YAML reformat (#7669)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Glenn Jocher 2024-01-18 19:33:12 +01:00 committed by GitHub
parent d021524e85
commit 63e7db1dac
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55 changed files with 725 additions and 756 deletions

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@ -9,27 +9,27 @@ on:
pull_request: pull_request:
branches: [main] branches: [main]
schedule: schedule:
- cron: '0 0 * * *' # runs at 00:00 UTC every day - cron: "0 0 * * *" # runs at 00:00 UTC every day
workflow_dispatch: workflow_dispatch:
inputs: inputs:
hub: hub:
description: 'Run HUB' description: "Run HUB"
default: false default: false
type: boolean type: boolean
benchmarks: benchmarks:
description: 'Run Benchmarks' description: "Run Benchmarks"
default: false default: false
type: boolean type: boolean
tests: tests:
description: 'Run Tests' description: "Run Tests"
default: false default: false
type: boolean type: boolean
gpu: gpu:
description: 'Run GPU' description: "Run GPU"
default: false default: false
type: boolean type: boolean
conda: conda:
description: 'Run Conda' description: "Run Conda"
default: false default: false
type: boolean type: boolean
@ -41,13 +41,13 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
os: [ubuntu-latest] os: [ubuntu-latest]
python-version: ['3.11'] python-version: ["3.11"]
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
- uses: actions/setup-python@v5 - uses: actions/setup-python@v5
with: with:
python-version: ${{ matrix.python-version }} python-version: ${{ matrix.python-version }}
cache: 'pip' # caching pip dependencies cache: "pip" # caching pip dependencies
- name: Install requirements - name: Install requirements
shell: bash # for Windows compatibility shell: bash # for Windows compatibility
run: | run: |
@ -95,14 +95,14 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
os: [ubuntu-latest] os: [ubuntu-latest]
python-version: ['3.11'] python-version: ["3.11"]
model: [yolov8n] model: [yolov8n]
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
- uses: actions/setup-python@v5 - uses: actions/setup-python@v5
with: with:
python-version: ${{ matrix.python-version }} python-version: ${{ matrix.python-version }}
cache: 'pip' # caching pip dependencies cache: "pip" # caching pip dependencies
- name: Install requirements - name: Install requirements
shell: bash # for Windows compatibility shell: bash # for Windows compatibility
run: | run: |
@ -150,21 +150,22 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
os: [ubuntu-latest] os: [ubuntu-latest]
python-version: ['3.11'] python-version: ["3.11"]
torch: [latest] torch: [latest]
include: include:
- os: ubuntu-latest - os: ubuntu-latest
python-version: '3.8' # torch 1.8.0 requires python >=3.6, <=3.8 python-version: "3.8" # torch 1.8.0 requires python >=3.6, <=3.8
torch: '1.8.0' # min torch version CI https://pypi.org/project/torchvision/ torch: "1.8.0" # min torch version CI https://pypi.org/project/torchvision/
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
- uses: actions/setup-python@v5 - uses: actions/setup-python@v5
with: with:
python-version: ${{ matrix.python-version }} python-version: ${{ matrix.python-version }}
cache: 'pip' # caching pip dependencies cache: "pip" # caching pip dependencies
- name: Install requirements - name: Install requirements
shell: bash # for Windows compatibility shell: bash # for Windows compatibility
run: | # CoreML must be installed before export due to protobuf error from AutoInstall run: |
# CoreML must be installed before export due to protobuf error from AutoInstall
python -m pip install --upgrade pip wheel python -m pip install --upgrade pip wheel
torch="" torch=""
if [ "${{ matrix.torch }}" == "1.8.0" ]; then if [ "${{ matrix.torch }}" == "1.8.0" ]; then
@ -220,7 +221,7 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
os: [ubuntu-latest] os: [ubuntu-latest]
python-version: ['3.11'] python-version: ["3.11"]
defaults: defaults:
run: run:
shell: bash -el {0} shell: bash -el {0}

