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Overview

The Weeds dataset is a collection of garden weeds that can easily confuse object detection models due to similiarity of the weeds compared to its surroundings. This dataset was used with YOLOR for object detection to detect weeds in complex backgrounds.

Example Footage!

Weeds Detection

Training and Deployment

The weeds model has been trained in Roboflow, available for inference on the Dataset tab.

One could also build a Weeds Detector using YOLOR. This is achieved using the Roboflow Platform which you can deploy the model for robust and real-time detections. You can learn more here: https://augmentedstartups.info/YOLOR-Get-Started

About Augmented Startups

We are at the forefront of Artificial Intelligence in computer vision. With over 92k subscribers on YouTube, we embark on fun and innovative projects in this field and create videos and courses so that everyone can be an expert in this field. Our vision is to create a world full of inventors that can turn their dreams into reality

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{
                            weeds-nxe1w_dataset,
                            title = { Weeds Dataset },
                            type = { Open Source Dataset },
                            author = { Augmented Startups },
                            howpublished = { \url{ https://universe.roboflow.com/augmented-startups/weeds-nxe1w } },
                            url = { https://universe.roboflow.com/augmented-startups/weeds-nxe1w },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2021 },
                            month = { nov },
                            note = { visited on 2024-04-26 },
                            }