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This video tutorial focuses on creating a custom object detector that can detect a koala, although other objects can be chosen. The process is divided into three steps: preparing the images for training with Yolo, uploading the images to Google servers for processing on the cloud GPU for free, and testing the model to ensure its effectiveness. The image dataset for training should contain multiple images of the chosen object, such as the 350 koala images used in the example.
