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Deep Dive into Object Detection with YOLO

Exercise: Using the Albumentations Library for Augmentations

Explore how to use the Albumentations library to create custom image augmentation pipelines that modify brightness, contrast, saturation, hue, and spatial features, while correctly updating bounding boxes. This lesson helps you understand applying multiple transformations to enhance model robustness and data diversity in object detection tasks.

We'll cover the following...

Playground

Using an image, we will implement a technique to produce two variations of the image by adjusting its brightness, contrast, saturation, and hue.

Functions to learn before coding

  • The Compose function: It is used to combine multiple image transformation operations. Each transformation is applied sequentially in the order it appears in the list.

  • The HorizontalFlip function: This is a transformation that flips an image horizontally (like a mirror effect). Here are its parameters:

    • p: It is the probability of applying the augmentation. If p=1, it will always flip the image, while if p=0, it will never flip the image. A p=0.5 means there’s a 50% chance to apply the flip.

  • The augmentation probability (p) function: For many ...