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To help with this process, we have developed some open resources that can use a cellphone video as input, and a cluster count as output. We have written a public Google Colaboratory (Colab) that is freely available and can detect, track, and count flower clusters in video files. This makes it possible to get a rough count of clusters over a given distance in a vineyard. Here we’ll walk you through the steps to use our Colab notebook—a free tool from Google—to upload and analyze your own cluster videos using one of our pre-trained models. This Colab notebook is compatible with custom object detection models as well.
Getting Started
To use our video cluster counter, you will need a few things:
A Google Account
Colaboratory runs on Google Drive
A video file
This is the actual video of your grapes. We will talk about capturing this video file below.
Capturing Video
In this tutorial we will be using ‘nighttime-grape-flower-clusters/1’ which is a nighttime cluster counting model. You can explore our other cluster counting models, leverage any Roboflow Universe models, or even train your own model.
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Credit: The data used to train nighttime-grape-flower-clusters/1 was originally captured and trained by Jonathan Jaramillo as part of his PHD research which motivated the creation of this guide. Read the original paper >> |
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Note: ‘nighttime-grape-flower-clusters/1’ is a nighttime only model. This means you’ll need to capture your video at night using a lighting source. We recommend placing light sources a few feet above and/or below your camera as in the figure below:  |