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Analyzing The Papers Behind Facebook’s Computer Vision Approach

Analyzing The Papers...

Introduction You know that company called Facebook? Yeah, the one that has 1.6 billion people hooked on their website. Take all of the happy birthday posts, embarrassing pictures of you as a little kid, that one family relative that likes every single one of your statuses, and you have a whole lot of data to […]

Image Processing in Python

Image Processing in ...

This was originally posted on the Silicon Valley Data Science blog.  The first step in developing our Caltrain project was creating a proof of concept for the image processing component of the device we used to detect passing trains. We’re big fans of Jupyter Notebooks at SVDS, and so we’ve created a notebook to walk […]

Introduction to Trainspotting

Introduction to Trai...

This was originally posted on the Silicon Valley Data Science blog. At Silicon Valley Data Science, we have a slight obsession with the Caltrain. Our interest stems from the fact that half of our employees rely on the Caltrain to get to work each day. We also want to give back to the community, and […]

Feature Learning Escapades

Feature Learning Esc...

Act I: Google Research Summer Internship 2011 Disclaimer: The following post was brought out of the archives on Andrej Karpathy’s blog for your viewing here.  Hanging out at Google in 2011 The thread of this paper begins in Summer of 2011, when I accepted a summer internship offer from Google Research. My project involved Deep Learning for videos, as […]

Deep Reinforcement Learning: Pong from Pixels

Deep Reinforcement L...

This is a long overdue blog post on Reinforcement Learning (RL). RL is hot! You may have noticed that computers can now automatically learn to play ATARI games (from raw game pixels!), they are beating world champions at Go, simulated quadrupeds are learning to run and leap, and robots are learning how to perform complex manipulation […]

Bring It All Together: Panorama Stitching with OpenCV

Bring It All Togethe...

In a few lines of Python, Adrian Rosebrock, a computer vision expert, shows how to stitch together two photos of a landscape into one large panorama using OpenCV. The process involves: detecting key points, matching descriptors, estimating a homographic matrix with the RANSAC algorithm, and finally applying a warping transformation.

Walk This Way, Safely

Walk This Way, Safel...

This may be why self-driving cars will be safer than human driven ones. Using OpenCV and Python and the fact that we all have a head, two arms, a torso, and two legs, Adrian Rosebrock, a Computer Vision & Machine Learning expert, guides us through pedestrians detection with impressive results. He explains methodologies such as […]

Analyzing 91 Years of Time Magazine Covers for Visual Trends

Analyzing 91 Years o...

Adrian Rosebrock (@PyImageSearch) is an expert in computer vision. In this blog post Rosebrock creates a dataset out of Time magazine’s covers from the 1920s to now and exposes some interesting findings using python and the opencv image processing package. An excellent python script is given and explained. This is a great post that combines creating […]