The repository contains files to build a object detection model using the yolo pre-trained weights. We have then applied transfer learning to train the model on the Berkley Driving dataset.
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.ipynb_checkpoints
berk_data
model
Extract train labels and store it as CSV .ipynb
LICENSE
README.md

README.md

object-detection-using-yolo

The repository contains files to build a object detection model using the yolo pre-trained weights. Finally, we applied transfer learning to train the model on the Berkley Driving dataset to build an object detection model for a self driving car.

Details to the code and the concepts covered in this code can be found in the blog : Object Detection for Self Driving Car. The blog covers the following concepts:

  • Threshold Filtering
  • Non Max Suppression
  • Intersection over Union (IoU) metrics
  • Anchor Boxes
  • YOLO Algorithm

You can watch the video with the object detection algorithm in action here

If Object Detection seems to be a new word for you, you can learn the basics of object detection through the blog: Introduction to Object Detection.