Roboflow Universe usdacranberrybreeding CranCart_BerryFinder_GoPro

CranCart_BerryFinder_GoPro Computer Vision Project

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This objective of this project is to use RGB images to count and size berries in each of many cranberry breeding plots. The end goal is to develop a pipeline that will allow us to estimate yield, fruit rot incidence, fruit quality, foliar disease incidence on many more breeding plots than might be possible using visual assessment.

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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.

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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{
                            crancart_berryfinder_gopro_dataset,
                            title = { CranCart_BerryFinder_GoPro Dataset },
                            type = { Open Source Dataset },
                            author = { usdacranberrybreeding },
                            howpublished = { \url{ https://universe.roboflow.com/usdacranberrybreeding/crancart_berryfinder_gopro } },
                            url = { https://universe.roboflow.com/usdacranberrybreeding/crancart_berryfinder_gopro },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { mar },
                            note = { visited on 2024-04-27 },
                            }