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| _base_ = [ | |
| '../_base_/models/ssd300.py', '../_base_/datasets/voc0712.py', | |
| '../_base_/default_runtime.py' | |
| ] | |
| model = dict( | |
| bbox_head=dict( | |
| num_classes=20, anchor_generator=dict(basesize_ratio_range=(0.2, | |
| 0.9)))) | |
| # dataset settings | |
| dataset_type = 'VOCDataset' | |
| data_root = 'data/VOCdevkit/' | |
| img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[1, 1, 1], to_rgb=True) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile', to_float32=True), | |
| dict(type='LoadAnnotations', with_bbox=True), | |
| dict( | |
| type='PhotoMetricDistortion', | |
| brightness_delta=32, | |
| contrast_range=(0.5, 1.5), | |
| saturation_range=(0.5, 1.5), | |
| hue_delta=18), | |
| dict( | |
| type='Expand', | |
| mean=img_norm_cfg['mean'], | |
| to_rgb=img_norm_cfg['to_rgb'], | |
| ratio_range=(1, 4)), | |
| dict( | |
| type='MinIoURandomCrop', | |
| min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), | |
| min_crop_size=0.3), | |
| dict(type='Resize', img_scale=(300, 300), keep_ratio=False), | |
| dict(type='Normalize', **img_norm_cfg), | |
| dict(type='RandomFlip', flip_ratio=0.5), | |
| dict(type='DefaultFormatBundle'), | |
| dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']), | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='MultiScaleFlipAug', | |
| img_scale=(300, 300), | |
| flip=False, | |
| transforms=[ | |
| dict(type='Resize', keep_ratio=False), | |
| dict(type='Normalize', **img_norm_cfg), | |
| dict(type='ImageToTensor', keys=['img']), | |
| dict(type='Collect', keys=['img']), | |
| ]) | |
| ] | |
| data = dict( | |
| samples_per_gpu=8, | |
| workers_per_gpu=3, | |
| train=dict( | |
| type='RepeatDataset', times=10, dataset=dict(pipeline=train_pipeline)), | |
| val=dict(pipeline=test_pipeline), | |
| test=dict(pipeline=test_pipeline)) | |
| # optimizer | |
| optimizer = dict(type='SGD', lr=1e-3, momentum=0.9, weight_decay=5e-4) | |
| optimizer_config = dict() | |
| # learning policy | |
| lr_config = dict( | |
| policy='step', | |
| warmup='linear', | |
| warmup_iters=500, | |
| warmup_ratio=0.001, | |
| step=[16, 20]) | |
| checkpoint_config = dict(interval=1) | |
| # runtime settings | |
| runner = dict(type='EpochBasedRunner', max_epochs=24) | |