{"id":2911,"date":"2024-01-16T09:50:31","date_gmt":"2024-01-16T01:50:31","guid":{"rendered":"https:\/\/www.1ai.net\/?p=2911"},"modified":"2024-01-16T09:50:31","modified_gmt":"2024-01-16T01:50:31","slug":"ddcolor-%e9%ab%98%e5%ba%a6%e7%9c%9f%e5%ae%9e%e7%9a%84ai%e5%9b%be%e5%83%8f%e7%9d%80%e8%89%b2%e5%b7%a5%e5%85%b7","status":"publish","type":"post","link":"https:\/\/www.1ai.net\/en\/2911.html","title":{"rendered":"DDColor: Highly realistic AI image colorization tool"},"content":{"rendered":"<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-2910\" src=\"https:\/\/www.1ai.net\/wp-content\/uploads\/2024\/01\/6384093362179703492885678.jpg\" alt=\"\" width=\"1296\" height=\"626\" \/><\/p>\n<p><a href=\"https:\/\/www.1ai.net\/en\/tag\/ddcolor\" title=\"[See articles with [DCLOOR] labels]\" target=\"_blank\" >DDColor<\/a>Is a photo-realistic image<a href=\"https:\/\/www.1ai.net\/en\/tag\/%e7%9d%80%e8%89%b2%e5%b7%a5%e5%85%b7\" title=\"[Sees articles with labels]\" target=\"_blank\" >Coloring Tools<\/a>, using dual decoder technology, self-learning image content, and achieving highly realistic colorization effects for historical black-and-white photos and animation scenes. The working principle includes encoder analysis of images, multi-scale feature extraction, colorization decision and decoder output combination, while introducing a color richness loss function to innovatively improve the color saturation and attractiveness of the generated images. For more information, please visit the project address.<\/p>\n<p>DDColor is the latest image colorization algorithm. It takes a black-and-white image as input and returns a color image after colorization. It can also achieve natural and vivid colorization effects. This model is a black-and-white image colorization model. It takes a black-and-white image as input, realizes end-to-end full-image colorization, and returns a color image after colorization. Expected usage and scope of application of the model: This model is applicable to image inputs in various formats. Given a black-and-white image, it generates a color image after colorization. Given a color image, it automatically extracts the grayscale channel as input to generate a re-colored image.<\/p>\n<p class=\"detail-dl-div-item-t\" data-v-86be4cee=\"\">Product Features:<\/p>\n<p class=\"detail-dl-div-item-c\" data-v-86be4cee=\"\">Input a black and white image and generate a colored image<\/p>\n<p class=\"detail-dl-div-item-c\" data-v-86be4cee=\"\">Input a color image and automatically extract the grayscale channel to generate a recolored image<\/p>\n<p data-v-86be4cee=\"\">Official website address: <a href=\"https:\/\/www.modelscope.cn\/models\/damo\/cv_ddcolor_image-colorization\/summary\">https:\/\/www.modelscope.cn\/models\/damo\/cv_ddcolor_image-colorization\/summary<\/a><\/p>","protected":false},"excerpt":{"rendered":"<p>DDColor is a photo-quality, realistic image coloring tool that uses dual-decoder technology to self-learn image content and achieve highly realistic coloring effects for historical black and white photos and anime scenes. The working principle includes a combination of encoder analysis of the image, multi-scale feature extraction, coloring decision and decoder output, while a color richness loss function is introduced to innovatively improve the color saturation and attractiveness of the generated image. Detailed information can be found at the project address. DDColor is the latest image coloring algorithm that inputs a black-and-white image and returns a color image after the colorization process, and is capable of achieving natural and vivid coloring effects. The model is a black-and-white image coloring model that inputs a black-and-white image, achieves end-to-end full-image coloring, and returns a color image after color processing. The model is expected to be used in a way and suitable for<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[138,142],"tags":[928,931],"collection":[],"class_list":["post-2911","post","type-post","status-publish","format-standard","hentry","category-product","category-tuxiang","tag-ddcolor","tag-931"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/2911","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/comments?post=2911"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/2911\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=2911"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=2911"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=2911"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=2911"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}