A socially distant Central Park?
A socially distant Central Park?
Photo by Alex Simpson on Unsplash

The COVID-19 pandemic has brought a lot of changes to New York City from its usual day to day hustle & bustle. Subway ridership is down 90% of its usual riders, rents in Manhattan are falling quickly while apartment vacancies are at a peak, and even foot traffic is down in many NYC neighborhoods. In the early days of the pandemic, New Yorkers were encouraged to stay at home by Governor Cuomo’s NY on Pause initiative. …


Cron allows you to schedule repeat tasks, making it a great tool to run data collection scripts

Image for post
Image for post
Photo by Nick Chong on Unsplash

A major concern when collecting time series data is ensuring that all data is collected at equal time intervals. Without equal time intervals, you will be unable to use most methods for time series analysis. Unfortunately, not all data comes so clean and evenly spaced. Whether you are webscraping or using an API to collect your data, you may be stuck with a live feed of current data when evenly spaced historical data is unavailable. Or perhaps, you need to repeatedly grab the most up-to-date data for your dashboard or project. …


Getting Started

Using pre-existing computer vision models for object detection

Image for post
Image for post
Photo by Daiga Ellaby on Unsplash

In my last blog, I discussed some basics concepts of computer vision and how to create a facial recognition filter using OpenCV. But what if you want to detect in an image something other than faces? There are two possible ways forward:

  1. Train your own model: If you have a lot of images ready to go of the object you are trying to identify, using OpenCV’s built-in functions (like k-Nearest-Neighbors) or more powerful machine learning libraries like PyTorch and TensorFlow you could build your own model. However, this would mean that you need hundreds if not thousands of images at your disposal that all display your object of interest. Creating a model for these could also take time, hard drive space, and computer power. …


Hands-on Tutorials

Image for post
Image for post
Image by teguhjati pras; Creative Commons License via Pixabay

Over the past 10 years, Facial recognition technology has developed rapidly and has quickly developed a variety of uses. From the utilitarian (unlocking your phone), to playful (Instagram filters), to the controversial (security, surveillance, and policing), our faces can be used by tech in many ways. Curious about how to create some facial recognition tech yourself? Facebook offers the SparkAR platform to create facial recognition filters for Facebook and Instagram. However, we can pretty easily create one ourselves using the OpenCV package in python, so we can use facial recognition anywhere.

Background Info: How do computers “see”?

To a computer, images are just a series of numbers indicating where pixels are located. Computer programmers can create algorithms that teach computers how to identify unique features in images. Interestingly, computers “see” similarly to how humans solve jigsaw puzzles. …

About

Mitchell Krieger

Mitch Krieger lives in NYC // Board of Directors at L!FE Leaders Inc. // Formerly: NYU Tisch and CITYterm at the Masters School // Hampshire College alum

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store