Challenge: Object Detection with Custom Model and YOLO
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 β and briefly mention the importance of **transfer learning88 for practical applications.
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Completion rate improved to 3.45Challenge: Object Detection with Custom Model and YOLO
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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 β and briefly mention the importance of **transfer learning88 for practical applications.
Thanks for your feedback!
