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- _base_ = 'ssd300_coco.py'
- # model settings
- input_size = 512
- model = dict(
- neck=dict(
- out_channels=(512, 1024, 512, 256, 256, 256, 256),
- level_strides=(2, 2, 2, 2, 1),
- level_paddings=(1, 1, 1, 1, 1),
- last_kernel_size=4),
- bbox_head=dict(
- in_channels=(512, 1024, 512, 256, 256, 256, 256),
- anchor_generator=dict(
- type='SSDAnchorGenerator',
- scale_major=False,
- input_size=input_size,
- basesize_ratio_range=(0.1, 0.9),
- strides=[8, 16, 32, 64, 128, 256, 512],
- ratios=[[2], [2, 3], [2, 3], [2, 3], [2, 3], [2], [2]])))
- # dataset settings
- train_pipeline = [
- dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
- dict(type='LoadAnnotations', with_bbox=True),
- dict(
- type='Expand',
- mean={{_base_.model.data_preprocessor.mean}},
- to_rgb={{_base_.model.data_preprocessor.bgr_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', scale=(input_size, input_size), keep_ratio=False),
- dict(type='RandomFlip', prob=0.5),
- dict(
- type='PhotoMetricDistortion',
- brightness_delta=32,
- contrast_range=(0.5, 1.5),
- saturation_range=(0.5, 1.5),
- hue_delta=18),
- dict(type='PackDetInputs')
- ]
- test_pipeline = [
- dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
- dict(type='Resize', scale=(input_size, input_size), keep_ratio=False),
- dict(type='LoadAnnotations', with_bbox=True),
- dict(
- type='PackDetInputs',
- meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
- 'scale_factor'))
- ]
- train_dataloader = dict(dataset=dict(dataset=dict(pipeline=train_pipeline)))
- val_dataloader = dict(dataset=dict(pipeline=test_pipeline))
- test_dataloader = val_dataloader
- # NOTE: `auto_scale_lr` is for automatically scaling LR,
- # USER SHOULD NOT CHANGE ITS VALUES.
- # base_batch_size = (8 GPUs) x (8 samples per GPU)
- auto_scale_lr = dict(base_batch_size=64)
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