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@ -24,14 +24,14 @@ jobs:
# must be repository secret token # must be repository secret token
PERSONAL_ACCESS_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }} PERSONAL_ACCESS_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }}
with: with:
path-to-signatures: 'signatures/version1/cla.json' path-to-signatures: "signatures/version1/cla.json"
path-to-document: 'https://docs.ultralytics.com/help/CLA' # CLA document path-to-document: "https://docs.ultralytics.com/help/CLA" # CLA document
# branch should not be protected # branch should not be protected
branch: 'main' branch: "main"
allowlist: dependabot[bot],github-actions,[pre-commit*,pre-commit*,bot* allowlist: dependabot[bot],github-actions,[pre-commit*,pre-commit*,bot*
remote-organization-name: ultralytics remote-organization-name: ultralytics
remote-repository-name: cla remote-repository-name: cla
custom-pr-sign-comment: 'I have read the CLA Document and I sign the CLA' custom-pr-sign-comment: "I have read the CLA Document and I sign the CLA"
custom-allsigned-prcomment: All Contributors have signed the CLA. ✅ custom-allsigned-prcomment: All Contributors have signed the CLA. ✅
#custom-notsigned-prcomment: 'pull request comment with Introductory message to ask new contributors to sign' #custom-notsigned-prcomment: 'pull request comment with Introductory message to ask new contributors to sign'

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@ -4,7 +4,7 @@ name: "CodeQL"
on: on:
schedule: schedule:
- cron: '0 0 1 * *' - cron: "0 0 1 * *"
workflow_dispatch: workflow_dispatch:
jobs: jobs:
@ -19,7 +19,7 @@ jobs:
strategy: strategy:
fail-fast: false fail-fast: false
matrix: matrix:
language: ['python'] language: ["python"]
# CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python', 'ruby' ] # CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python', 'ruby' ]
steps: steps:

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@ -12,7 +12,7 @@ name: Check Broken links
on: on:
workflow_dispatch: workflow_dispatch:
schedule: schedule:
- cron: '0 0 * * *' # runs at 00:00 UTC every day - cron: "0 0 * * *" # runs at 00:00 UTC every day
jobs: jobs:
Links: Links:

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@ -28,8 +28,8 @@ jobs:
- name: Set up Python environment - name: Set up Python environment
uses: actions/setup-python@v5 uses: actions/setup-python@v5
with: with:
python-version: '3.11' python-version: "3.11"
cache: 'pip' # caching pip dependencies cache: "pip" # caching pip dependencies
- name: Install dependencies - name: Install dependencies
run: | run: |
python -m pip install --upgrade pip wheel build twine python -m pip install --upgrade pip wheel build twine

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@ -3,7 +3,7 @@
name: Close stale issues name: Close stale issues
on: on:
schedule: schedule:
- cron: '0 0 * * *' # Runs at 00:00 UTC every day - cron: "0 0 * * *" # Runs at 00:00 UTC every day
jobs: jobs:
stale: stale:
@ -43,5 +43,5 @@ jobs:
days-before-issue-close: 10 days-before-issue-close: 10
days-before-pr-stale: 90 days-before-pr-stale: 90
days-before-pr-close: 30 days-before-pr-close: 30
exempt-issue-labels: 'documentation,tutorial,TODO' exempt-issue-labels: "documentation,tutorial,TODO"
operations-per-run: 300 # The maximum number of operations per run, used to control rate limiting. operations-per-run: 300 # The maximum number of operations per run, used to control rate limiting.

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@ -5,7 +5,7 @@
# Define bot property if installed via https://github.com/marketplace/pre-commit-ci # Define bot property if installed via https://github.com/marketplace/pre-commit-ci
ci: ci:
autofix_prs: true autofix_prs: true
autoupdate_commit_msg: '[pre-commit.ci] pre-commit suggestions' autoupdate_commit_msg: "[pre-commit.ci] pre-commit suggestions"
autoupdate_schedule: monthly autoupdate_schedule: monthly
submodules: true submodules: true
@ -55,7 +55,7 @@ repos:
rev: v2.2.6 rev: v2.2.6
hooks: hooks:
- id: codespell - id: codespell
exclude: 'docs/de|docs/fr|docs/pt|docs/es|docs/mkdocs_de.yml' exclude: "docs/de|docs/fr|docs/pt|docs/es|docs/mkdocs_de.yml"
args: args:
- --ignore-words-list=crate,nd,ned,strack,dota,ane,segway,fo,gool,winn,commend,bloc,nam,afterall - --ignore-words-list=crate,nd,ned,strack,dota,ane,segway,fo,gool,winn,commend,bloc,nam,afterall
@ -64,7 +64,7 @@ repos:
hooks: hooks:
- id: pycln - id: pycln
args: [--all] args: [--all]
#
# - repo: https://github.com/PyCQA/docformatter # - repo: https://github.com/PyCQA/docformatter
# rev: v1.7.5 # rev: v1.7.5
# hooks: # hooks:

