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YOLOv5 model architecture overview #4518
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@dariogonle we've made visualizing YOLOv5 🚀 architectures super easy. There are two main ways:
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# YOLOv5 backbone | |
backbone: | |
# [from, number, module, args] | |
[[-1, 1, Focus, [64, 3]], # 0-P1/2 | |
[-1, 1, Conv, [128, 3, 2]], # 1-P2/4 | |
[-1, 3, C3, [128]], | |
[-1, 1, Conv, [256, 3, 2]], # 3-P3/8 | |
[-1, 9, C3, [256]], | |
[-1, 1, Conv, [512, 3, 2]], # 5-P4/16 | |
[-1, 9, C3, [512]], | |
[-1, 1, Conv, [1024, 3, 2]], # 7-P5/32 | |
[-1, 1, SPP, [1024, [5, 9, 13]]], | |
[-1, 3, C3, [1024, False]], # 9 | |
] | |
# YOLOv5 head | |
head: | |
[[-1, 1, Conv, [512, 1, 1]], | |
[-1, 1, nn.Upsample, [None, 2, 'nearest']], | |
[[-1, 6], 1, Concat, [1]], # cat backbone P4 | |
[-1, 3, C3, [512, False]], # 13 | |
[-1, 1, Conv, [256, 1, 1]], | |
[-1, 1, nn.Upsample, [None, 2, 'nearest']], | |
[[-1, 4], 1, Concat, [1]], # cat backbone P3 | |
[-1, 3, C3, [256, False]], # 17 (P3/8-small) | |
[-1, 1, Conv, [256, 3, 2]], | |
[[-1, 14], 1, Concat, [1]], # cat head P4 | |
[-1, 3, C3, [512, False]], # 20 (P4/16-medium) | |
[-1, 1, Conv, [512, 3, 2]], | |
[[-1, 10], 1, Concat, [1]], # cat head P5 | |
[-1, 3, C3, [1024, False]], # 23 (P5/32-large) | |
[[17, 20, 23], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5) | |
] |
TensorBoard Graph
Simply start training a model, and then view the TensorBoard Graph for an interactive view of the model architecture. This example shows YOLOv5s viewed in our Notebook –
# Tensorboard
%load_ext tensorboard
%tensorboard --logdir runs/train
# Train YOLOv5s on COCO128 for 3 epochs
python train.py --weights yolov5s.pt --epochs 3
That‘s cool. I like it! |
👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs. Access additional YOLOv5 🚀 resources:
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Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed! Thank you for your contributions to YOLOv5 🚀 and Vision AI ⭐! |
❔Question
Is this architecture overview, mentionated in #280, still valid?
Additional context
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