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Add YouTube iframe `loading="lazy"` (#8001)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
pull/8003/head
Glenn Jocher 1 year ago committed by GitHub
parent 70d4a3752e
commit 9d35ecbf0f
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39 changed files with 39 additions and 39 deletions
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  1. 2
      docs/en/datasets/explorer/api.md
  2. 2
      docs/en/datasets/explorer/dashboard.md
  3. 2
      docs/en/datasets/explorer/index.md
  4. 2
      docs/en/datasets/pose/tiger-pose.md
  5. 2
      docs/en/guides/heatmaps.md
  6. 2
      docs/en/guides/index.md
  7. 2
      docs/en/guides/object-counting.md
  8. 2
      docs/en/guides/raspberry-pi.md
  9. 2
      docs/en/guides/region-counting.md
  10. 2
      docs/en/guides/security-alarm-system.md
  11. 2
      docs/en/guides/triton-inference-server.md
  12. 2
      docs/en/hub/index.md
  13. 2
      docs/en/hub/integrations.md
  14. 2
      docs/en/hub/projects.md
  15. 2
      docs/en/hub/quickstart.md
  16. 2
      docs/en/index.md
  17. 2
      docs/en/integrations/clearml.md
  18. 2
      docs/en/integrations/openvino.md
  19. 2
      docs/en/models/index.md
  20. 2
      docs/en/models/yolov8.md
  21. 2
      docs/en/modes/benchmark.md
  22. 2
      docs/en/modes/export.md
  23. 2
      docs/en/modes/index.md
  24. 2
      docs/en/modes/predict.md
  25. 2
      docs/en/modes/track.md
  26. 2
      docs/en/modes/train.md
  27. 2
      docs/en/modes/val.md
  28. 2
      docs/en/quickstart.md
  29. 2
      docs/en/tasks/classify.md
  30. 2
      docs/en/tasks/detect.md
  31. 2
      docs/en/tasks/index.md
  32. 2
      docs/en/tasks/obb.md
  33. 2
      docs/en/tasks/pose.md
  34. 2
      docs/en/tasks/segment.md
  35. 2
      docs/en/usage/callbacks.md
  36. 2
      docs/en/usage/cfg.md
  37. 2
      docs/en/usage/cli.md
  38. 2
      docs/en/usage/engine.md
  39. 2
      docs/en/usage/python.md

2
docs/en/datasets/explorer/api.md
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@ -13,7 +13,7 @@ The Explorer API is a Python API for exploring your datasets. It supports filter
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/3VryynorQeo?start=279"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/3VryynorQeo?start=279"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/datasets/explorer/dashboard.md
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@ -14,7 +14,7 @@ Explorer GUI is like a playground build using [Ultralytics Explorer API](api.md)
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/3VryynorQeo?start=306"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/3VryynorQeo?start=306"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/datasets/explorer/index.md
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@ -15,7 +15,7 @@ Ultralytics Explorer is a tool for exploring CV datasets using semantic search,
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/3VryynorQeo"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/3VryynorQeo"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/datasets/pose/tiger-pose.md
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@ -16,7 +16,7 @@ This dataset is intended for use with [Ultralytics HUB](https://hub.ultralytics.
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/Gc6K5eKrTNQ"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Gc6K5eKrTNQ"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/guides/heatmaps.md
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@ -12,7 +12,7 @@ A heatmap generated with [Ultralytics YOLOv8](https://github.com/ultralytics/ult
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/4ezde5-nZZw"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/4ezde5-nZZw"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/guides/index.md
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@ -12,7 +12,7 @@ Whether you're a beginner or an expert in deep learning, our tutorials offer val
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/96NkhsV-W1U"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/96NkhsV-W1U"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/guides/object-counting.md
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@ -12,7 +12,7 @@ Object counting with [Ultralytics YOLOv8](https://github.com/ultralytics/ultraly
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/Ag2e-5_NpS0"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Ag2e-5_NpS0"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/guides/raspberry-pi.md
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@ -10,7 +10,7 @@ This comprehensive guide aims to expedite your journey with YOLO object detectio
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/yul4gq_LrOI"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/yul4gq_LrOI"
title="Introducing Raspberry Pi 5" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/guides/region-counting.md
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@ -12,7 +12,7 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Counting, Object Trackin
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/okItf1iHlV8"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/okItf1iHlV8"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/guides/security-alarm-system.md
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@ -16,7 +16,7 @@ The Security Alarm System Project utilizing Ultralytics YOLOv8 integrates advanc
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/_1CmwUzoxY4"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/_1CmwUzoxY4"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/guides/triton-inference-server.md
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@ -10,7 +10,7 @@ The [Triton Inference Server](https://developer.nvidia.com/nvidia-triton-inferen
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/NQDtfSi5QF4"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/NQDtfSi5QF4"
title="Getting Started with NVIDIA Triton Inference Server" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/hub/index.md
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@ -39,7 +39,7 @@ HUB is designed to be user-friendly and intuitive, with a drag-and-drop interfac
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/hub/integrations.md
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@ -12,7 +12,7 @@ Welcome to the Integrations guide for [Ultralytics HUB](https://hub.ultralytics.
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/hub/projects.md
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@ -12,7 +12,7 @@ This creates a unified and organized workspace that facilitates easier model man
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/Gc6K5eKrTNQ"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Gc6K5eKrTNQ"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/hub/quickstart.md
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@ -12,7 +12,7 @@ Thank you for visiting the Quickstart guide for [Ultralytics HUB](https://hub.ul
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/index.md
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@ -49,7 +49,7 @@ Explore the YOLOv8 Docs, a comprehensive resource designed to help you understan
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/LNwODJXcvt4?si=7n1UvGRLSd9p5wKs"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/LNwODJXcvt4?si=7n1UvGRLSd9p5wKs"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/integrations/clearml.md
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@ -147,7 +147,7 @@ For a visual walkthrough of what the ClearML Results Page looks like, watch the
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/iLcC7m3bCes?si=oSEAoZbrg8inCg_2"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/iLcC7m3bCes?si=oSEAoZbrg8inCg_2"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/integrations/openvino.md
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@ -14,7 +14,7 @@ OpenVINO, short for Open Visual Inference & Neural Network Optimization toolkit,
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/kONm9nE5_Fk?si=kzquuBrxjSbntHoU"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/kONm9nE5_Fk?si=kzquuBrxjSbntHoU"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/models/index.md
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@ -26,7 +26,7 @@ Here are some of the key models supported:
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/MWq1UxqTClU?si=nHAW-lYDzrz68jR0"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/MWq1UxqTClU?si=nHAW-lYDzrz68jR0"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/models/yolov8.md
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@ -14,7 +14,7 @@ YOLOv8 is the latest iteration in the YOLO series of real-time object detectors,
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/Na0HvJ4hkk0"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Na0HvJ4hkk0"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/modes/benchmark.md
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@ -14,7 +14,7 @@ Once your model is trained and validated, the next logical step is to evaluate i
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/j8uQc0qB91s?start=105"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/j8uQc0qB91s?start=105"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/modes/export.md
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@ -14,7 +14,7 @@ The ultimate goal of training a model is to deploy it for real-world application
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/WbomGeoOT_k?si=aGmuyooWftA0ue9X"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/WbomGeoOT_k?si=aGmuyooWftA0ue9X"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/modes/index.md
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@ -14,7 +14,7 @@ Ultralytics YOLOv8 is not just another object detection model; it's a versatile
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/j8uQc0qB91s?si=dhnGKgqvs7nPgeaM"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/j8uQc0qB91s?si=dhnGKgqvs7nPgeaM"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/modes/predict.md
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@ -14,7 +14,7 @@ In the world of machine learning and computer vision, the process of making sens
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/QtsI0TnwDZs?si=ljesw75cMO2Eas14"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/QtsI0TnwDZs?si=ljesw75cMO2Eas14"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