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── Argoverse ← downloads here (31.5 GB) # └── Argoverse ← downloads here (31.5 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/Argoverse # dataset root dir path: ../datasets/Argoverse # dataset root dir
train: Argoverse-1.1/images/train/ # train images (relative to 'path') 39384 images train: Argoverse-1.1/images/train/ # train images (relative to 'path') 39384 images
@ -25,7 +24,6 @@ names:
6: traffic_light 6: traffic_light
7: stop_sign 7: stop_sign
# Download script/URL (optional) --------------------------------------------------------------------------------------- # Download script/URL (optional) ---------------------------------------------------------------------------------------
download: | download: |
import json import json

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── GlobalWheat2020 ← downloads here (7.0 GB) # └── GlobalWheat2020 ← downloads here (7.0 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/GlobalWheat2020 # dataset root dir path: ../datasets/GlobalWheat2020 # dataset root dir
train: # train images (relative to 'path') 3422 images train: # train images (relative to 'path') 3422 images
@ -30,7 +29,6 @@ test: # test images (optional) 1276 images
names: names:
0: wheat_head 0: wheat_head
# Download script/URL (optional) --------------------------------------------------------------------------------------- # Download script/URL (optional) ---------------------------------------------------------------------------------------
download: | download: |
from ultralytics.utils.downloads import download from ultralytics.utils.downloads import download

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@ -8,7 +8,6 @@
# └── datasets # └── datasets
# └── imagenet ← downloads here (144 GB) # └── imagenet ← downloads here (144 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/imagenet # dataset root dir path: ../datasets/imagenet # dataset root dir
train: train # train images (relative to 'path') 1281167 images train: train # train images (relative to 'path') 1281167 images
@ -2021,6 +2020,5 @@ map:
n13133613: ear n13133613: ear
n15075141: toilet_tissue n15075141: toilet_tissue
# Download script/URL (optional) # Download script/URL (optional)
download: yolo/data/scripts/get_imagenet.sh download: yolo/data/scripts/get_imagenet.sh

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── Objects365 ← downloads here (712 GB = 367G data + 345G zips) # └── Objects365 ← downloads here (712 GB = 367G data + 345G zips)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/Objects365 # dataset root dir path: ../datasets/Objects365 # dataset root dir
train: images/train # train images (relative to 'path') 1742289 images train: images/train # train images (relative to 'path') 1742289 images
@ -382,7 +381,6 @@ names:
363: Curling 363: Curling
364: Table Tennis 364: Table Tennis
# Download script/URL (optional) --------------------------------------------------------------------------------------- # Download script/URL (optional) ---------------------------------------------------------------------------------------
download: | download: |
from tqdm import tqdm from tqdm import tqdm

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── SKU-110K ← downloads here (13.6 GB) # └── SKU-110K ← downloads here (13.6 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/SKU-110K # dataset root dir path: ../datasets/SKU-110K # dataset root dir
train: train.txt # train images (relative to 'path') 8219 images train: train.txt # train images (relative to 'path') 8219 images
@ -18,7 +17,6 @@ test: test.txt # test images (optional) 2936 images
names: names:
0: object 0: object
# Download script/URL (optional) --------------------------------------------------------------------------------------- # Download script/URL (optional) ---------------------------------------------------------------------------------------
download: | download: |
import shutil import shutil

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── VOC ← downloads here (2.8 GB) # └── VOC ← downloads here (2.8 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/VOC path: ../datasets/VOC
train: # train images (relative to 'path') 16551 images train: # train images (relative to 'path') 16551 images
@ -43,7 +42,6 @@ names:
18: train 18: train
19: tvmonitor 19: tvmonitor
# Download script/URL (optional) --------------------------------------------------------------------------------------- # Download script/URL (optional) ---------------------------------------------------------------------------------------
download: | download: |
import xml.etree.ElementTree as ET import xml.etree.ElementTree as ET

