hierarchy=True, | |
| specific_key_path=specific_key_path, | |
| data_root=data_root, | |
| ann_file=val_ann, | |
| test_mode=True, | |
| pipeline=test_pipeline)) | |
| test_dataloader = val_dataloader | |
| default_hooks = dict(logger=dict(type='LoggerHook', interval=1000), ) | |
| train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=3, val_interval=1) | |
| param_scheduler = [ | |
| dict( | |
| type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500), | |
| dict( | |
| type='MultiStepLR', | |
| begin=0, | |
| end=12, | |
| by_epoch=True, | |
| milestones=[1, 2], | |
| gamma=0.1) | |
| ] | |
| # optimizer | |
| optim_wrapper = dict( | |
| type='OptimWrapper', | |
| optimizer=dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)) | |
| val_evaluator = dict( | |
| type='OpenImagesMetric', | |
| iou_thrs=0.5, | |
| ioa_thrs=0.5, | |
| use_group_of=True, | |
| get_supercategory=True) | |
| test_evaluator = val_evaluator | |