From 98321aa7d5ac82af10a237ac271b57f067a03d9b Mon Sep 17 00:00:00 2001 From: Yunhao Meng Date: Sat, 10 May 2025 16:19:00 +0800 Subject: [PATCH] =?UTF-8?q?=E8=AE=AD=E7=BB=83=E6=A8=A1=E5=9E=8B=E9=85=8D?= =?UTF-8?q?=E7=BD=AE?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- federated_learning/yolov8.yaml | 49 ++++++++++++++++++++++++++++++++++ 1 file changed, 49 insertions(+) create mode 100644 federated_learning/yolov8.yaml diff --git a/federated_learning/yolov8.yaml b/federated_learning/yolov8.yaml new file mode 100644 index 0000000..c83adaf --- /dev/null +++ b/federated_learning/yolov8.yaml @@ -0,0 +1,49 @@ +# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license + +# Ultralytics YOLOv8 object detection model with P3/8 - P5/32 outputs +# Model docs: https://docs.ultralytics.com/models/yolov8 +# Task docs: https://docs.ultralytics.com/tasks/detect + +# Parameters +nc: 1 # number of classes +scales: # model compound scaling constants, i.e. 'model=yolov8n.yaml' will call yolov8.yaml with scale 'n' + # [depth, width, max_channels] + n: [0.33, 0.25, 1024] # YOLOv8n summary: 129 layers, 3157200 parameters, 3157184 gradients, 8.9 GFLOPS + s: [0.33, 0.50, 1024] # YOLOv8s summary: 129 layers, 11166560 parameters, 11166544 gradients, 28.8 GFLOPS + m: [0.67, 0.75, 768] # YOLOv8m summary: 169 layers, 25902640 parameters, 25902624 gradients, 79.3 GFLOPS + l: [1.00, 1.00, 512] # YOLOv8l summary: 209 layers, 43691520 parameters, 43691504 gradients, 165.7 GFLOPS + x: [1.00, 1.25, 512] # YOLOv8x summary: 209 layers, 68229648 parameters, 68229632 gradients, 258.5 GFLOPS + +# YOLOv8.0n backbone +backbone: + # [from, repeats, module, args] + - [-1, 1, Conv, [64, 3, 2]] # 0-P1/2 + - [-1, 1, Conv, [128, 3, 2]] # 1-P2/4 + - [-1, 3, C2f, [128, True]] + - [-1, 1, Conv, [256, 3, 2]] # 3-P3/8 + - [-1, 6, C2f, [256, True]] + - [-1, 1, Conv, [512, 3, 2]] # 5-P4/16 + - [-1, 6, C2f, [512, True]] + - [-1, 1, Conv, [1024, 3, 2]] # 7-P5/32 + - [-1, 3, C2f, [1024, True]] + - [-1, 1, SPPF, [1024, 5]] # 9 + +# YOLOv8.0n head +head: + - [-1, 1, nn.Upsample, [None, 2, "nearest"]] + - [[-1, 6], 1, Concat, [1]] # cat backbone P4 + - [-1, 3, C2f, [512]] # 12 + + - [-1, 1, nn.Upsample, [None, 2, "nearest"]] + - [[-1, 4], 1, Concat, [1]] # cat backbone P3 + - [-1, 3, C2f, [256]] # 15 (P3/8-small) + + - [-1, 1, Conv, [256, 3, 2]] + - [[-1, 12], 1, Concat, [1]] # cat head P4 + - [-1, 3, C2f, [512]] # 18 (P4/16-medium) + + - [-1, 1, Conv, [512, 3, 2]] + - [[-1, 9], 1, Concat, [1]] # cat head P5 + - [-1, 3, C2f, [1024]] # 21 (P5/32-large) + + - [[15, 18, 21], 1, Detect, [nc]] # Detect(P3, P4, P5) \ No newline at end of file