`ultralytics 8.0.223` add YOLOv8-Ghost P2 and P6 variants (#6826)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: Burhan <62214284+Burhan-Q@users.noreply.github.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com> Co-authored-by: Awsome <1579093407@qq.com>pull/6830/head v8.0.223
Glenn Jocher
11 months ago
committed by
GitHub
parent
742cbc1b4e
commit
d74a5a9499
20 changed files with 153 additions and 16 deletions
@ -0,0 +1,54 @@ |
||||
# Ultralytics YOLO 🚀, AGPL-3.0 license |
||||
# YOLOv8 object detection model with P2-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect |
||||
|
||||
# Parameters |
||||
nc: 80 # 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-ghost-p2 summary: 491 layers, 2033944 parameters, 2033928 gradients, 13.8 GFLOPs |
||||
s: [0.33, 0.50, 1024] # YOLOv8s-ghost-p2 summary: 491 layers, 5562080 parameters, 5562064 gradients, 25.1 GFLOPs |
||||
m: [0.67, 0.75, 768] # YOLOv8m-ghost-p2 summary: 731 layers, 9031728 parameters, 9031712 gradients, 42.8 GFLOPs |
||||
l: [1.00, 1.00, 512] # YOLOv8l-ghost-p2 summary: 971 layers, 12214448 parameters, 12214432 gradients, 69.1 GFLOPs |
||||
x: [1.00, 1.25, 512] # YOLOv8x-ghost-p2 summary: 971 layers, 18664776 parameters, 18664760 gradients, 103.3 GFLOPs |
||||
|
||||
# YOLOv8.0-ghost backbone |
||||
backbone: |
||||
# [from, repeats, module, args] |
||||
- [-1, 1, Conv, [64, 3, 2]] # 0-P1/2 |
||||
- [-1, 1, GhostConv, [128, 3, 2]] # 1-P2/4 |
||||
- [-1, 3, C3Ghost, [128, True]] |
||||
- [-1, 1, GhostConv, [256, 3, 2]] # 3-P3/8 |
||||
- [-1, 6, C3Ghost, [256, True]] |
||||
- [-1, 1, GhostConv, [512, 3, 2]] # 5-P4/16 |
||||
- [-1, 6, C3Ghost, [512, True]] |
||||
- [-1, 1, GhostConv, [1024, 3, 2]] # 7-P5/32 |
||||
- [-1, 3, C3Ghost, [1024, True]] |
||||
- [-1, 1, SPPF, [1024, 5]] # 9 |
||||
|
||||
# YOLOv8.0-ghost-p2 head |
||||
head: |
||||
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] |
||||
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 |
||||
- [-1, 3, C3Ghost, [512]] # 12 |
||||
|
||||
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] |
||||
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 |
||||
- [-1, 3, C3Ghost, [256]] # 15 (P3/8-small) |
||||
|
||||
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] |
||||
- [[-1, 2], 1, Concat, [1]] # cat backbone P2 |
||||
- [-1, 3, C3Ghost, [128]] # 18 (P2/4-xsmall) |
||||
|
||||
- [-1, 1, GhostConv, [128, 3, 2]] |
||||
- [[-1, 15], 1, Concat, [1]] # cat head P3 |
||||
- [-1, 3, C3Ghost, [256]] # 21 (P3/8-small) |
||||
|
||||
- [-1, 1, GhostConv, [256, 3, 2]] |
||||
- [[-1, 12], 1, Concat, [1]] # cat head P4 |
||||
- [-1, 3, C3Ghost, [512]] # 24 (P4/16-medium) |
||||
|
||||
- [-1, 1, GhostConv, [512, 3, 2]] |
||||
- [[-1, 9], 1, Concat, [1]] # cat head P5 |
||||
- [-1, 3, C3Ghost, [1024]] # 27 (P5/32-large) |
