“Currently, I pay around $30 a month to keep the project active,” he said. It also only responds to one mention per hour, per user as a way to save on infrastructure costs that, as a student, Zambrano can’t easily afford. However, the bot is programmed to respond only every 30 seconds so as not to break Twitter’s rules about spamming. The entire system of capturing an initial mention through responding to a tweet takes only 10 seconds in terms of processing. The completed image is then passed back to Colorize_bot to post on Twitter. Additionally, they seem remarkably robust so that even in moving scenes the renders are very consistent.” Geovanny Zambrano/Colorize_bot “This result leads to nicely deterministic and consistent results, and that means you don’t have track model colorization decisions because they’re not arbitrary. “My best guess is that the models are learning some interesting rules about how to colorize based on subtle cues present in the black-and-white images that I certainly wouldn’t expect to exist,” Antic writes. It just learns this from massive amounts of data, which can then be prodded in the right direction by using the proper algorithms. As Antic explains in a post about the model, even he isn’t totally sure of how it extracts the kind of data it does for colorizing images. The NoGAN tool can be used to colorize both still images and video, although the latter unsurprisingly takes a bit longer. system that has previously been used to create everything from fake human genetic code to A.I. Geovanny Zambrano/Colorize_botĪs described on Github, the model uses a variation of a Generative Adversarial Network (GAN), the discriminator and generator A.I. This one was not created by Zambrano, but is rather an open-source model developed by researcher Jason Antic. Once a mention is captured, processed, and validated, it then gathers the monochrome images and passes them onto another colorization A.I. Whenever a user tags Colorize_bot in a tweet, it is activated instantly using a webhook that monitors for summons 24/7. The first version of the bot - a limited one that could only cope with one single image per tweet - was posted on November 28, 2020.
He started on October 26 and worked for a month, putting in about three or four hours each day. tools, which were freely available online, and transforming them into a colorizing tool.
Zambrano came up with the concept of building on some of these A.I. My goal was just to create ”Īt this point, he remembered a YouTube video he had seen seven months earlier that detailed how machine learning can be used to remaster old photographs. “From a bot that publishes a motivational phrase every hour to a bot ‘hour translator.’ The objective of the project was never to gain followers. These simple software tools, of varying usefulness, can be called on to perform an assortment of autonomous actions on Twitter - whether it’s tweeting links to free e-books on Amazon or mashing together news headlines for comical effect. “I had many ideas,” he said. Finding himself stuck at home with “a lot of free time” on his hands, Zambrano decided to create a Twitter bot to practice his JavaScript skills. “Colorize_bot is without a doubt my best project,” creator Geovanny Zambrano told Digital Trends.Īs with many projects now doing the rounds, Colorize_bot sprang to digital life as a result of the pandemic. How easy? All you need to do is post, or spot, a monochrome image on Twitter and reply to it with Like summoning a colorizing Captain Planet, Colorize_bot - as it is known - will instantly spring into action with its digital Crayolas, leaving the user with a freshly multicolored image and a cheery, “Of course, nice to help you!” This all occurs in the space of just a few seconds.Īnd you’ve got a 21-year old computer science and engineering student from Ecuador - and some nifty A.I. Today, turning black-and-white images into full color photographs is a whole lot easier - and the results far, far better.
0 kommentar(er)
