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Ross Kippenbrock - Finding Lane Lines for Self Driving Cars

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Published on Jul 26, 2017

Description
Self-driving cars might not be in our everyday lives yet, but they are coming! Analyzing images and figuring out where the lane lines are on a given roadway is one of the core competencies of any respectable self-driving car. Humans do this with ease and this talk will show you how to find these lines using Python and OpenCV.

Abstract
-Introduction to the OpenCV library (loading images, plotting with matplotlib, etc…)
-Starting with single images, introduce Gaussian blur, region of interest filtering, canny edge detection, Hough transform and draw the lane lines.
-Create a lane line detection pipeline with those functions; extrapolating the lines to represent the boundaries of the lane.
-Process dash cam video using the single image techniques with the pipeline.
-Stitch together images from the processing pipeline to create a sweet video!

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PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

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