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yolov9_m-detection.yaml
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73 lines (73 loc) · 1.87 KB
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model:
task: detection
name: yolov9_m
checkpoint:
use_pretrained: true
load_head: false
path: ~
optimizer_path: ~
freeze_backbone: false
architecture:
full: ~ # auto
backbone:
name: gelan
params:
stem_out_channels: 32
stem_kernel_size: 3
stem_stride: 2
return_stage_idx: [1, 2, 3]
act_type: &act_type silu
stage_params:
# Conv2D: ['conv', out_channels, kernel_size, stride]
# ELAN: ['elan', out_channels, part_channels, use_identity]
# RepNCSPELAN: ['repncspelan', out_channels, part_channels, use_identity, depth]
# AConv: ['aconv', out_channels]
# ADown: ['adown', out_channels]
-
- ['conv', 64, 3, 2]
- ['repncspelan', 128, 128, false, 1]
-
- ['aconv', 240]
- ['repncspelan', 240, 240, false, 1]
-
- ['aconv', 360]
- ['repncspelan', 360, 360, false, 1]
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- ['aconv', 480]
- ['repncspelan', 480, 480, false, 1]
neck:
name: yolov9fpn
params:
repeat_num: 1
act_type: *act_type
use_aux_loss: &use_aux_loss false
bu_type: aconv
spp_channels: 480
n4_channels: 360
p3_channels: 240
p3_to_p4_channels: 184
p4_channels: 360
p4_to_p5_channels: 240
p5_channels: 480
head:
name: yolo_detection_head
params:
version: v9
num_anchors: ~
use_group: true
reg_max: ®_max 16
act_type: *act_type
use_aux_loss: *use_aux_loss
postprocessor:
params:
# postprocessor - decode
reg_max: *reg_max
score_thresh: 0.01
# postprocessor - nms
nms_thresh: 0.65
class_agnostic: false
losses:
- criterion: yolov9_loss
reg_max: *reg_max
weight: ~
l1_activate_epoch: ~