Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 2 Next »

As part of our effort to make computer vision accessible to viticulturists, we trained several flower cluster object detection models. These models can be used to automatically detect and count visible clusters in images.

You may be wondering, ‘why create several models to count grape clusters?’ Good question. With so many varieties, locations, trellis systems, etc. it is hard to accurately represent all variations of clusters in a single model. We also tested model training at night with artificial lights and during the day. We captured images in New York, California, and Washington. As we refine our models, we may add more options to choose from or we may consolidate some of them. Either way, you will have to consider which model will best reflect the conditions that you are capturing images in in your vineyards. Are you collecting at night? Then perhaps our nighttime model is the best fit.

Getting Started

To start off, you’ll need a few things to get started:

  • No labels