LA PV Instance Segmentation Dataset and Pre-Trained Model by HaifengLAN

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Explore Dataset

Here are a few use cases for this project:

Energy Optimization: Energy companies could use the "LA PV" model to identify the location and distribution of photovoltaic (PV) systems in Los Angeles (LA) to optimize energy feed into the electrical grid and improve load balancing.
Solar Energy Potential Analysis: Urban planners or local governments could employ the model to analyze the potential for expansion of solar energy in specific neighborhoods of LA.
Environmental Research: Environmental scientists might use this model to research the influence of urban solar power on local ecological systems.
Real Estate Development: Property developers or investors could leverage this model to locate ideal areas lacking in photovoltaic systems for potential green building projects.
Infrastructure Upgrade Planning: Utility providers could use this computer vision model to plan infrastructure upgrades or replacements based on the model's identification of PV installations sites. This could help prevent accidental damage of the PV installations during the upgrade process.

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{
                            la-pv_dataset,
                            title = { LA PV Dataset },
                            type = { Open Source Dataset },
                            author = { HaifengLAN },
                            howpublished = { \url{ https://universe.roboflow.com/haifenglan/la-pv } },
                            url = { https://universe.roboflow.com/haifenglan/la-pv },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-05-10 },
                            }