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- _base_ = [
- '../_base_/models/faster-rcnn_r50_fpn.py',
- '../_base_/datasets/coco_detection.py',
- '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
- ]
- model = dict(
- data_preprocessor=dict(
- # The mean and std are used in PyCls when training RegNets
- mean=[103.53, 116.28, 123.675],
- std=[57.375, 57.12, 58.395],
- bgr_to_rgb=False),
- backbone=dict(
- _delete_=True,
- type='RegNet',
- arch='regnetx_3.2gf',
- out_indices=(0, 1, 2, 3),
- frozen_stages=1,
- norm_cfg=dict(type='BN', requires_grad=True),
- norm_eval=True,
- style='pytorch',
- init_cfg=dict(
- type='Pretrained', checkpoint='open-mmlab://regnetx_3.2gf')),
- neck=dict(
- type='FPN',
- in_channels=[96, 192, 432, 1008],
- out_channels=256,
- num_outs=5))
- optim_wrapper = dict(
- optimizer=dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.00005))
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