Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

pavement distress detection #684

Closed
1 task done
jj6066 opened this issue May 15, 2024 · 3 comments
Closed
1 task done

pavement distress detection #684

jj6066 opened this issue May 15, 2024 · 3 comments
Labels
enhancement New feature or request

Comments

@jj6066
Copy link

jj6066 commented May 15, 2024

Search before asking

  • I have searched the HUB issues and found no similar feature requests.

Description

road damage detection application

Use case

detect road crack type and measure depth , length ,width ,etc

Additional

No response

@jj6066 jj6066 added the enhancement New feature or request label May 15, 2024
Copy link

👋 Hello @jj6066, thank you for raising an issue about Ultralytics HUB 🚀! Please visit our HUB Docs to learn more:

  • Quickstart. Start training and deploying YOLO models with HUB in seconds.
  • Datasets: Preparing and Uploading. Learn how to prepare and upload your datasets to HUB in YOLO format.
  • Projects: Creating and Managing. Group your models into projects for improved organization.
  • Models: Training and Exporting. Train YOLOv5 and YOLOv8 models on your custom datasets and export them to various formats for deployment.
  • Integrations. Explore different integration options for your trained models, such as TensorFlow, ONNX, OpenVINO, CoreML, and PaddlePaddle.
  • Ultralytics HUB App. Learn about the Ultralytics App for iOS and Android, which allows you to run models directly on your mobile device.
    • iOS. Learn about YOLO CoreML models accelerated on Apple's Neural Engine on iPhones and iPads.
    • Android. Explore TFLite acceleration on mobile devices.
  • Inference API. Understand how to use the Inference API for running your trained models in the cloud to generate predictions.

If this is a 🐛 Bug Report, please provide screenshots and steps to reproduce your problem to help us get started working on a fix.

If this is a ❓ Question, please provide as much information as possible, including dataset, model, environment details etc. so that we might provide the most helpful response.

We try to respond to all issues as promptly as possible. Thank you for your patience!

@jj6066
Copy link
Author

jj6066 commented May 15, 2024

initial comment

@jj6066 jj6066 closed this as completed May 15, 2024
@pderrenger
Copy link
Member

Hello! Thanks for your inquiry about pavement distress detection using the Ultralytics HUB. For detecting and measuring specific features like cracks, depth, length, and width in road surfaces, you'll primarily configure your detection model to recognize these attributes effectively.

Adjusting your training dataset to include varied examples of road damage and tuning your model parameters to focus on these features will be essential. Our comprehensive guide on creating custom datasets, available in the Ultralytics HUB Docs, will be a great starting point.

If you have further questions or need more guidance, feel free to ask. Happy detecting! 😊

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

2 participants