The goals / steps of this project are the following:
- Compute the camera calibration matrix and distortion coefficients given a set of chessboard images.
- Apply the distortion correction to the raw image.
- Use color transforms, gradients, etc., to create a thresholded binary image.
- Apply a perspective transform to rectify binary image ("birds-eye view").
- Detect lane pixels and fit to find lane boundary.
- Determine curvature of the lane and vehicle position with respect to center.
- Warp the detected lane boundaries back onto the original image.
- Output visual display of the lane boundaries and numerical estimation of lane curvature and vehicle position.
The images for camera calibration are stored in the folder called camera_cal. The images in test_images are for testing your pipeline on single frames. The video called project_video.mp4 is the video your pipeline should work well on. challenge_video.mp4 is an extra (and optional) challenge for you if you want to test your pipeline.
If you're feeling ambitious (totally optional though), don't stop there! We encourage you to go out and take video of your own, calibrate your camera and show us how you would implement this project from scratch!