Check for broken links (#1422)

Co-authored-by: Joris LIMONIER <joris.limonier@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2 years ago committed by GitHub
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commit 30fc4b537f
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@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, GPL-3.0 license
name: "CLA Assistant" name: CLA Assistant
on: on:
issue_comment: issue_comment:
types: types:
@ -16,7 +16,7 @@ jobs:
if: github.repository == 'ultralytics/ultralytics' if: github.repository == 'ultralytics/ultralytics'
runs-on: ubuntu-latest runs-on: ubuntu-latest
steps: steps:
- name: "CLA Assistant" - name: CLA Assistant
if: (github.event.comment.body == 'recheck' || github.event.comment.body == 'I have read the CLA Document and I sign the CLA') || github.event_name == 'pull_request_target' if: (github.event.comment.body == 'recheck' || github.event.comment.body == 'I have read the CLA Document and I sign the CLA') || github.event_name == 'pull_request_target'
uses: contributor-assistant/github-action@v2.3.0 uses: contributor-assistant/github-action@v2.3.0
env: env:

@ -25,7 +25,7 @@ jobs:
See our [Contributing Guide](https://github.com/ultralytics/ultralytics/blob/main/CONTRIBUTING.md) for details and let us know if you have any questions! See our [Contributing Guide](https://github.com/ultralytics/ultralytics/blob/main/CONTRIBUTING.md) for details and let us know if you have any questions!
issue-message: | issue-message: |
👋 Hello @${{ github.actor }}, thank you for your interest in YOLOv8 🚀! We recommend a visit to the [YOLOv8 Docs](https://docs.ultralytics.com) for new users where you can find many [Python](https://docs.ultralytics.com/python/) and [CLI](https://docs.ultralytics.com/cli/) usage examples and where many of the most common questions may already be answered. 👋 Hello @${{ github.actor }}, thank you for your interest in YOLOv8 🚀! We recommend a visit to the [YOLOv8 Docs](https://docs.ultralytics.com) for new users where you can find many [Python](https://docs.ultralytics.com/usage/python/) and [CLI](https://docs.ultralytics.com/usage/cli/) usage examples and where many of the most common questions may already be answered.
If this is a 🐛 Bug Report, please provide a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) to help us debug it. If this is a 🐛 Bug Report, please provide a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) to help us debug it.

@ -0,0 +1,38 @@
# Ultralytics YOLO 🚀, GPL-3.0 license
# YOLO Continuous Integration (CI) GitHub Actions tests
name: Check Broken links
on:
push:
branches: [main]
pull_request:
branches: [main]
workflow_dispatch:
schedule:
- cron: '0 0 * * *' # runs at 00:00 UTC every day
jobs:
Links:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Test Markdown and HTML links
uses: lycheeverse/lychee-action@v1.6.1
with:
fail: true
# accept 429(Instagram, 'too many requests'), 999(LinkedIn, 'unknown status code'), Timeout(Twitter)
args: --accept 429,999 --exclude twitter.com --verbose --no-progress './**/*.md' './**/*.html'
env:
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
- name: Test Markdown, HTML, YAML, Python and Notebook links
if: github.event_name == 'workflow_dispatch'
uses: lycheeverse/lychee-action@v1.6.1
with:
fail: true
# accept 429(Instagram, 'too many requests'), 999(LinkedIn, 'unknown status code'), Timeout(Twitter)
args: --accept 429,999 --exclude twitter.com,url.com --verbose --no-progress './**/*.md' './**/*.html' './**/*.yml' './**/*.yaml' './**/*.py' './**/*.ipynb'
env:
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}

@ -26,7 +26,6 @@ repos:
hooks: hooks:
- id: pyupgrade - id: pyupgrade
name: Upgrade code name: Upgrade code
args: [--py37-plus]
- repo: https://github.com/PyCQA/isort - repo: https://github.com/PyCQA/isort
rev: 5.12.0 rev: 5.12.0
@ -67,3 +66,8 @@ repos:
# rev: v1.4.0 # rev: v1.4.0
# hooks: # hooks:
# - id: yesqa # - id: yesqa
# - repo: https://github.com/asottile/dead
# rev: v1.5.0
# hooks:
# - id: dead

@ -32,7 +32,7 @@ To request an Enterprise License please complete the form at [Ultralytics Licens
<a href="https://github.com/ultralytics" style="text-decoration:none;"> <a href="https://github.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;"> <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://twitter.com/ultralytics" style="text-decoration:none;"> <a href="https://twitter.com/ultralytics" style="text-decoration:none;">
@ -83,7 +83,7 @@ yolo predict model=yolov8n.pt source="https://ultralytics.com/images/bus.jpg"
``` ```
`yolo` can be used for a variety of tasks and modes and accepts additional arguments, i.e. `imgsz=640`. See the YOLOv8 `yolo` can be used for a variety of tasks and modes and accepts additional arguments, i.e. `imgsz=640`. See the YOLOv8
[CLI Docs](https://docs.ultralytics.com/cli) for examples. [CLI Docs](https://docs.ultralytics.com/usage/cli) for examples.