||||
|
||||
- [[18, 21, 24, 27], 1, Detect, [nc]] # Detect(P2, P3, P4, P5) |
||||
@ -0,0 +1,56 @@ |
||||
# Ultralytics YOLO 🚀, AGPL-3.0 license |
||||
# YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect |
||||
|
||||
# Parameters |
||||
nc: 80 # number of classes |
||||
scales: # model compound scaling constants, i.e. 'model=yolov8n-p6.yaml' will call yolov8-p6.yaml with scale 'n' |
||||
# [depth, width, max_channels] |
||||
n: [0.33, 0.25, 1024] # YOLOv8n-ghost-p6 summary: 529 layers, 2901100 parameters, 2901084 gradients, 5.8 GFLOPs |
||||
s: [0.33, 0.50, 1024] # YOLOv8s-ghost-p6 summary: 529 layers, 9520008 parameters, 9519992 gradients, 16.4 GFLOPs |
||||
m: [0.67, 0.75, 768] # YOLOv8m-ghost-p6 summary: 789 layers, 18002904 parameters, 18002888 gradients, 34.4 GFLOPs |
||||
l: [1.00, 1.00, 512] # YOLOv8l-ghost-p6 summary: 1049 layers, 21227584 parameters, 21227568 gradients, 55.3 GFLOPs |
||||
x: [1.00, 1.25, 512] # YOLOv8x-ghost-p6 summary: 1049 layers, 33057852 parameters, 33057836 gradients, 85.7 GFLOPs |
||||
|
||||
# YOLOv8.0-ghost backbone |
||||
backbone: |
||||
# [from, repeats, module, args] |
||||
- [-1, 1, Conv, [64, 3, 2]] # 0-P1/2 |
||||
- [-1, 1, GhostConv, [128, 3, 2]] # 1-P2/4 |
||||
- [-1, 3, C3Ghost, [128, True]] |
||||
- [-1, 1, GhostConv, [256, 3, 2]] # 3-P3/8 |
||||
- [-1, 6, C3Ghost, [256, True]] |
||||
- [-1, 1, GhostConv, [512, 3, 2]] # 5-P4/16 |
||||
- [-1, 6, C3Ghost, [512, True]] |
||||
- [-1, 1, GhostConv, [768, 3, 2]] # 7-P5/32 |
||||
- [-1, 3, C3Ghost, [768, True]] |
||||
- [-1, 1, GhostConv, [1024, 3, 2]] # 9-P6/64 |
||||
- [-1, 3, C3Ghost, [1024, True]] |
||||
- [-1, 1, SPPF, [1024, 5]] # 11 |
||||
|
||||
# YOLOv8.0-ghost-p6 head |
||||
head: |
||||
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] |
||||
- [[-1, 8], 1, Concat, [1]] # cat backbone P5 |
||||
- [-1, 3, C3Ghost, [768]] # 14 |
||||
|
||||
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] |
||||
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 |
||||
- [-1, 3, C3Ghost, [512]] # 17 |
||||
|
||||
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] |
||||
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 |
||||
- [-1, 3, C3Ghost, [256]] # 20 (P3/8-small) |
||||
|
||||
- [-1, 1, GhostConv, [256, 3, 2]] |
||||
- [[-1, 17], 1, Concat, [1]] # cat head P4 |
||||
- [-1, 3, C3Ghost, [512]] # 23 (P4/16-medium) |
||||
|
||||
- [-1, 1, GhostConv, [512, 3, 2]] |
||||
- [[-1, 14], 1, Concat, [1]] # cat head P5 |
||||
- [-1, 3, C3Ghost, [768]] # 26 (P5/32-large) |
||||
|
||||
- [-1, 1, GhostConv, [768, 3, 2]] |
||||
- [[-1, 11], 1, Concat, [1]] # cat head P6 |
||||
- [-1, 3, C3Ghost, [1024]] # 29 (P6/64-xlarge) |
||||
|
||||
- [[20, 23, 26, 29], 1, Detect, [nc]] # Detect(P3, P4, P5, P6) |
||||
Loading…
Reference in new issue