nuaayxy / advancelane Goto Github PK

In this project, we create a pipeline to identify the lane boundaries in a video, the main function and code in detect.py I saved examples of the output from each stage in the folder called output_images There is also a video result

There are issues when in the shadows or light changes suddenly, the lanes detected will tend to fail, then what i rely on is the previously successfully detected lines. There are several safe proof way to avoid sudden jump

• check number of detected binary pixels and if below threshold we search around previous detected poly
• use a moving average of the lane filter away some jumps
• Use of different color spaces and combine them together such as LAB/HSV with gradients

Futher improvement would be using deep learning method for more robust detection especially these edge cases when lighting changes rapidly and we cannot hand engineer everything

The steps of this project are the following:

• Compute the camera calibration matrix and distortion coefficients given a set of chessboard images.(done)
• Apply a distortion correction to raw images.(done)
• 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.