#### Python #### Python
@ -106,7 +106,7 @@ success = model.export(format="onnx") # export the model to ONNX format
[Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models) download automatically from the latest [Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models) download automatically from the latest
Ultralytics [release](https://github.com/ultralytics/assets/releases). See Ultralytics [release](https://github.com/ultralytics/assets/releases). See
YOLOv8 [Python Docs](https://docs.ultralytics.com/python) for more examples. YOLOv8 [Python Docs](https://docs.ultralytics.com/usage/python) for more examples.
#### Model Architectures #### Model Architectures
@ -136,7 +136,7 @@ Ultralytics [release](https://github.com/ultralytics/assets/releases) on first u
<details open><summary>Detection</summary> <details open><summary>Detection</summary>
See [Detection Docs](https://docs.ultralytics.com/tasks/detection/) for usage examples with these models. See [Detection Docs](https://docs.ultralytics.com/tasks/detect/) for usage examples with these models.
| Model | size<br><sup>(pixels) | mAP<sup>val<br>50-95 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) | | Model | size<br><sup>(pixels) | mAP<sup>val<br>50-95 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
| ------------------------------------------------------------------------------------ | --------------------- | -------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- | | ------------------------------------------------------------------------------------ | --------------------- | -------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
@ -156,7 +156,7 @@ See [Detection Docs](https://docs.ultralytics.com/tasks/detection/) for usage ex
<details><summary>Segmentation</summary> <details><summary>Segmentation</summary>
See [Segmentation Docs](https://docs.ultralytics.com/tasks/segmentation/) for usage examples with these models. See [Segmentation Docs](https://docs.ultralytics.com/tasks/segment/) for usage examples with these models.
| Model | size<br><sup>(pixels) | mAP<sup>box<br>50-95 | mAP<sup>mask<br>50-95 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) | | Model | size<br><sup>(pixels) | mAP<sup>box<br>50-95 | mAP<sup>mask<br>50-95 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
| -------------------------------------------------------------------------------------------- | --------------------- | -------------------- | --------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- | | -------------------------------------------------------------------------------------------- | --------------------- | -------------------- | --------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
@ -176,7 +176,7 @@ See [Segmentation Docs](https://docs.ultralytics.com/tasks/segmentation/) for us
<details><summary>Classification</summary> <details><summary>Classification</summary>
See [Classification Docs](https://docs.ultralytics.com/tasks/classification/) for usage examples with these models. See [Classification Docs](https://docs.ultralytics.com/tasks/classify/) for usage examples with these models.
| Model | size<br><sup>(pixels) | acc<br><sup>top1 | acc<br><sup>top5 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) at 640 | | Model | size<br><sup>(pixels) | acc<br><sup>top1 | acc<br><sup>top5 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) at 640 |
| -------------------------------------------------------------------------------------------- | --------------------- | ---------------- | ---------------- | ------------------------------ | ----------------------------------- | ------------------ | ------------------------ | | -------------------------------------------------------------------------------------------- | --------------------- | ---------------- | ---------------- | ------------------------------ | ----------------------------------- | ------------------ | ------------------------ |
@ -262,7 +262,7 @@ the [Ultralytics Community Forum](https://community.ultralytics.com/).
