From the course: Hands-On Data Annotation: Applied Machine Learning

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Image bounding box annotation for object detection in GCP

Image bounding box annotation for object detection in GCP

From the course: Hands-On Data Annotation: Applied Machine Learning

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Image bounding box annotation for object detection in GCP

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To prepare training data for object detection in machine learning, you need to draw bounding boxes around the object of interest. To create bounding boxes in Vertex AI on GCP, log in into your console at console.cloud.google.com and select the project. If you do not have a project, create one. In the project search, search for Vertex AI. On the Vertex AI dashboard on the left pane, scroll down to Data Sets. In data sets, create a new project. Let's call it car-bounding-boxes. And under image, select image object detection. Now let's add our data set. We are uploading images from the computer. It's the cars-on-the-street data set. So select all and add. While the data is being uploaded, here we can see GCP's definition of object detection. It says object detection models draw bounding boxes around item or object of interest. For example, in their sample image you could be identifying vegetables from images of food. This time around, we will be identifying cars from images of cars…

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