2025-12-09 –, General Track
Are you a scientist or a developer looking to understand how to use NumPy to solve computer vision problems?
NumPy is a Python package that provides the multidimensional array object which you can use to solve the lane detection problem in computer vision for self-driving cars or autonomous driving. You can apply non-machine learning techniques using NumPy to find the straight lines on street images. No other external libraries, just python with NumPy.
Car accidents happen every day. Lane detection is a common use case in computer vision and self-driving which can help prevent accidents by identifying the boundaries of driving lanes on an image of a road scene. It is a fundamental requirement for autonomous vehicles to drive safely on the roads.
In my talk, “Lane detection in self-driving using only numpy”, I will share my learning experience on how to solve a computer vision problem with a small dataset.
Outline of my talk: 25-27 minutes
2 minutes - the problem
5 minutes - What is NumPy and the steps of the algorithm, & the methods (Create Arrays using NumPy functions, Array slicing, indexing, math using NumPy Broadcasting)
10 minutes - edge detection algorithms
10 minutes - ROI extraction, hough transform and detecting the lines
Emma Saroyan is the co-author of "Generative AI for Web Development: Building Web Applications Powered by OpenAI APIs and Next.js", published by Apress. She is an active speaker in the open-source and AI communities, having presented talks at PyData NYC and PyData Boston meetups in 2025, as well as at various open-source and AI events across the U.S. and Europe. A passionate advocate for AI, diversity, and open collaboration, Emma leads the PostgreSQL User Group in Armenia and serves on the DISC Committee of NumFOCUS, supporting diversity and inclusion initiatives across global open-source ecosystems.