car-line-detect/configs/fcos/_base_/fcos_r50_fpn.yml
2021-06-23 08:58:10 +08:00

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YAML

architecture: FCOS
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
FCOS:
backbone: ResNet
neck: FPN
fcos_head: FCOSHead
fcos_post_process: FCOSPostProcess
ResNet:
# index 0 stands for res2
depth: 50
norm_type: bn
freeze_at: 0
return_idx: [1,2,3]
num_stages: 4
FPN:
out_channel: 256
spatial_scales: [0.125, 0.0625, 0.03125]
extra_stage: 2
has_extra_convs: true
use_c5: false
FCOSHead:
fcos_feat:
name: FCOSFeat
feat_in: 256
feat_out: 256
num_convs: 4
norm_type: "gn"
use_dcn: false
num_classes: 80
fpn_stride: [8, 16, 32, 64, 128]
prior_prob: 0.01
fcos_loss: FCOSLoss
norm_reg_targets: true
centerness_on_reg: true
FCOSLoss:
loss_alpha: 0.25
loss_gamma: 2.0
iou_loss_type: "giou"
reg_weights: 1.0
FCOSPostProcess:
decode:
name: FCOSBox
num_classes: 80
nms:
name: MultiClassNMS
nms_top_k: 1000
keep_top_k: 100
score_threshold: 0.025
nms_threshold: 0.6