mirror of
https://github.com/THU-MIG/yolov10.git
synced 2025-05-22 21:04:21 +08:00
Add HUB-SDK docs (#7775)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com> Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com>
This commit is contained in:
Glenn Jocher
GitHub
parent
67ae86f006
commit
1152a06cbc
1
.github/workflows/publish.yml
vendored
1
.github/workflows/publish.yml
vendored
@ -66,7 +66,6 @@ jobs:
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env:
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PERSONAL_ACCESS_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }}
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INDEXNOW_KEY: ${{ secrets.INDEXNOW_KEY_DOCS }}
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WEGLOT_KEY: ${{ secrets.WEGLOT_KEY_DOCS }}
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run: |
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python docs/build_docs.py
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git config --global user.name "Glenn Jocher"
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@ -33,24 +33,36 @@ from tqdm import tqdm
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DOCS = Path(__file__).parent.resolve()
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SITE = DOCS.parent / "site"
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LANGUAGES = False
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def build_docs():
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def build_docs(use_languages=False, clone_repos=True):
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"""Build docs using mkdocs."""
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if SITE.exists():
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print(f"Removing existing {SITE}")
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shutil.rmtree(SITE)
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# Get hub-sdk repo
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if clone_repos:
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repo = "https://github.com/ultralytics/hub-sdk"
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local_dir = DOCS.parent / Path(repo).name
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if not local_dir.exists():
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os.system(f"git clone {repo} {local_dir}")
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os.system(f"git -C {local_dir} pull") # update repo
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shutil.rmtree(DOCS / "en/hub/sdk")
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shutil.copytree(local_dir / "docs", DOCS / "en/hub/sdk")
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shutil.rmtree(DOCS / "en/hub/sdk/reference") # temporarily delete reference until we find a solution for this
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print(f"Cloned/Updated {repo} in {local_dir}")
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# Build the main documentation
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print(f"Building docs from {DOCS}")
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subprocess.run(f"mkdocs build -f {DOCS}/mkdocs.yml", check=True, shell=True)
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# Build other localized documentations
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if LANGUAGES:
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if use_languages:
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for file in DOCS.glob("mkdocs_*.yml"):
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print(f"Building MkDocs site with configuration file: {file}")
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subprocess.run(f"mkdocs build -f {file}", check=True, shell=True)
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update_html_links() # update .md in href links
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print(f"Site built at {SITE}")
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@ -104,21 +116,13 @@ def update_page_title(file_path: Path, new_title: str):
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file.write(updated_content)
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def update_html_head(key=""):
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def update_html_head(script=""):
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"""Update the HTML head section of each file."""
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html_files = Path(SITE).rglob("*.html")
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for html_file in tqdm(html_files, desc="Processing HTML files"):
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with html_file.open("r", encoding="utf-8") as file:
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html_content = file.read()
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script = f"""
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<script type="text/javascript" src="https://cdn.weglot.com/weglot.min.js"></script>
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<script>
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Weglot.initialize({{
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api_key: '{key}'
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}});
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</script>
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"""
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if script in html_content: # script already in HTML file
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return
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@ -137,13 +141,8 @@ def main():
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# Update titles
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update_page_title(SITE / "404.html", new_title="Ultralytics Docs - Not Found")
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# Update .md in href links
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if LANGUAGES:
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update_html_links()
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# Update HTML file head section
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if not LANGUAGES and False:
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update_html_head(key=os.environ.get("WEGLOT_KEY"))
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# update_html_head("")
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# Show command to serve built website
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print('Serve site at http://localhost:8000 with "python -m http.server --directory site"')
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34
docs/coming_soon_template.md
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34
docs/coming_soon_template.md
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@ -0,0 +1,34 @@
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---
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description: Discover what's next for Ultralytics with our under-construction page, previewing new, groundbreaking AI and ML features coming soon.
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keywords: Ultralytics, coming soon, under construction, new features, AI updates, ML advancements, YOLO, technology preview
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---
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# Under Construction 🏗️🌟
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Welcome to the Ultralytics "Under Construction" page! Here, we're hard at work developing the next generation of AI and ML innovations. This page serves as a teaser for the exciting updates and new features we're eager to share with you!
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## Exciting New Features on the Way 🎉
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- **Innovative Breakthroughs:** Get ready for advanced features and services that will transform your AI and ML experience.
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- **New Horizons:** Anticipate novel products that redefine AI and ML capabilities.
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- **Enhanced Services:** We're upgrading our services for greater efficiency and user-friendliness.
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## Stay Updated 🚧
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This placeholder page is your first stop for upcoming developments. Keep an eye out for:
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- **Newsletter:** Subscribe [here](https://ultralytics.com/#newsletter) for the latest news.
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- **Social Media:** Follow us [here](https://www.linkedin.com/company/ultralytics) for updates and teasers.
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- **Blog:** Visit our [blog](https://ultralytics.com/blog) for detailed insights.
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## We Value Your Input 🗣️
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Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://ultralytics.com/contact).