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── VisDrone ← downloads here (2.3 GB) # └── VisDrone ← downloads here (2.3 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/VisDrone # dataset root dir path: ../datasets/VisDrone # dataset root dir
train: VisDrone2019-DET-train/images # train images (relative to 'path') 6471 images train: VisDrone2019-DET-train/images # train images (relative to 'path') 6471 images
@ -27,7 +26,6 @@ names:
8: bus 8: bus
9: motor 9: motor
# Download script/URL (optional) --------------------------------------------------------------------------------------- # Download script/URL (optional) ---------------------------------------------------------------------------------------
download: | download: |
import os import os

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── coco-pose ← downloads here (20.1 GB) # └── coco-pose ← downloads here (20.1 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco-pose # dataset root dir path: ../datasets/coco-pose # dataset root dir
train: train2017.txt # train images (relative to 'path') 118287 images train: train2017.txt # train images (relative to 'path') 118287 images

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── coco ← downloads here (20.1 GB) # └── coco ← downloads here (20.1 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco # dataset root dir path: ../datasets/coco # dataset root dir
train: train2017.txt # train images (relative to 'path') 118287 images train: train2017.txt # train images (relative to 'path') 118287 images
@ -97,7 +96,6 @@ names:
78: hair drier 78: hair drier
79: toothbrush 79: toothbrush
# Download script/URL (optional) # Download script/URL (optional)
download: | download: |
from ultralytics.utils.downloads import download from ultralytics.utils.downloads import download

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── coco128-seg ← downloads here (7 MB) # └── coco128-seg ← downloads here (7 MB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco128-seg # dataset root dir path: ../datasets/coco128-seg # dataset root dir
train: images/train2017 # train images (relative to 'path') 128 images train: images/train2017 # train images (relative to 'path') 128 images
@ -97,6 +96,5 @@ names:
78: hair drier 78: hair drier
79: toothbrush 79: toothbrush
# Download script/URL (optional) # Download script/URL (optional)
download: https://ultralytics.com/assets/coco128-seg.zip download: https://ultralytics.com/assets/coco128-seg.zip

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── coco128 ← downloads here (7 MB) # └── coco128 ← downloads here (7 MB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco128 # dataset root dir path: ../datasets/coco128 # dataset root dir
train: images/train2017 # train images (relative to 'path') 128 images train: images/train2017 # train images (relative to 'path') 128 images
@ -97,6 +96,5 @@ names:
78: hair drier 78: hair drier
79: toothbrush 79: toothbrush
# Download script/URL (optional) # Download script/URL (optional)
download: https://ultralytics.com/assets/coco128.zip download: https://ultralytics.com/assets/coco128.zip

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── coco8-pose ← downloads here (1 MB) # └── coco8-pose ← downloads here (1 MB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco8-pose # dataset root dir path: ../datasets/coco8-pose # dataset root dir
train: images/train # train images (relative to 'path') 4 images train: images/train # train images (relative to 'path') 4 images

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── coco8-seg ← downloads here (1 MB) # └── coco8-seg ← downloads here (1 MB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco8-seg # dataset root dir path: ../datasets/coco8-seg # dataset root dir
train: images/train # train images (relative to 'path') 4 images train: images/train # train images (relative to 'path') 4 images
@ -97,6 +96,5 @@ names:
78: hair drier 78: hair drier
79: toothbrush 79: toothbrush
# Download script/URL (optional) # Download script/URL (optional)
download: https://ultralytics.com/assets/coco8-seg.zip download: https://ultralytics.com/assets/coco8-seg.zip

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── coco8 ← downloads here (1 MB) # └── coco8 ← downloads here (1 MB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco8 # dataset root dir path: ../datasets/coco8 # dataset root dir
train: images/train # train images (relative to 'path') 4 images train: images/train # train images (relative to 'path') 4 images
@ -97,6 +96,5 @@ names:
78: hair drier 78: hair drier
79: toothbrush 79: toothbrush
# Download script/URL (optional) # Download script/URL (optional)
download: https://ultralytics.com/assets/coco8.zip download: https://ultralytics.com/assets/coco8.zip