<a href="https://github.com/ultralytics" style="text-decoration:none;"> <a href="https://github.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="3%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="3%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
<a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;"> <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="3%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="3%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
<a href="https://twitter.com/ultralytics" style="text-decoration:none;"> <a href="https://twitter.com/ultralytics" style="text-decoration:none;">

@ -28,7 +28,7 @@ SOTA 模型。它在以前成功的 YOLO 版本基础上,引入了新的功能
<a href="https://github.com/ultralytics" style="text-decoration:none;"> <a href="https://github.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;"> <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://twitter.com/ultralytics" style="text-decoration:none;"> <a href="https://twitter.com/ultralytics" style="text-decoration:none;">
@ -232,14 +232,14 @@ YOLOv8 在两种不同的 License 下可用:
## <div align="center">联系我们</div> ## <div align="center">联系我们</div>
请访问 [GitHub Issues](https://github.com/ultralytics/ultralytics/issues) 请访问 [GitHub Issues](https://github.com/ultralytics/ultralytics/issues)
或 [Ultralytics Community Forum](https://community.ultralytis.com) 以报告 YOLOv8 错误和请求功能。 或 [Ultralytics Community Forum](https://community.ultralytics.com) 以报告 YOLOv8 错误和请求功能。
<br> <br>
<div align="center"> <div align="center">
<a href="https://github.com/ultralytics" style="text-decoration:none;"> <a href="https://github.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="3%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="3%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
<a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;"> <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="3%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="3%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
<a href="https://twitter.com/ultralytics" style="text-decoration:none;"> <a href="https://twitter.com/ultralytics" style="text-decoration:none;">

@ -7,7 +7,7 @@
<a href="https://github.com/ultralytics" style="text-decoration:none;"> <a href="https://github.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;"> <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://twitter.com/ultralytics" style="text-decoration:none;"> <a href="https://twitter.com/ultralytics" style="text-decoration:none;">

@ -7,7 +7,7 @@
<a href="https://github.com/ultralytics" style="text-decoration:none;"> <a href="https://github.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;"> <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" /> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://twitter.com/ultralytics" style="text-decoration:none;"> <a href="https://twitter.com/ultralytics" style="text-decoration:none;">

@ -52,7 +52,7 @@ do is loading the corresponding (detection or segmentation) model.
### Tracking ### Tracking
Tracking shares the configuration with predict, i.e `conf`, `iou`, `show`. More configurations please refer Tracking shares the configuration with predict, i.e `conf`, `iou`, `show`. More configurations please refer
to [predict page](https://docs.ultralytics.com/usage/cfg/#prediction). to [predict page](https://docs.ultralytics.com/modes/predict/).
!!! example "" !!! example ""
=== "Python" === "Python"

@ -4,7 +4,7 @@ This is a list of real-world applications and walkthroughs. These can be folders
| Title | Format | Contributor | | Title | Format | Contributor |
| ------------------------------------------------------------------------ | ------------------ | --------------------------------------------------- | | ------------------------------------------------------------------------ | ------------------ | --------------------------------------------------- |
| [YOLO ONNX detection Inference with C++](./YOLOv8_CPP_Inference) | C++/ONNX | [Justas Bartnykas](https://github.com/JustasBart) | | [YOLO ONNX detection Inference with C++](./YOLOv8-CPP-Inference) | C++/ONNX | [Justas Bartnykas](https://github.com/JustasBart) |
| [YOLO OpenCV ONNX detection Python](./YOLOv8-OpenCV-ONNX-Python) | OpenCV/Python/ONNX | [Farid Inawan](https://github.com/frdteknikelektro) | | [YOLO OpenCV ONNX detection Python](./YOLOv8-OpenCV-ONNX-Python) | OpenCV/Python/ONNX | [Farid Inawan](https://github.com/frdteknikelektro) |
| [YOLO .Net ONNX detection C#](https://www.nuget.org/packages/Yolov8.Net) | C# .Net | [Samuel Stainback](https://github.com/sstainba) | | [YOLO .Net ONNX detection C#](https://www.nuget.org/packages/Yolov8.Net) | C# .Net | [Samuel Stainback](https://github.com/sstainba) |

@ -276,7 +276,7 @@
"\n", "\n",
"<p align=\"\"><a href=\"https://roboflow.com/?ref=ultralytics\"><img width=\"1000\" src=\"https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png\"/></a></p>\n", "<p align=\"\"><a href=\"https://roboflow.com/?ref=ultralytics\"><img width=\"1000\" src=\"https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png\"/></a></p>\n",
"\n", "\n",
"Train YOLOv8 on [Detection](https://docs.ultralytics.com/tasks/detection/), [Segmentation](https://docs.ultralytics.com/tasks/segmentation/) and [Classification](https://docs.ultralytics.com/tasks/classification/) datasets." "Train YOLOv8 on [Detection](https://docs.ultralytics.com/tasks/detect/), [Segmentation](https://docs.ultralytics.com/tasks/segment/) and [Classification](https://docs.ultralytics.com/tasks/classify/) datasets."
