In this task, you'll dive into the world of object detection using deep learning. First, you'll build your own object detection model from scratch using Keras. Then, you'll load a pretrained YOLOv8 model and apply it to the same dataset.

Along the way, you'll:

• Train a simple Keras-based object detector;

• Load and run predictions with a YOLOv8 model trained on the same data;

• Evaluate its performance on real validation images;

• Compare results and understand the gap between custom models and state-of-the-art ones.

In the middle of the notebook, you'll reflect on why building detection models from scratch can be limiting — and briefly mention the importance of **transfer learning88 for practical applications.