RMBG v1.4 is our state-of-the-art background removal model, designed to effectively separate foreground from background in a range of categories and image types. This model has been trained on a carefully selected dataset, which includes: general stock images, e-commerce, gaming, and advertising content, making it suitable for commercial use cases powering enterprise content creation at scale. The accuracy, efficiency, and versatility currently rival leading source-available models. It is ideal where content safety, legally licensed datasets, and bias mitigation are paramount.
FROM: Underscore_ @ YouTube
In order to preserve the opacity/transparency of the layer while using the bucket fill tool, you can click the "Lock Transparency" button in the layers dialog.
Upload photo and find out where images are published
Discovered thanks to Micode: https://www.youtube.com/watch?v=4daO2QM12WY
Downloads any free app and its dependencies from the Microsoft store.
Very useful if you cannot access the Microsoft store on a computer.
Usage example, to install the HEIF image codec to handle .avif images (hope you know what you are doing):
powershell -c "Set-ExecutionPolicy Unrestricted"
powershell .\Download-AppxFromStore.ps1 https://apps.microsoft.com/store/detail/extensions-dimage-heif/9PMMSR1CGPWG
powershell -c "Set-ExecutionPolicy RemoteSigned"
Then run the installer program downloaded.
permet de modifier de façon subtile et imperceptible une image, de sorte qu'elle ne puisse pas être rattachée à un visage sur une autre photo [...] : il retouche très légèrement les traits principaux du visage afin de tromper la reconnaissance faciale. Le procédé s'appuie sur une base de données contenant des visages de célébrités.
En utilisant des visages de stars ressemblant très peu aux photographies originales, les images s'en trouvent étrangement transformées.
«Les changements apportés à [mes] photos sont visibles à l'œil nu. Sur les images modifiées, j'ai l'air morte, ma fille de 3 ans a du duvet sur le visage et mon mari a l'air d'avoir un œil au beurre noir.»
Githup repo: https://github.com/fawkesrobotics/fawkes
Any gif that claims to be showing
60fps
is simply untrue due to the fact that no web browser out there right now supports displaying gifs higher than50fps
. If you try to set your frame rate any higher than what the browser supports (or if you set the frame delay to zero) then most browsers will default to a playback of10fps
(over 5 times slower than you probably intended).
FROM: https://sebsauvage.net/links/?ZYOVJA
À savoir : les navigateurs ne supportent pas les GIF animés à plus de 50 images par seconde (50 fps).
For example, there are three eggs. The left egg is the largest and the front egg is leaning on its side. And from front to back, they are colored purple, yellow, and blue.
What? You do see purple, yellow, and blue, right? Uh... you don't? What colors do you see? Let's make sure that we are talking about the right file...The result is pretty clear: I have one picture (a PNG) that yields NINE different color sets! (Ten if you convert it to JPEG and use LCMS to render it.) The colors that you see are strictly dependent on the specific program that you use to view the image. Even something as minor as calibrating your video driver or patching your software could alter how the image is displayed.
This year, researcher David Buchanan tried to implement parallel decoding using the iDOT information. During development, he made a simple programming mistake and ended up making a wonderful discovery. He could create a PNG file with platform-dependent rendering. It looked one way on Windows, Linux, Firefox, and Chrome, and a different way on a Mac with default Apple applications, like the Safari web browser. (He found that Apple had implemented the same bug!) Buchanan provided two sample pictures (Hello World and computers) to demonstrate this per-platform rendering. It didn't take long for other people to use his code and generate other examples. Many of these images were uploaded to FotoForensics:
Aperi'Solve is an online platform which performs layer analysis on image. The platform also uses zsteg, steghide, outguess, exiftool, binwalk, foremost and strings for deeper steganography analysis. The platform supports the following images format: .png, .jpg, .gif, .bmp, .jpeg, .jfif, .jpe, .tiff...
All of these images were synthesized using two machine learning models, VQGAN and CLIP.
RootAbout is a search-by-image system. You supply a picture, and RootAbout will check if it looks similar to any indexed picture.
For pictures that match, RootAbout provides additional information about the picture and a link to where you can find more information.
TinEye is a reverse image search engine built by Idée currently in beta. Give it an image and it will tell you where the image appears on the web.