| _base_ = 'ssd300_voc0712.py' | |
| input_size = 512 | |
| model = dict( | |
| backbone=dict(input_size=input_size), | |
| bbox_head=dict( | |
| in_channels=(512, 1024, 512, 256, 256, 256, 256), | |
| anchor_generator=dict( | |
| input_size=input_size, | |
| strides=[8, 16, 32, 64, 128, 256, 512], | |
| basesize_ratio_range=(0.15, 0.9), | |
| ratios=([2], [2, 3], [2, 3], [2, 3], [2, 3], [2], [2])))) | |
| 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=(512, 512), 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=(512, 512), | |
| 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( | |
| train=dict(dataset=dict(pipeline=train_pipeline)), | |
| val=dict(pipeline=test_pipeline), | |
| test=dict(pipeline=test_pipeline)) | |