zh/datasets/segment/crack-seg/

[giscus[bot]]

zh/datasets/segment/crack-seg/

探索内容广泛的Roboflow 裂缝分割数据集，该数据集非常适合交通和公共安全研究或自动驾驶汽车模型开发。

https://docs.ultralytics.com/zh/datasets/segment/crack-seg/

[UltralyticsAssistant]

👋 Hello, thank you for your interest in Ultralytics 🚀! It's great to see your exploration of the Crack Segmentation dataset for segmentation tasks. We recommend checking out our Docs for guidance on using datasets for segmentation and more insights into YOLO's capabilities.

If you're running into any issues or have specific questions regarding this dataset or your workflow, please provide as much context as possible so we can assist, such as any code snippets, error messages, or logs. If this is a 🐛 bug report, sharing a minimum reproducible example will be greatly helpful in resolving it.

Explore our community options to connect and discuss further:

• For real-time chat, join our Discord 🎧.
• Dive into threads on our Subreddit for community-driven discussions.
• Visit Discourse for insightful in-depth exchanges.

Upgrade

If you're experiencing any unexpected behavior, please ensure you are operating with the latest version of the ultralytics package by updating with:

pip install -U ultralytics

Make sure your environment meets the required specifications (Python>=3.8, PyTorch>=1.8). You can verify all dependencies are met by checking our requirements file.

Environments

YOLO can be seamlessly executed in the following supported environments, all pre-configured with necessary dependencies:

• Notebooks with Free GPU:
• Google Cloud VM: GCP Quickstart Guide
• AWS Deep Learning AMI: AWS Quickstart Guide
• Docker containers: Docker Guide

Status

If this badge is green, all Ultralytics CI tests are passing, which confirms that YOLO modes and tasks are functioning on supported platforms (macOS, Windows, Ubuntu).

This is an automated response to help promptly guide you to resources and debug tools 😊. An Ultralytics engineer will follow up with further assistance soon!