|
- _base_ = [
- '../_base_/models/faster_rcnn_r50_caffe_c4.py',
- '../_base_/datasets/coco_detection.py',
- '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
- ]
-
- model = dict(
- type='TridentFasterRCNN',
- backbone=dict(
- type='TridentResNet',
- trident_dilations=(1, 2, 3),
- num_branch=3,
- test_branch_idx=1,
- init_cfg=dict(
- type='Pretrained',
- checkpoint='open-mmlab://detectron2/resnet50_caffe')),
- roi_head=dict(type='TridentRoIHead', num_branch=3, test_branch_idx=1),
- train_cfg=dict(
- rpn_proposal=dict(max_per_img=500),
- rcnn=dict(
- sampler=dict(num=128, pos_fraction=0.5,
- add_gt_as_proposals=False))))
-
- # use caffe img_norm
- 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='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', 'gt_bboxes', 'gt_labels'])
- ]
- 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(
- train=dict(pipeline=train_pipeline),
- val=dict(pipeline=test_pipeline),
- test=dict(pipeline=test_pipeline))
|