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