From the course: Deep Learning with Python: Convolutional Neural Networks

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Using a pretrained model for image classification in Python

Using a pretrained model for image classification in Python - Python Tutorial

From the course: Deep Learning with Python: Convolutional Neural Networks

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Using a pretrained model for image classification in Python

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- [Presenter] In this tutorial, you'll learn how to use a pre-trained "YOLO" model for image classification. Before we begin, let's select our Kernel. By the end of this tutorial, you'll know how to load and prepare a YOLO image classification model for inference. You also know how to run inference and interpret "raw" and "formatted" outputs, including "top one" and "top five" predictions. The first thing we do is import the YOLO class and load the pre-trained classification model. Once that's complete, we now specify the path or the image we want to classify. However, before we actually classify this image, let's take a look at it just to confirm that the image that we specified is the image that we actually do want to classify. So that looks right. Now we get into the classification process. To classify this image, we pass the path of the image to the YOLO model we loaded previously. So the output is a summary line showing the "Full Path", the "Resize Dimensions", the "Top class…

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