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── open-images-v7 ← downloads here (561 GB) # └── open-images-v7 ← downloads here (561 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/open-images-v7 # dataset root dir path: ../datasets/open-images-v7 # dataset root dir
train: images/train # train images (relative to 'path') 1743042 images train: images/train # train images (relative to 'path') 1743042 images
@ -618,7 +617,6 @@ names:
599: Zebra 599: Zebra
600: Zucchini 600: Zucchini
# Download script/URL (optional) --------------------------------------------------------------------------------------- # Download script/URL (optional) ---------------------------------------------------------------------------------------
download: | download: |
from ultralytics.utils import LOGGER, SETTINGS, Path, is_ubuntu, get_ubuntu_version from ultralytics.utils import LOGGER, SETTINGS, Path, is_ubuntu, get_ubuntu_version

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@ -7,7 +7,6 @@
# └── datasets # └── datasets
# └── tiger-pose ← downloads here (75.3 MB) # └── tiger-pose ← downloads here (75.3 MB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/tiger-pose # dataset root dir path: ../datasets/tiger-pose # dataset root dir
train: train # train images (relative to 'path') 210 images train: train # train images (relative to 'path') 210 images

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@ -8,7 +8,6 @@
# └── datasets # └── datasets
# └── xView ← downloads here (20.7 GB) # └── xView ← downloads here (20.7 GB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/xView # dataset root dir path: ../datasets/xView # dataset root dir
train: images/autosplit_train.txt # train images (relative to 'path') 90% of 847 train images train: images/autosplit_train.txt # train images (relative to 'path') 90% of 847 train images
@ -77,7 +76,6 @@ names:
58: Pylon 58: Pylon
59: Tower 59: Tower
# Download script/URL (optional) --------------------------------------------------------------------------------------- # Download script/URL (optional) ---------------------------------------------------------------------------------------
download: | download: |
import json import json

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@ -28,13 +28,13 @@ head:
- [-1, 1, AIFI, [1024, 8]] - [-1, 1, AIFI, [1024, 8]]
- [-1, 1, Conv, [256, 1, 1]] # 12, Y5, lateral_convs.0 - [-1, 1, Conv, [256, 1, 1]] # 12, Y5, lateral_convs.0
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [7, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 14 input_proj.1 - [7, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 14 input_proj.1
- [[-2, -1], 1, Concat, [1]] - [[-2, -1], 1, Concat, [1]]
- [-1, 3, RepC3, [256]] # 16, fpn_blocks.0 - [-1, 3, RepC3, [256]] # 16, fpn_blocks.0
- [-1, 1, Conv, [256, 1, 1]] # 17, Y4, lateral_convs.1 - [-1, 1, Conv, [256, 1, 1]] # 17, Y4, lateral_convs.1
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [3, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 19 input_proj.0 - [3, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 19 input_proj.0
- [[-2, -1], 1, Concat, [1]] # cat backbone P4 - [[-2, -1], 1, Concat, [1]] # cat backbone P4
- [-1, 3, RepC3, [256]] # X3 (21), fpn_blocks.1 - [-1, 3, RepC3, [256]] # X3 (21), fpn_blocks.1

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@ -20,13 +20,13 @@ head:
- [-1, 1, AIFI, [1024, 8]] - [-1, 1, AIFI, [1024, 8]]
- [-1, 1, Conv, [256, 1, 1]] # 7 - [-1, 1, Conv, [256, 1, 1]] # 7
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [3, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 9 - [3, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 9
- [[-2, -1], 1, Concat, [1]] - [[-2, -1], 1, Concat, [1]]
- [-1, 3, RepC3, [256]] # 11 - [-1, 3, RepC3, [256]] # 11
- [-1, 1, Conv, [256, 1, 1]] # 12 - [-1, 1, Conv, [256, 1, 1]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [2, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 14 - [2, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 14
- [[-2, -1], 1, Concat, [1]] # cat backbone P4 - [[-2, -1], 1, Concat, [1]] # cat backbone P4
- [-1, 3, RepC3, [256]] # X3 (16), fpn_blocks.1 - [-1, 3, RepC3, [256]] # X3 (16), fpn_blocks.1

