solarFinder Instance Segmentation Dataset and Pre-Trained Model by Solarfinderlabel

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Explore Dataset

Here are a few use cases for this project:

Solar Panel Installation Analysis: solarFinder could be used by installation companies to optimally design solar setups by avoiding areas detected as trees or shadow. This will help increase the efficiency of the solar panels by allowing maximum sunlight exposure.
Solar Potential Assessment: Real estate agencies or homeowners could use solarFinder to understand the potential for solar panel installation on a property by identifying suitable spaces.
Energy Efficiency Audit: Green energy consultants and auditors could use this model to conduct energy efficiency audits on properties, identifying how many panels are installed, and if their placement can be optimized further.
Urban Planning and Development: City planners could employ this computer vision model to evaluate the solar energy potential of buildings in a city, thereby aiding in sustainable urban planning and development efforts.
Satellite Imagery Analysis: The model could be used to analyze satellite imagery to track the adoption and prevalence of solar panels at a regional or national level. This can be particularly useful for policymakers and researchers studying renewable energy trends.

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{
                            solarfinder_dataset,
                            title = { solarFinder Dataset },
                            type = { Open Source Dataset },
                            author = { Solarfinderlabel },
                            howpublished = { \url{ https://universe.roboflow.com/solarfinderlabel/solarfinder } },
                            url = { https://universe.roboflow.com/solarfinderlabel/solarfinder },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { aug },
                            note = { visited on 2024-06-18 },
                            }