] ]
}, },
{ {
@ -509,7 +509,7 @@
"source": [ "source": [
"# 5. Python Usage\n", "# 5. Python Usage\n",
"\n", "\n",
"YOLOv8 was reimagined using Python-first principles for the most seamless Python YOLO experience yet. YOLOv8 models can be loaded from a trained checkpoint or created from scratch. Then methods are used to train, val, predict, and export the model. See a detailed Python usage examples in the YOLOv8 [Docs](https://docs.ultralytics.com/python/)." "YOLOv8 was reimagined using Python-first principles for the most seamless Python YOLO experience yet. YOLOv8 models can be loaded from a trained checkpoint or created from scratch. Then methods are used to train, val, predict, and export the model. See a detailed Python usage examples in the YOLOv8 [Docs](https://docs.ultralytics.com/usage/python/)."
], ],
"metadata": { "metadata": {
"id": "kUMOQ0OeDBJG" "id": "kUMOQ0OeDBJG"
@ -554,7 +554,7 @@
"source": [ "source": [
"## 1. Detection\n", "## 1. Detection\n",
"\n", "\n",
"YOLOv8 _detection_ models have no suffix and are the default YOLOv8 models, i.e. `yolov8n.pt` and are pretrained on COCO. See [Detection Docs](https://docs.ultralytics.com/tasks/detection/) for full details.\n" "YOLOv8 _detection_ models have no suffix and are the default YOLOv8 models, i.e. `yolov8n.pt` and are pretrained on COCO. See [Detection Docs](https://docs.ultralytics.com/tasks/detect/) for full details.\n"
], ],
"metadata": { "metadata": {
"id": "yq26lwpYK1lq" "id": "yq26lwpYK1lq"
@ -581,7 +581,7 @@
"source": [ "source": [
"## 2. Segmentation\n", "## 2. Segmentation\n",
"\n", "\n",
"YOLOv8 _segmentation_ models use the `-seg` suffix, i.e. `yolov8n-seg.pt` and are pretrained on COCO. See [Segmentation Docs](https://docs.ultralytics.com/tasks/segmentation/) for full details.\n" "YOLOv8 _segmentation_ models use the `-seg` suffix, i.e. `yolov8n-seg.pt` and are pretrained on COCO. See [Segmentation Docs](https://docs.ultralytics.com/tasks/segment/) for full details.\n"
], ],
"metadata": { "metadata": {
"id": "7ZW58jUzK66B" "id": "7ZW58jUzK66B"
@ -608,7 +608,7 @@
"source": [ "source": [
"## 3. Classification\n", "## 3. Classification\n",
"\n", "\n",
"YOLOv8 _classification_ models use the `-cls` suffix, i.e. `yolov8n-cls.pt` and are pretrained on ImageNet. See [Classification Docs](https://docs.ultralytics.com/tasks/classification/) for full details.\n" "YOLOv8 _classification_ models use the `-cls` suffix, i.e. `yolov8n-cls.pt` and are pretrained on ImageNet. See [Classification Docs](https://docs.ultralytics.com/tasks/classify/) for full details.\n"
], ],
"metadata": { "metadata": {
"id": "ax3p94VNK9zR" "id": "ax3p94VNK9zR"

@ -69,7 +69,7 @@ extra:
- icon: fontawesome/brands/github - icon: fontawesome/brands/github
link: https://github.com/ultralytics link: https://github.com/ultralytics
- icon: fontawesome/brands/linkedin - icon: fontawesome/brands/linkedin
link: https://www.linkedin.com/company/ultralytics link: https://www.linkedin.com/company/ultralytics/
- icon: fontawesome/brands/twitter - icon: fontawesome/brands/twitter
link: https://twitter.com/ultralytics link: https://twitter.com/ultralytics
- icon: fontawesome/brands/youtube - icon: fontawesome/brands/youtube

@ -258,7 +258,7 @@ class AutoBackend(nn.Module):
else: else:
from ultralytics.yolo.engine.exporter import export_formats from ultralytics.yolo.engine.exporter import export_formats
raise TypeError(f"model='{w}' is not a supported model format. " raise TypeError(f"model='{w}' is not a supported model format. "
'See https://docs.ultralytics.com/tasks/detection/#export for help.' 'See https://docs.ultralytics.com/modes/predict for help.'
