Class Project Cat, Dog and Duck

This video tutorial guides viewers through setting up a project for image recognition using machine learning. It covers collecting images of cats, dogs, and ducks, training a model, and testing it using Scratch. The tutorial also explains programming logic for image recognition and evaluates the confidence levels of predictions.

What is the first step in setting up a new image recognition project?

• Collecting images from Google

• Naming the project and selecting the type

• Training the machine learning model

• Uploading images as costumes

How many images are required for each label in the project setup?

• 10 images

• 5 images

• 15 images

• 20 images

What is the purpose of uploading images as costumes in Scratch?

• To animate the images

• To test the machine learning model

• To create a slideshow

• To change the background

In the program logic, what does the variable 'item' represent?

• The confidence level of the prediction

• The number of the picture being shown

• The size of the image

• The position of the image

How is the confidence level of a prediction determined in the program?

• By comparing it with a standard image

• By using a confidence block in Scratch

• By checking the image size

• By manually calculating it