From c0a4201370bf620fcc77a691dfddb172167027c9 Mon Sep 17 00:00:00 2001 From: Muhammad Rizwan Munawar Date: Thu, 6 Feb 2025 07:41:37 +0500 Subject: [PATCH] Add https://youtu.be/C4mc40YKm-g and notebook badge in docs (#19086) --- docs/en/datasets/segment/crack-seg.md | 13 +++++++++++++ 1 file changed, 13 insertions(+) diff --git a/docs/en/datasets/segment/crack-seg.md b/docs/en/datasets/segment/crack-seg.md index 1526fa5e..3a82a107 100644 --- a/docs/en/datasets/segment/crack-seg.md +++ b/docs/en/datasets/segment/crack-seg.md @@ -6,8 +6,21 @@ keywords: Roboflow, Crack Segmentation Dataset, Ultralytics, transportation safe # Roboflow Universe Crack Segmentation Dataset +Open Crack Segmentation Dataset In Colab + The [Roboflow](https://roboflow.com/?ref=ultralytics) [Crack Segmentation Dataset](https://universe.roboflow.com/university-bswxt/crack-bphdr?ref=ultralytics) stands out as an extensive resource designed specifically for individuals involved in transportation and public safety studies. It is equally beneficial for those working on the development of self-driving car models or simply exploring [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv) applications for recreational purposes. +

+
+ +
+ Watch: Crack segmentation using Ultralytics YOLOv9 +

+ Comprising a total of 4029 static images captured from diverse road and wall scenarios, this dataset emerges as a valuable asset for tasks related to crack segmentation. Whether you are delving into the intricacies of transportation research or seeking to enhance the [accuracy](https://www.ultralytics.com/glossary/accuracy) of your self-driving car models, this dataset provides a rich and varied collection of images to support your endeavors. ## Dataset Structure