In this project, the goal is to write a software pipeline to identify the lane boundaries in a video, but the main output or product we want you to create is a detailed writeup of the project.
The goals / steps of this project are the following:
- Compute the camera calibration matrix and distortion coefficients given a set of chessboard images.
- Apply a distortion correction to raw images.
- 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 the lane boundary.
- Determine the 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. If you want to extract more test images from the videos, you can simply use an image writing method like cv2.imwrite(), i.e., you can read the video in frame by frame as usual, and for frames you want to save for later you can write to an image file.
Each step of the pipeline was saved in output_images and output_transformations. Folders like output_images_challenge, challenge_images were used to tune the pipeline.
The final video called videos_output/improved_project_video.mp4 is the video my pipeline works well on and is the processed result of 'project_video'
For mode details refer to the writeup.
