Importantly, the algorithm was never taught what a Coca Cola logo is - through the magic of CNNs, it figured this out from looking at lots of training data. Given a grayscale historical image with a Coca Cola logo, for example, it correctly colors the logo Coca Cola red - presumably from seeing thousands of training images with red Coca Cola logos. Some pretty remarkable emergent properties bubble up in the algorithm’s results. Doing this was a machine from a grayscale original - even 32% of the time - is quite an accomplishment. People in the Turing test didn’t just believe the image they were seeing was a well-executed hand colorization - rather, they believed the image really was a color image. That doesn’t sound like much, but remember, this task was even harder than just plausibly colorizing a historical image. Its creators report that when the results were shown to humans in a “colorization Turing test”, people believed the colors were real 32% of the time. Original photo credit New York Public Library, colorization by Gado via Colorful Image ColorizationĬolorful Image Colorization was trained on over 1 million images. The Colorful Image Colorization algorithm can add plausible colors to black and white photographs. The algorithm uses several feed-forward passes to ultimately take in a grayscale image, and in the words of the algorithm's creators, “hallucinate” a plausible (though not necessarily correct) set of colors to fill into the image. Training data is easy to obtain here - any color image can be changed to grayscale, and then paired with its color version to make an easy training example. This means you can actually use a Convolutional Neural Network to colorize historical black and white photos.Ĭolorful Image Colorization is an algorithm which uses a CNN to analyze the colors across a set of color images, and their black and white versions. Skies are usually blue (or could plausibly be blue), greenery is green, people’s skin is skin colored, water is blueish, clothes usually aren’t garish or crazy colors, etc.īecause color is more predictable than you’d think, it’s almost more tractable using Machine Learning than you might initially think. In other cases, though, colors are predictable - surprisingly so. are lost forever the second a black and white photo is taken. In many cases, the colors in an image are unique - the exact color of a person’s clothing, the perfect shade of green for a tree, etc. A Deep Learning ApproachĮnter Convolutional Neural Networks. Even with modern tools, hiring an artist to colorize a single historical photo costs between $300 and $500. You have to make decisions about the colors to add in, have the painting skills to place them into the original photo, etc. Hand-colored photos are beautiful, but making them is slow work. Photo credits: Skip Robinson, Petty Officer 3rd Class Aaron Smith and Lance Cpl.Hand colored images, like this lithograph of Cincinnati ca 1840s, were works of art. Department of Defense (DoD) visual information does not imply or constitute DoD endorsement. Products may be shown with optional equipment and upgrades. reserves the right to change product designs and specifications without notice. will not be responsible for damages (of any kind or nature, including incidental, direct, indirect, or consequential damages) resulting from the use of or reliance on this information. makes no representations or warranties, either expressed or implied, including without limitation any warranties of merchantability or fitness for a particular purpose with respect to the information set forth herein or the product(s) and service(s) to which the information refers. For performance data and operating limitations for any specific mission, reference must be made to the approved flight manual. Individuals using this information must exercise their independent judgment in evaluating product selection and determining product appropriateness for their particular purpose and requirements. The information herein is general in nature and may vary with conditions. All registered trademarks are the property of their respective owners.
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