Spaces:
Build error
Build error
| _base_ = '../fast_rcnn/fast_rcnn_r50_fpn_1x_coco.py' | |
| model = dict( | |
| pretrained='open-mmlab://detectron2/resnet50_caffe', | |
| backbone=dict( | |
| type='ResNet', | |
| depth=50, | |
| num_stages=4, | |
| out_indices=(0, 1, 2, 3), | |
| frozen_stages=1, | |
| norm_cfg=dict(type='BN', requires_grad=False), | |
| norm_eval=True, | |
| style='caffe'), | |
| roi_head=dict( | |
| bbox_head=dict(bbox_coder=dict(target_stds=[0.05, 0.05, 0.1, 0.1]))), | |
| # model training and testing settings | |
| train_cfg=dict( | |
| rcnn=dict( | |
| assigner=dict(pos_iou_thr=0.6, neg_iou_thr=0.6, min_pos_iou=0.6), | |
| sampler=dict(num=256))), | |
| test_cfg=dict(rcnn=dict(score_thr=1e-3))) | |
| dataset_type = 'CocoDataset' | |
| data_root = 'data/coco/' | |
| img_norm_cfg = dict( | |
| mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict(type='LoadProposals', num_max_proposals=300), | |
| dict(type='LoadAnnotations', with_bbox=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', 'proposals', 'gt_bboxes', 'gt_labels']), | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict(type='LoadProposals', num_max_proposals=None), | |
| 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', 'proposals']), | |
| ]) | |
| ] | |
| data = dict( | |
| train=dict( | |
| proposal_file=data_root + 'proposals/ga_rpn_r50_fpn_1x_train2017.pkl', | |
| pipeline=train_pipeline), | |
| val=dict( | |
| proposal_file=data_root + 'proposals/ga_rpn_r50_fpn_1x_val2017.pkl', | |
| pipeline=test_pipeline), | |
| test=dict( | |
| proposal_file=data_root + 'proposals/ga_rpn_r50_fpn_1x_val2017.pkl', | |
| pipeline=test_pipeline)) | |
| optimizer_config = dict( | |
| _delete_=True, grad_clip=dict(max_norm=35, norm_type=2)) | |