Items tagged computervision in 2018
Filters: Year: 2018 × computervision × Sorted by date
jantic/DeOldify (via) “A Deep Learning based project for colorizing and restoring old images”. Delightful (and well documented) project that uses a Self-Attention Generative Adversarial Network to colorize old black and white photos, with extremely impressive results. Built on an older version of the fastai library, and trained by running for several days on a 1080TI graphics card. # 2nd November 2018, 11:13 am
Automatically playing science communication games with transfer learning and fastai
This weekend was the 9th annual Science Hack Day San Francisco, which was also the 100th Science Hack Day held worldwide.
[... 1174 words]BearID: Bear Face Detector. Comprehensive tutorial on building a computer vision system to identify faces of bears, using dlib and the Histogram of Oriented Gradients (HOG) technique. Bears! # 1st March 2018, 5:31 pm
Family fun with deepfakes. Or how I got my wife onto the Tonight Show. deepfakes is dystopian nightmare technology: take a few thousand photos of two different people with similar shaped faces and you can produce an extremely realistic video where you swap one person’s face for the other. Unsurprisingly it’s being used for porn. This is a pleasantly SFW explanation of how it works, complete with a demo where Sven Charleer swaps his wife Elke for Anne Hathaway on the Tonight Show. # 2nd February 2018, 4:06 pm
6M observations total! Where has iNaturalist grown in 80 days with 1 million new observations? Citizen science app iNaturalist is seeing explosive growth at the moment—they’ve been around for nearly a decade but 1/6 of the observations posted to the site were added in just the past few months. Having tried the latest version of their iPhone app it’s easy to see why: snap a photo of some nature and upload it to the app and it will use surprisingly effective machine learning to suggest the genus or even the individual species. Submit the observation and within a few minutes other iNaturalist community members will confirm the identification or suggest a correction. It’s brilliantly well executed and an utter delight to use. # 28th January 2018, 8:18 pm