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_base_ = './ppyoloe_s_fast_8xb32-300e_coco.py'
# The pretrained model is geted and converted from official PPYOLOE.
# https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/ppyoloe/README.md
checkpoint = 'https://download.openmmlab.com/mmyolo/v0/ppyoloe/ppyoloe_pretrain/cspresnet_l_imagenet1k_pretrained-c0010e6c.pth' # noqa
deepen_factor = 1.0
widen_factor = 1.0
train_batch_size_per_gpu = 20
model = dict(
backbone=dict(
deepen_factor=deepen_factor,
widen_factor=widen_factor,
init_cfg=dict(checkpoint=checkpoint)),
neck=dict(
deepen_factor=deepen_factor,
widen_factor=widen_factor,
),
bbox_head=dict(head_module=dict(widen_factor=widen_factor)))
train_dataloader = dict(batch_size=train_batch_size_per_gpu)
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