2
docs/en/modes/track.md
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@ -21,7 +21,7 @@ The output from Ultralytics trackers is consistent with standard object detectio
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/hHyHmOtmEgs?si=VNZtXmm45Nb9s-N-"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/hHyHmOtmEgs?si=VNZtXmm45Nb9s-N-"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/modes/train.md
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@ -14,7 +14,7 @@ Training a deep learning model involves feeding it data and adjusting its parame
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/LNwODJXcvt4?si=7n1UvGRLSd9p5wKs"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/LNwODJXcvt4?si=7n1UvGRLSd9p5wKs"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/modes/val.md
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@ -14,7 +14,7 @@ Validation is a critical step in the machine learning pipeline, allowing you to
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/j8uQc0qB91s?start=47"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/j8uQc0qB91s?start=47"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/quickstart.md
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@ -10,7 +10,7 @@ Ultralytics provides various installation methods including pip, conda, and Dock
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/_a7cVL9hqnk"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/_a7cVL9hqnk"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/tasks/classify.md
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@ -14,7 +14,7 @@ The output of an image classifier is a single class label and a confidence score
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/NAs-cfq9BDw?start=169"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/NAs-cfq9BDw?start=169"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/tasks/detect.md
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@ -14,7 +14,7 @@ The output of an object detector is a set of bounding boxes that enclose the obj
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/5ku7npMrW40?si=6HQO1dDXunV8gekh"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/5ku7npMrW40?si=6HQO1dDXunV8gekh"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/tasks/index.md
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@ -13,7 +13,7 @@ YOLOv8 is an AI framework that supports multiple computer vision **tasks**. The
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/NAs-cfq9BDw"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/NAs-cfq9BDw"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/tasks/obb.md
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@ -20,7 +20,7 @@ The output of an oriented object detector is a set of rotated bounding boxes tha
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/Z7Z9pHF8wJc"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Z7Z9pHF8wJc"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/tasks/pose.md
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@ -14,7 +14,7 @@ The output of a pose estimation model is a set of points that represent the keyp
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/Y28xXQmju64?si=pCY4ZwejZFu6Z4kZ"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Y28xXQmju64?si=pCY4ZwejZFu6Z4kZ"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/tasks/segment.md
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@ -14,7 +14,7 @@ The output of an instance segmentation model is a set of masks or contours that
<p align="center">
<br>
<iframe width="720" height="405" src="https://www.youtube.com/embed/o4Zd-IeMlSY?si=37nusCzDTd74Obsp"
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/o4Zd-IeMlSY?si=37nusCzDTd74Obsp"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>

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docs/en/usage/callbacks.md
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@ -10,7 +10,7 @@ Ultralytics framework supports callbacks as entry points in strategic stages of
<p align="center">
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