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@ -20,13 +20,13 @@ head:
- [-1, 1, AIFI, [1024, 8]] - [-1, 1, AIFI, [1024, 8]]
- [-1, 1, Conv, [256, 1, 1]] # 7 - [-1, 1, Conv, [256, 1, 1]] # 7
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [3, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 9 - [3, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 9
- [[-2, -1], 1, Concat, [1]] - [[-2, -1], 1, Concat, [1]]
- [-1, 3, RepC3, [256]] # 11 - [-1, 3, RepC3, [256]] # 11
- [-1, 1, Conv, [256, 1, 1]] # 12 - [-1, 1, Conv, [256, 1, 1]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [2, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 14 - [2, 1, Conv, [256, 1, 1, None, 1, 1, False]] # 14
- [[-2, -1], 1, Concat, [1]] # cat backbone P4 - [[-2, -1], 1, Concat, [1]] # cat backbone P4
- [-1, 3, RepC3, [256]] # X3 (16), fpn_blocks.1 - [-1, 3, RepC3, [256]] # X3 (16), fpn_blocks.1

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@ -32,13 +32,13 @@ head:
- [-1, 1, AIFI, [2048, 8]] - [-1, 1, AIFI, [2048, 8]]
- [-1, 1, Conv, [384, 1, 1]] # 16, Y5, lateral_convs.0 - [-1, 1, Conv, [384, 1, 1]] # 16, Y5, lateral_convs.0
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [10, 1, Conv, [384, 1, 1, None, 1, 1, False]] # 18 input_proj.1 - [10, 1, Conv, [384, 1, 1, None, 1, 1, False]] # 18 input_proj.1
- [[-2, -1], 1, Concat, [1]] - [[-2, -1], 1, Concat, [1]]
- [-1, 3, RepC3, [384]] # 20, fpn_blocks.0 - [-1, 3, RepC3, [384]] # 20, fpn_blocks.0
- [-1, 1, Conv, [384, 1, 1]] # 21, Y4, lateral_convs.1 - [-1, 1, Conv, [384, 1, 1]] # 21, Y4, lateral_convs.1
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [4, 1, Conv, [384, 1, 1, None, 1, 1, False]] # 23 input_proj.0 - [4, 1, Conv, [384, 1, 1, None, 1, 1, False]] # 23 input_proj.0
- [[-2, -1], 1, Concat, [1]] # cat backbone P4 - [[-2, -1], 1, Concat, [1]] # cat backbone P4
- [-1, 3, RepC3, [384]] # X3 (25), fpn_blocks.1 - [-1, 3, RepC3, [384]] # X3 (25), fpn_blocks.1

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@ -30,7 +30,7 @@ head:
- [-1, 1, Conv, [1024, 3, 1]] # 15 (P5/32-large) - [-1, 1, Conv, [1024, 3, 1]] # 15 (P5/32-large)
- [-2, 1, Conv, [256, 1, 1]] - [-2, 1, Conv, [256, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 8], 1, Concat, [1]] # cat backbone P4 - [[-1, 8], 1, Concat, [1]] # cat backbone P4
- [-1, 1, Bottleneck, [512, False]] - [-1, 1, Bottleneck, [512, False]]
- [-1, 1, Bottleneck, [512, False]] - [-1, 1, Bottleneck, [512, False]]
@ -38,7 +38,7 @@ head:
- [-1, 1, Conv, [512, 3, 1]] # 22 (P4/16-medium) - [-1, 1, Conv, [512, 3, 1]] # 22 (P4/16-medium)
- [-2, 1, Conv, [128, 1, 1]] - [-2, 1, Conv, [128, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P3 - [[-1, 6], 1, Concat, [1]] # cat backbone P3
- [-1, 1, Bottleneck, [256, False]] - [-1, 1, Bottleneck, [256, False]]
- [-1, 2, Bottleneck, [256, False]] # 27 (P3/8-small) - [-1, 2, Bottleneck, [256, False]] # 27 (P3/8-small)

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@ -30,7 +30,7 @@ head:
- [-1, 1, Conv, [512, 3, 1]] # 15 (P5/32-large) - [-1, 1, Conv, [512, 3, 1]] # 15 (P5/32-large)
- [-2, 1, Conv, [128, 1, 1]] - [-2, 1, Conv, [128, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 8], 1, Concat, [1]] # cat backbone P4 - [[-1, 8], 1, Concat, [1]] # cat backbone P4
- [-1, 1, Conv, [256, 3, 1]] # 19 (P4/16-medium) - [-1, 1, Conv, [256, 3, 1]] # 19 (P4/16-medium)

