ALL_image Object Detection Dataset and Pre-Trained Model by Hanshin University

Images

3384 images

Explore Dataset

Here are a few use cases for this project:

Power Infrastructure Monitoring: Use the ALL_image model to analyze images captured by drones or ground-based cameras to monitor the condition and status of power transmission components, such as insulators, arresters, transformers, and electric poles. This can improve maintenance efficiency and prolong the lifespan of the infrastructure.
Vegetation Management near Power Lines: Identify nearby trees and other vegetation that could pose a risk to power lines and equipment. The model can help utility companies plan and prioritize tree trimming or removal activities to minimize the risk of outages caused by falling limbs or trees.
Damage Assessment in Disaster Recovery: In the aftermath of natural disasters, such as hurricanes or earthquakes, the ALL_image model can process images from affected areas to identify damaged power infrastructure components. This helps prioritize repair efforts and accelerate the restoration of electricity.
Power Network Expansion Planning: Use the model to process aerial or satellite images, identifying existing electric lines, transformers, and other components. Analyzing this data allows for better planning and efficient expansion of the power grid in growing urban and rural areas.
Training and Education: The ALL_image model can be used as a training tool for electrical engineers and technicians to learn about different transmission components and their organization within the power grid. Students can use the model to practice identifying components in real-world images, improving their understanding of the electrical infrastructure.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            all_image_dataset,
                            title = { ALL_image Dataset },
                            type = { Open Source Dataset },
                            author = { Hanshin University },
                            howpublished = { \url{ https://universe.roboflow.com/hanshin-university/all_image } },
                            url = { https://universe.roboflow.com/hanshin-university/all_image },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-05-07 },
                            }