f-r-d Object Detection Dataset and Pre-Trained Model by joe duprez

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Explore Dataset

Here are a few use cases for this project:

Solar Panel Installation Planning: The "f-r-d" model can be used to identify suitable flat-roof surfaces for solar panel installation. By recognizing flat roofs with or without pre-existing photovoltaic (PV) systems, solar installation companies can target ideal residential and commercial properties for solar panel installations, increasing efficiency and reducing costs.
Urban Heat Island Mitigation: Urban planners can use the model to analyze aerial images of cities and identify flat-roofed buildings that can benefit from green roof installations or light-colored roofing materials. These solutions can help reduce the heat island effect in urban areas, improving air quality and overall livability.
Building Energy Efficiency Analysis: The "f-r-d" model can assist energy consultants and auditors in identifying buildings with flat roofs for potential energy efficiency upgrades. By detecting the presence (or absence) of PV systems or reflective roofing materials, experts can develop targeted strategies to reduce energy consumption for these properties.
Insurance Risk Assessment: Insurance companies can use the "f-r-d" model to evaluate the risk of property damage associated with flat-roof structures. By identifying the presence of PV systems or the level of maintenance on flat-roofed buildings, insurers can better estimate the likelihood of roof-related claims and set premiums accordingly.
Drone-based Roof Inspection and Maintenance: Maintenance companies can utilize the "f-r-d" model in combination with drone-based mapping technologies to identify flat-roof structures that may require inspection or repairs. This can help streamline the inspection process and prioritize maintenance tasks, ultimately reducing costs and extending the lifespan of roofing materials.

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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            f-r-d_dataset,
                            title = { f-r-d Dataset },
                            type = { Open Source Dataset },
                            author = { joe duprez },
                            howpublished = { \url{ https://universe.roboflow.com/joe-duprez-nje2m/f-r-d } },
                            url = { https://universe.roboflow.com/joe-duprez-nje2m/f-r-d },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-06-28 },
                            }