pose-detect/ultralytics/cfg/models/v9/yolov9t.yaml

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1.2 KiB
YAML

# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv9t object detection model. For Usage examples see https://docs.ultralytics.com/models/yolov9
# 917 layers, 2128720 parameters, 8.5 GFLOPs
# Parameters
nc: 80 # number of classes
# GELAN backbone
backbone:
- [-1, 1, Conv, [16, 3, 2]] # 0-P1/2
- [-1, 1, Conv, [32, 3, 2]] # 1-P2/4
- [-1, 1, ELAN1, [32, 32, 16]] # 2
- [-1, 1, AConv, [64]] # 3-P3/8
- [-1, 1, RepNCSPELAN4, [64, 64, 32, 3]] # 4
- [-1, 1, AConv, [96]] # 5-P4/16
- [-1, 1, RepNCSPELAN4, [96, 96, 48, 3]] # 6
- [-1, 1, AConv, [128]] # 7-P5/32
- [-1, 1, RepNCSPELAN4, [128, 128, 64, 3]] # 8
- [-1, 1, SPPELAN, [128, 64]] # 9
head:
- [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 1, RepNCSPELAN4, [96, 96, 48, 3]] # 12
- [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 1, RepNCSPELAN4, [64, 64, 32, 3]] # 15
- [-1, 1, AConv, [48]]
- [[-1, 12], 1, Concat, [1]] # cat head P4
- [-1, 1, RepNCSPELAN4, [96, 96, 48, 3]] # 18 (P4/16-medium)
- [-1, 1, AConv, [64]]
- [[-1, 9], 1, Concat, [1]] # cat head P5
- [-1, 1, RepNCSPELAN4, [128, 128, 64, 3]] # 21 (P5/32-large)
- [[15, 18, 21], 1, Detect, [nc]] # Detect(P3, P4, P5)