97 lines
2.8 KiB
Python
97 lines
2.8 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
|
|
model = dict(
|
|
type='RotatedRetinaNet',
|
|
backbone=dict(
|
|
type='ResNet',
|
|
depth=50,
|
|
num_stages=4,
|
|
out_indices=(0, 1, 2, 3),
|
|
frozen_stages=1,
|
|
zero_init_residual=False,
|
|
norm_cfg=dict(type='BN', requires_grad=True),
|
|
norm_eval=True,
|
|
style='pytorch',
|
|
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
|
|
neck=dict(
|
|
type='FPN',
|
|
in_channels=[256, 512, 1024, 2048],
|
|
out_channels=256,
|
|
start_level=1,
|
|
add_extra_convs='on_input',
|
|
num_outs=5),
|
|
bbox_head=dict(
|
|
type='RotatedRetinaHead',
|
|
num_classes=15,
|
|
in_channels=256,
|
|
stacked_convs=4,
|
|
feat_channels=256,
|
|
assign_by_circumhbbox=None,
|
|
anchor_generator=dict(
|
|
type='RotatedAnchorGenerator',
|
|
octave_base_scale=4,
|
|
scales_per_octave=3,
|
|
ratios=[1.0, 0.5, 2.0],
|
|
strides=[8, 16, 32, 64, 128]),
|
|
bbox_coder=dict(
|
|
type='DeltaXYWHAOBBoxCoder',
|
|
angle_range='le135',
|
|
norm_factor=1,
|
|
edge_swap=False,
|
|
proj_xy=True,
|
|
target_means=(0.0, 0.0, 0.0, 0.0, 0.0),
|
|
target_stds=(1.0, 1.0, 1.0, 1.0, 1.0)),
|
|
loss_cls=dict(
|
|
type='FocalLoss',
|
|
use_sigmoid=True,
|
|
gamma=2.0,
|
|
alpha=0.25,
|
|
loss_weight=1.0),
|
|
loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
|
|
train_cfg=dict(
|
|
assigner=dict(
|
|
type='MaxIoUAssigner',
|
|
pos_iou_thr=0.5,
|
|
neg_iou_thr=0.4,
|
|
min_pos_iou=0,
|
|
ignore_iof_thr=-1,
|
|
iou_calculator=dict(type='RBboxOverlaps2D')),
|
|
allowed_border=-1,
|
|
pos_weight=-1,
|
|
debug=False),
|
|
test_cfg=dict(
|
|
nms_pre=2000,
|
|
min_bbox_size=0,
|
|
score_thr=0.05,
|
|
nms=dict(iou_thr=0.1),
|
|
max_per_img=2000))
|
|
# dataset settings
|
|
dataset_type = 'DOTADataset'
|
|
data_root = '.'
|
|
test_pipeline = [
|
|
dict(type='LoadImageFromFile'),
|
|
dict(
|
|
type='MultiScaleFlipAug',
|
|
img_scale=(1024, 1024),
|
|
flip=False,
|
|
transforms=[
|
|
dict(type='RResize'),
|
|
dict(
|
|
type='Normalize',
|
|
mean=[123.675, 116.28, 103.53],
|
|
std=[58.395, 57.12, 57.375],
|
|
to_rgb=True),
|
|
dict(type='Pad', size_divisor=32),
|
|
dict(type='DefaultFormatBundle'),
|
|
dict(type='Collect', keys=['img'])
|
|
])
|
|
]
|
|
data = dict(
|
|
samples_per_gpu=2,
|
|
workers_per_gpu=2,
|
|
test=dict(
|
|
type=dataset_type,
|
|
ann_file='tests/test_codebase/test_mmrotate/data/dota_sample/',
|
|
img_prefix=data_root,
|
|
pipeline=test_pipeline,
|
|
version='le135'))
|