Want to try the Demo Data?
You can also try some trained models with our raillens webapp. The models are trained only with synthetic data. LINK
Experience the power of synthetic data to elevate your models and revolutionize infrastructure maintenance. Take advantage of this opportunity to optimize your algorithms and shape the future of maintenance.
Introduction
Explore our demo dataset designed for machine learning projects in infrastructure maintenance. This dataset is an essential tool to test and enhance the capabilities and performance of your detection algorithms.
Training Tips
We are excited to share valuable insights on how to train your models effectively to achieve the best results.
Dataset Description
Our demo dataset includes 1000 high-resolution black-and-white images featuring key components of railway superstructure: the guide plate, tension clamp, and 60E1 rail. These images, captured using a single sensor system, provide a comprehensive representation of real-world scenarios.
High Shader Variance
The dataset features high shader variance to simulate a variety of realistic conditions, ensuring your models can generalize well across different lighting and shadow situations.
Error Categories
The dataset includes various annotated error categories:
- Missing clamp
- Rotated clamp
- Fractured clamp
- Intact clamp
- Screw
- Sleeper
- Rail
These error images cover common defects in railway infrastructure, crucial for training robust detection algorithms.
Use this dataset to train algorithms for automatic detection and classification of railway infrastructure defects, significantly improving maintenance efficiency.
Benefits are:
- Comprehensive Scenarios: Wide range of possible errors and conditions.
- High Quality: High-resolution images with precise annotations.
- Efficient Training: Optimized for training convolutional neural networks (CNNs) and other machine learning models.
- Cost-Effective: Reduces the need for expensive and time-consuming data collection.