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## Thank You, Community! 🌍
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Your [contributions](https://docs.ultralytics.com/help/contributing) inspire our continuous [innovation](https://github.com/ultralytics/ultralytics). Stay tuned for the big reveal of what's next in AI and ML at Ultralytics!
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---
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Excited for what's coming? Bookmark this page and get ready for a transformative AI and ML journey with Ultralytics! 🛠️🤖
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34
docs/en/hub/api/index.md
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34
docs/en/hub/api/index.md
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@ -0,0 +1,34 @@
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---
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description: Discover what's next for Ultralytics with our under-construction page, previewing new, groundbreaking AI and ML features coming soon.
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keywords: Ultralytics, coming soon, under construction, new features, AI updates, ML advancements, YOLO, technology preview
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---
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# Under Construction 🏗️🌟
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Welcome to the Ultralytics "Under Construction" page! Here, we're hard at work developing the next generation of AI and ML innovations. This page serves as a teaser for the exciting updates and new features we're eager to share with you!
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## Exciting New Features on the Way 🎉
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- **Innovative Breakthroughs:** Get ready for advanced features and services that will transform your AI and ML experience.
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- **New Horizons:** Anticipate novel products that redefine AI and ML capabilities.
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- **Enhanced Services:** We're upgrading our services for greater efficiency and user-friendliness.
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## Stay Updated 🚧
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This placeholder page is your first stop for upcoming developments. Keep an eye out for:
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- **Newsletter:** Subscribe [here](https://ultralytics.com/#newsletter) for the latest news.
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- **Social Media:** Follow us [here](https://www.linkedin.com/company/ultralytics) for updates and teasers.
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- **Blog:** Visit our [blog](https://ultralytics.com/blog) for detailed insights.
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## We Value Your Input 🗣️
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Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://ultralytics.com/contact).
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## Thank You, Community! 🌍
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Your [contributions](https://docs.ultralytics.com/help/contributing) inspire our continuous [innovation](https://github.com/ultralytics/ultralytics). Stay tuned for the big reveal of what's next in AI and ML at Ultralytics!
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---
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Excited for what's coming? Bookmark this page and get ready for a transformative AI and ML journey with Ultralytics! 🛠️🤖
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@ -58,4 +58,4 @@ We hope that the resources here will help you get the most out of HUB. Please br
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- [**Ultralytics HUB App**](app/index.md). Learn about the Ultralytics App for iOS and Android, which allows you to run models directly on your mobile device.
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- [**iOS**](app/ios.md). Learn about YOLO CoreML models accelerated on Apple's Neural Engine on iPhones and iPads.
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- [**Android**](app/android.md). Explore TFLite acceleration on mobile devices.
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- [**Inference API**](inference_api.md). Understand how to use the Inference API for running your trained models in the cloud to generate predictions.
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- [**Inference API**](inference-api.md). Understand how to use the Inference API for running your trained models in the cloud to generate predictions.
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@ -103,7 +103,7 @@ The JSON list contains information about the detected objects, their coordinates
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### Detect Model Format
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YOLO detection models, such as `yolov8n.pt`, can return JSON responses from local inference, CLI API inference, and Python API inference. All of these methods produce the same JSON response format.
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YOLO detection models, such as `yolov8n.pt`, can return JSON responses from local inference, CLI inference, and Python inference. All of these methods produce the same JSON response format.
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!!! Example "Detect Model JSON Response"
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@ -122,7 +122,7 @@ YOLO detection models, such as `yolov8n.pt`, can return JSON responses from loca
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print(results[0].tojson())
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```
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=== "CLI API"
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=== "CLI"
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```bash
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curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
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@ -133,7 +133,7 @@ YOLO detection models, such as `yolov8n.pt`, can return JSON responses from loca
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-F "iou=0.45"
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```
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=== "Python API"
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=== "Python"
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```python
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import requests
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@ -201,7 +201,7 @@ YOLO detection models, such as `yolov8n.pt`, can return JSON responses from loca
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### Segment Model Format
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YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses from local inference, CLI API inference, and Python API inference. All of these methods produce the same JSON response format.
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YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses from local inference, CLI inference, and Python inference. All of these methods produce the same JSON response format.
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!!! Example "Segment Model JSON Response"
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@ -220,7 +220,7 @@ YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses fr
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print(results[0].tojson())
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```
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=== "CLI API"
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=== "CLI"
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```bash
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curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
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@ -231,7 +231,7 @@ YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses fr
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-F "iou=0.45"
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```
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=== "Python API"
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=== "Python"
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```python
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import requests
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@ -342,7 +342,7 @@ YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses fr
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### Pose Model Format
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YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from local inference, CLI API inference, and Python API inference. All of these methods produce the same JSON response format.
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YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from local inference, CLI inference, and Python inference. All of these methods produce the same JSON response format.
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!!! Example "Pose Model JSON Response"
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@ -361,7 +361,7 @@ YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from loca
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print(results[0].tojson())
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```
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=== "CLI API"
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=== "CLI"
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```bash
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curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
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@ -372,7 +372,7 @@ YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from loca
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-F "iou=0.45"
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```
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=== "Python API"
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=== "Python"
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```python
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import requests
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@ -124,7 +124,7 @@ You can preview your model if you click on the **Preview** tab and upload an ima
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You can also use our Ultralytics Cloud API to effortlessly [run inference](https://docs.ultralytics.com/hub/inference_api) with your custom model.
