waldo30_yolov8n_416x416 Computer Vision Project
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The WALDO30 model, developed by StephanST, is a family of object detection models built on the YOLOv8 architecture. It can identify a variety of objects, such as vehicles, people, buildings, and solar panels, in overhead and satellite imagery. The model is optimized for civilian use, with a focus on applications like disaster recovery, infrastructure monitoring, and traffic management. It is available under an MIT license, and users can fine-tune or modify it for specific use cases.
StephanST did not release the dataset behind the model, so in this dataset there are 10 images representative of those the model was trained on. This is a YOLOv8n model and was trained on images sized to 416x416.
For more details, you can visit the Hugging Face page here. The goal is to enable Roboflow users to use this model out of the box and as a training checkpoint.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
waldo30_yolov8n_416x416_dataset,
title = { waldo30_yolov8n_416x416 Dataset },
type = { Open Source Dataset },
author = { WALDO30 },
howpublished = { \url{ https://universe.roboflow.com/waldo30-cxwho/waldo30_yolov8n_416x416 } },
url = { https://universe.roboflow.com/waldo30-cxwho/waldo30_yolov8n_416x416 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { oct },
note = { visited on 2024-12-21 },
}