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@ -30,7 +30,7 @@ head:
- [-1, 1, Conv, [1024, 3, 1]] # 15 (P5/32-large) - [-1, 1, Conv, [1024, 3, 1]] # 15 (P5/32-large)
- [-2, 1, Conv, [256, 1, 1]] - [-2, 1, Conv, [256, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 8], 1, Concat, [1]] # cat backbone P4 - [[-1, 8], 1, Concat, [1]] # cat backbone P4
- [-1, 1, Bottleneck, [512, False]] - [-1, 1, Bottleneck, [512, False]]
- [-1, 1, Bottleneck, [512, False]] - [-1, 1, Bottleneck, [512, False]]
@ -38,7 +38,7 @@ head:
- [-1, 1, Conv, [512, 3, 1]] # 22 (P4/16-medium) - [-1, 1, Conv, [512, 3, 1]] # 22 (P4/16-medium)
- [-2, 1, Conv, [128, 1, 1]] - [-2, 1, Conv, [128, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P3 - [[-1, 6], 1, Concat, [1]] # cat backbone P3
- [-1, 1, Bottleneck, [256, False]] - [-1, 1, Bottleneck, [256, False]]
- [-1, 2, Bottleneck, [256, False]] # 27 (P3/8-small) - [-1, 2, Bottleneck, [256, False]] # 27 (P3/8-small)

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@ -30,17 +30,17 @@ backbone:
# YOLOv5 v6.0 head # YOLOv5 v6.0 head
head: head:
- [-1, 1, Conv, [768, 1, 1]] - [-1, 1, Conv, [768, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 8], 1, Concat, [1]] # cat backbone P5 - [[-1, 8], 1, Concat, [1]] # cat backbone P5
- [-1, 3, C3, [768, False]] # 15 - [-1, 3, C3, [768, False]] # 15
- [-1, 1, Conv, [512, 1, 1]] - [-1, 1, Conv, [512, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C3, [512, False]] # 19 - [-1, 3, C3, [512, False]] # 19
- [-1, 1, Conv, [256, 1, 1]] - [-1, 1, Conv, [256, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C3, [256, False]] # 23 (P3/8-small) - [-1, 3, C3, [256, False]] # 23 (P3/8-small)

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@ -25,16 +25,15 @@ backbone:
- [-1, 3, C3, [1024]] - [-1, 3, C3, [1024]]
- [-1, 1, SPPF, [1024, 5]] # 9 - [-1, 1, SPPF, [1024, 5]] # 9
# YOLOv5 v6.0 head # YOLOv5 v6.0 head
head: head:
- [-1, 1, Conv, [512, 1, 1]] - [-1, 1, Conv, [512, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C3, [512, False]] # 13 - [-1, 3, C3, [512, False]] # 13
- [-1, 1, Conv, [256, 1, 1]] - [-1, 1, Conv, [256, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C3, [256, False]] # 17 (P3/8-small) - [-1, 3, C3, [256, False]] # 17 (P3/8-small)

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@ -27,15 +27,15 @@ backbone:
# YOLOv8.0-ghost-p2 head # YOLOv8.0-ghost-p2 head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C3Ghost, [512]] # 12 - [-1, 3, C3Ghost, [512]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C3Ghost, [256]] # 15 (P3/8-small) - [-1, 3, C3Ghost, [256]] # 15 (P3/8-small)
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 2], 1, Concat, [1]] # cat backbone P2 - [[-1, 2], 1, Concat, [1]] # cat backbone P2
- [-1, 3, C3Ghost, [128]] # 18 (P2/4-xsmall) - [-1, 3, C3Ghost, [128]] # 18 (P2/4-xsmall)

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@ -29,15 +29,15 @@ backbone:
# YOLOv8.0-ghost-p6 head # YOLOv8.0-ghost-p6 head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 8], 1, Concat, [1]] # cat backbone P5 - [[-1, 8], 1, Concat, [1]] # cat backbone P5
- [-1, 3, C3Ghost, [768]] # 14 - [-1, 3, C3Ghost, [768]] # 14
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C3Ghost, [512]] # 17 - [-1, 3, C3Ghost, [512]] # 17
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C3Ghost, [256]] # 20 (P3/8-small) - [-1, 3, C3Ghost, [256]] # 20 (P3/8-small)

