Udacity Self-Driving Car Engineer Nanodegree: Project 1 - Finding Lane Lines on the Road
In this project, you will use the tools you learned about in the lesson to identify lane lines on the road.
You can develop your pipeline on a series of individual images, and later apply the result to a video stream (really just a series of images).
The tools you have are:
- Color selection
- Region of interest selection
- Grayscaling
- Gaussian smoothing
- Canny Edge Detection
- Hough Tranform line detection
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Follow the instructions in: this README.
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Learning more about Anaconda and Jupyter Notebooks.
- Launch the Jupyter notebook with Anaconda or Docker.
# Anaconda
source activate carnd-term1 # If currently deactivated, i.e. start of a new terminal session
jupyter notebook finding_lane_lines.ipynbcv2.inRange() for color selection
cv2.fillPoly() for regions selection
cv2.line() to draw lines on an image given endpoints
cv2.addWeighted() to coadd / overlay two images cv2.cvtColor() to grayscale or change color cv2.imwrite() to output images to file
cv2.bitwise_and() to apply a mask to an image