f'\n\n{export_formats()}') f'\n\n{export_formats()}')
# Load external metadata YAML # Load external metadata YAML

@ -20,7 +20,7 @@ CLI_HELP_MSG = \
Where TASK (optional) is one of [detect, segment, classify] Where TASK (optional) is one of [detect, segment, classify]
MODE (required) is one of [train, val, predict, export, track] MODE (required) is one of [train, val, predict, export, track]
ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults. ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.
See all ARGS at https://docs.ultralytics.com/cfg or with 'yolo cfg' See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg'
1. Train a detection model for 10 epochs with an initial learning_rate of 0.01 1. Train a detection model for 10 epochs with an initial learning_rate of 0.01
yolo train data=coco128.yaml model=yolov8n.pt epochs=10 lr0=0.01 yolo train data=coco128.yaml model=yolov8n.pt epochs=10 lr0=0.01
@ -42,7 +42,7 @@ CLI_HELP_MSG = \
yolo copy-cfg yolo copy-cfg
yolo cfg yolo cfg
Docs: https://docs.ultralytics.com/cli Docs: https://docs.ultralytics.com
Community: https://community.ultralytics.com Community: https://community.ultralytics.com
GitHub: https://github.com/ultralytics/ultralytics GitHub: https://github.com/ultralytics/ultralytics
""" """

@ -153,7 +153,7 @@ def check_source(source):
elif isinstance(source, torch.Tensor): elif isinstance(source, torch.Tensor):
tensor = True tensor = True
else: else:
raise TypeError('Unsupported image type. See docs for supported types https://docs.ultralytics.com/predict') raise TypeError('Unsupported image type. For supported types see https://docs.ultralytics.com/modes/predict')
return source, webcam, screenshot, from_img, in_memory, tensor return source, webcam, screenshot, from_img, in_memory, tensor

@ -359,7 +359,7 @@ def autocast_list(source):
files.append(im) files.append(im)
else: else:
raise TypeError(f'type {type(im).__name__} is not a supported Ultralytics prediction source type. \n' raise TypeError(f'type {type(im).__name__} is not a supported Ultralytics prediction source type. \n'
f'See https://docs.ultralytics.com/predict for supported source types.') f'See https://docs.ultralytics.com/modes/predict for supported source types.')
return files return files

@ -64,7 +64,7 @@ HELP_MSG = \
Where TASK (optional) is one of [detect, segment, classify] Where TASK (optional) is one of [detect, segment, classify]
MODE (required) is one of [train, val, predict, export] MODE (required) is one of [train, val, predict, export]
ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults. ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.
See all ARGS at https://docs.ultralytics.com/cfg or with 'yolo cfg' See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg'
- Train a detection model for 10 epochs with an initial learning_rate of 0.01 - Train a detection model for 10 epochs with an initial learning_rate of 0.01
yolo detect train data=coco128.yaml model=yolov8n.pt epochs=10 lr0=0.01 yolo detect train data=coco128.yaml model=yolov8n.pt epochs=10 lr0=0.01

@ -88,7 +88,7 @@ class SegLoss(Loss):
"This error can occur when incorrectly training a 'segment' model on a 'detect' dataset, " "This error can occur when incorrectly training a 'segment' model on a 'detect' dataset, "
"i.e. 'yolo train model=yolov8n-seg.pt data=coco128.yaml'.\nVerify your dataset is a " "i.e. 'yolo train model=yolov8n-seg.pt data=coco128.yaml'.\nVerify your dataset is a "
"correctly formatted 'segment' dataset using 'data=coco128-seg.yaml' " "correctly formatted 'segment' dataset using 'data=coco128-seg.yaml' "
'as an example.\nSee https://docs.ultralytics.com/tasks/segmentation/ for help.') from e 'as an example.\nSee https://docs.ultralytics.com/tasks/segment/ for help.') from e
# pboxes # pboxes
pred_bboxes = self.bbox_decode(anchor_points, pred_distri) # xyxy, (b, h*w, 4) pred_bboxes = self.bbox_decode(anchor_points, pred_distri) # xyxy, (b, h*w, 4)

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