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@ -28,11 +28,11 @@ backbone:
# YOLOv8.0n head # YOLOv8.0n head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C3Ghost, [512]] # 12 - [-1, 3, C3Ghost, [512]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C3Ghost, [256]] # 15 (P3/8-small) - [-1, 3, C3Ghost, [256]] # 15 (P3/8-small)

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@ -27,11 +27,11 @@ backbone:
# YOLOv8.0n head # YOLOv8.0n head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C2f, [512]] # 12 - [-1, 3, C2f, [512]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C2f, [256]] # 15 (P3/8-small) - [-1, 3, C2f, [256]] # 15 (P3/8-small)

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@ -27,15 +27,15 @@ backbone:
# YOLOv8.0-p2 head # YOLOv8.0-p2 head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C2f, [512]] # 12 - [-1, 3, C2f, [512]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C2f, [256]] # 15 (P3/8-small) - [-1, 3, C2f, [256]] # 15 (P3/8-small)
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 2], 1, Concat, [1]] # cat backbone P2 - [[-1, 2], 1, Concat, [1]] # cat backbone P2
- [-1, 3, C2f, [128]] # 18 (P2/4-xsmall) - [-1, 3, C2f, [128]] # 18 (P2/4-xsmall)

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@ -29,15 +29,15 @@ backbone:
# YOLOv8.0x6 head # YOLOv8.0x6 head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 8], 1, Concat, [1]] # cat backbone P5 - [[-1, 8], 1, Concat, [1]] # cat backbone P5
- [-1, 3, C2, [768, False]] # 14 - [-1, 3, C2, [768, False]] # 14
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C2, [512, False]] # 17 - [-1, 3, C2, [512, False]] # 17
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C2, [256, False]] # 20 (P3/8-small) - [-1, 3, C2, [256, False]] # 20 (P3/8-small)

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@ -30,15 +30,15 @@ backbone:
# YOLOv8.0x6 head # YOLOv8.0x6 head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 8], 1, Concat, [1]] # cat backbone P5 - [[-1, 8], 1, Concat, [1]] # cat backbone P5
- [-1, 3, C2, [768, False]] # 14 - [-1, 3, C2, [768, False]] # 14
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C2, [512, False]] # 17 - [-1, 3, C2, [512, False]] # 17
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C2, [256, False]] # 20 (P3/8-small) - [-1, 3, C2, [256, False]] # 20 (P3/8-small)

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@ -28,11 +28,11 @@ backbone:
# YOLOv8.0n head # YOLOv8.0n head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C2f, [512]] # 12 - [-1, 3, C2f, [512]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C2f, [256]] # 15 (P3/8-small) - [-1, 3, C2f, [256]] # 15 (P3/8-small)

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@ -27,11 +27,11 @@ backbone:
# YOLOv8.0n head # YOLOv8.0n head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C2f, [512]] # 12 - [-1, 3, C2f, [512]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C2f, [256]] # 15 (P3/8-small) - [-1, 3, C2f, [256]] # 15 (P3/8-small)

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@ -29,15 +29,15 @@ backbone:
# YOLOv8.0x6 head # YOLOv8.0x6 head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 8], 1, Concat, [1]] # cat backbone P5 - [[-1, 8], 1, Concat, [1]] # cat backbone P5
- [-1, 3, C2, [768, False]] # 14 - [-1, 3, C2, [768, False]] # 14
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C2, [512, False]] # 17 - [-1, 3, C2, [512, False]] # 17
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C2, [256, False]] # 20 (P3/8-small) - [-1, 3, C2, [256, False]] # 20 (P3/8-small)

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@ -27,11 +27,11 @@ backbone:
# YOLOv8.0n head # YOLOv8.0n head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C2f, [512]] # 12 - [-1, 3, C2f, [512]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C2f, [256]] # 15 (P3/8-small) - [-1, 3, C2f, [256]] # 15 (P3/8-small)

View File

@ -27,11 +27,11 @@ backbone:
# YOLOv8.0n head # YOLOv8.0n head
head: head:
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4 - [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C2f, [512]] # 12 - [-1, 3, C2f, [512]] # 12
- [-1, 1, nn.Upsample, [None, 2, 'nearest']] - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3 - [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C2f, [256]] # 15 (P3/8-small) - [-1, 3, C2f, [256]] # 15 (P3/8-small)