AI processing tool that removes watermarks from images
Dr. Watermark is an AI online image processing tool that mainly removes various watermarks such as text, logos, and characters from images. It can also remove full screen watermarks. You only need to upload the image and it can be processed within 5 seconds
I've tried it on several images; it works better on photos than on vectors and, unfortunately, it's not always good at guessing what it should draw in place of watermarks 😔 As other commenters have mentioned, the idea is interesting, and this tool can be handy and help restore your own watermarked image in some situations. However, the question of its legality arises in situations where people may obtain images from stock sources and remove watermarks to avoid payment, but its, I guess, more on
While surfing the web, I chanced upon Watermark.phd, a hidden gem amongst online tools. It marvelously removes watermarks from images, removes background and can even eliminate full-screen watermarks with precision. It's very easy to use. Just upload an image and apply it to the watermark you want to remove. The AI will automatically remove the watermark within 5 seconds. If you are also looking for such a tool, you can try it out. If it works well, I look forward to your feedback.
Aha this is questionable ethically, no? I can imagine people will want to use it
What are your thoughts on individuals using this tool to remove a watermark from other people's content and post them as theirs?
I feel it is disgusting that software like this exists. Remove a watermark and present it as your own. There is no legitimate reason for this to exist. Shame on you
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.
Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.