CVAT Image Annotation Tool

In the last few chapters, we exercised our skills with object detection and semantic segmentation CNNs by downloading pretrained weights and using them as is. We’ll probably never do this in a real-life automated inspection project unless working on an application that detects cats, dogs, and pedestrians in images of urban scenes.

A more realistic scenario would imply transfer learning or fine-tuning a pretrained CNN on an image dataset of the objects that matter for your inspection task. That means building our dataset with a sample of images we want to inspect, including examples of the defects, if applicable.