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You can also use our Ultralytics Cloud API to effortlessly [run inference](inference-api.md) with your custom model.
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34
docs/en/hub/on-premise/index.md
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34
docs/en/hub/on-premise/index.md
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@ -0,0 +1,34 @@
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---
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description: Discover what's next for Ultralytics with our under-construction page, previewing new, groundbreaking AI and ML features coming soon.
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keywords: Ultralytics, coming soon, under construction, new features, AI updates, ML advancements, YOLO, technology preview
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---
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# Under Construction 🏗️🌟
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Welcome to the Ultralytics "Under Construction" page! Here, we're hard at work developing the next generation of AI and ML innovations. This page serves as a teaser for the exciting updates and new features we're eager to share with you!
|
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## Exciting New Features on the Way 🎉
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||||
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- **Innovative Breakthroughs:** Get ready for advanced features and services that will transform your AI and ML experience.
|
||||
- **New Horizons:** Anticipate novel products that redefine AI and ML capabilities.
|
||||
- **Enhanced Services:** We're upgrading our services for greater efficiency and user-friendliness.
|
||||
|
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## Stay Updated 🚧
|
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This placeholder page is your first stop for upcoming developments. Keep an eye out for:
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|
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- **Newsletter:** Subscribe [here](https://ultralytics.com/#newsletter) for the latest news.
|
||||
- **Social Media:** Follow us [here](https://www.linkedin.com/company/ultralytics) for updates and teasers.
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- **Blog:** Visit our [blog](https://ultralytics.com/blog) for detailed insights.
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||||
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## We Value Your Input 🗣️
|
||||
|
||||
Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://ultralytics.com/contact).
|
||||
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## Thank You, Community! 🌍
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||||
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Your [contributions](https://docs.ultralytics.com/help/contributing) inspire our continuous [innovation](https://github.com/ultralytics/ultralytics). Stay tuned for the big reveal of what's next in AI and ML at Ultralytics!
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---
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Excited for what's coming? Bookmark this page and get ready for a transformative AI and ML journey with Ultralytics! 🛠️🤖
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@ -1,6 +1,6 @@
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---
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comments: true
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description: Learn how to use Ultralytics YOLO through Command Line: train models, run predictions and exports models to different formats easily using terminal commands.
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description: Learn how to use Ultralytics YOLO through Command Line, train models, run predictions and exports models to different formats easily using terminal commands.
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keywords: Ultralytics, YOLO, CLI, train, validation, prediction, command line interface, YOLO CLI, YOLO terminal, model training, prediction, exporting
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---
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@ -343,17 +343,28 @@ nav:
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- TensorBoard: integrations/tensorboard.md
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- Amazon SageMaker: integrations/amazon-sagemaker.md
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- HUB:
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- hub/index.md
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- Quickstart: hub/quickstart.md
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- Datasets: hub/datasets.md
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- Projects: hub/projects.md
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- Models: hub/models.md
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- Integrations: hub/integrations.md
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- Ultralytics HUB App:
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- Cloud:
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- hub/index.md
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- Quickstart: hub/quickstart.md
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- Datasets: hub/datasets.md
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- Projects: hub/projects.md
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- Models: hub/models.md
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- Integrations: hub/integrations.md
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- Inference API: hub/inference-api.md
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- On Premise:
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- hub/on-premise/index.md
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- App:
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- hub/app/index.md
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- iOS: hub/app/ios.md
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- Android: hub/app/android.md
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- Inference API: hub/inference_api.md
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- Python SDK:
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- hub/sdk/index.md
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- Quickstart: hub/sdk/quickstart.md
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- Model: hub/sdk/model.md
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- Dataset: hub/sdk/dataset.md
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- Project: hub/sdk/project.md
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- REST API:
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- hub/api/index.md
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- Reference:
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- cfg:
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@ -542,6 +553,7 @@ plugins:
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quick-start.md: quickstart.md
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app.md: hub/app/index.md
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sdk.md: index.md
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hub/inference_api.md: hub/inference-api.md
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usage/hyperparameter_tuning.md: integrations/ray-tune.md
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reference/base_pred.md: reference/engine/predictor.md
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reference/base_trainer.md: reference/engine/trainer.md
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@ -259,8 +259,8 @@ class Model(nn.Module):
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x in sys.argv for x in ("predict", "track", "mode=predict", "mode=track")
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)
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custom = {"conf": 0.25, "save": is_cli} # method defaults
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args = {**self.overrides, **custom, **kwargs, "mode": "predict"} # highest priority args on the right
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custom = {"conf": 0.25, "save": is_cli, "mode": "predict"} # method defaults
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args = {**self.overrides, **custom, **kwargs} # highest priority args on the right
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prompts = args.pop("prompts", None) # for SAM-type models
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if not self.predictor:
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