| dataset_type = 'ParkingDataset' |
| data_root = 'data/parking/' |
| img_norm_cfg = dict( |
| mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) |
| train_pipeline = [ |
| dict(type='LoadImageFromFile'), |
| dict(type='LoadAnnotations', with_bbox=True, with_mask=True), |
| dict(type='Resize', img_scale=(1333, 800), keep_ratio=True), |
| dict(type='RandomFlip', flip_ratio=0.5), |
| dict(type='Normalize', **img_norm_cfg), |
| dict(type='Pad', size_divisor=32), |
| dict(type='DefaultFormatBundle'), |
| dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_bboxes_3d','gt_bboxes_3d_proj']), |
| ] |
| test_pipeline = [ |
| dict(type='LoadImageFromFile'), |
| dict( |
| type='MultiScaleFlipAug', |
| img_scale=(1333, 800), |
| flip=False, |
| transforms=[ |
| dict(type='Resize', keep_ratio=True), |
| dict(type='RandomFlip'), |
| dict(type='Normalize', **img_norm_cfg), |
| dict(type='Pad', size_divisor=32), |
| dict(type='ImageToTensor', keys=['img']), |
| dict(type='Collect', keys=['img']), |
| ]) |
| ] |
| data = dict( |
| samples_per_gpu=1, |
| workers_per_gpu=1, |
| train=dict( |
| type=dataset_type, |
| ann_file=data_root + 'GT_data/', |
| img_prefix=data_root + 'images/', |
| pipeline=train_pipeline), |
| val=dict( |
| type=dataset_type, |
| ann_file=data_root + 'GT_data/', |
| img_prefix=data_root + 'images/', |
| pipeline=test_pipeline), |
| test=dict( |
| type=dataset_type, |
| ann_file=data_root + 'GT_data/', |
| img_prefix=data_root + 'images/', |
| pipeline=test_pipeline)) |
| evaluation = dict(metric=['bbox']) |
|
|
