rembg
U-2-Net
rembg | U-2-Net | |
---|---|---|
52 | 30 | |
14,536 | 8,115 | |
- | - | |
7.9 | 3.1 | |
13 days ago | 4 months ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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rembg
- Rembg: Tool to Remove Images Background
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π Background Removal in Python with PyTorch and Rembg! π¨π
A bit conflicted as the linked video is also linked from the actual rembg repo but it seems way faster and more detailed to just read the readme at that repo first, and maybe use a video if something doesnβt make sense.
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Ask HN: How does MS-Teams, Meets and Zoom virtual background works?
There are open source tools like rembg (https://github.com/danielgatis/rembg) which call into pre-trained models.
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Lora Training - how to not train background?
You can use Rembg extension to remove background automatically: https://github.com/danielgatis/rembg
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[Question] where to deploy remove background using u2net ml app ? (ec2, lambda or else?)
Hi guys π· I am new to ml deployment. Can anyone help about production deployment ? I made fastapi docker app which removes background from image (https://github.com/danielgatis/rembg). It uses u2net segmentation. I tried aws ec2, lambda, googld cloudrun and so far ec2(t2-large) is the fastest but still too slow. Also, it costs way more than I expected. Are there any other solution that I can deploy ml app with as low as possible? Where do you guys mostly deploy ml app?
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lineart_coarse + openpose, batch img2img
I am currently using rembg https://github.com/danielgatis/rembg
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Newgen / regen face revamp project (AI powered) - once and for all!
rembg
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The new Controlnet lineart is great for sprite sheets/2D animations when combined with Canny. The top left was input and the other three were just Controlnet with no inpainting or upscaling.
A python script with rembg could work
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Useful utilities that will help when trying to make stuff
4.) rembg -- backgrounds be gone. If there isn't an extension in Automatic1111 for this yet, there should be (I haven't checked recently). Same deal as midas, you can point it at a folder and zap the backgrounds off of all your images. Useful in combo with midas and imagemagick if, for instance, you want images of an object on a white background (Stable Diffusion training via LoRAs/Dreambooth may not benefit, but other things like GANs prefer that sort of training image). Useful if you want to "compose" a scene and you have images of dispirate objects/people you want in that scene.
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Just a reminder that there is a new 'remove background' extension for a1111
Ran into another issue with " LoadLibrary failed with error 126 Here's the solution: https://github.com/danielgatis/rembg/issues/312
U-2-Net
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I used the ChatGPT API to create a proof-of-concept AI driven video game. Using generative AI for the images and dialogue and GPT-3.5 for narrative and game control. More info in comments.
I use a finetuned custom Stable Diffusion model in combination with a style embedding for the characters for image generation and UΒ²-Net for background removal.
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[Help] Meta's segment anything - How can I make smooth border ?
Hi :) I am app/web developer and new to AI. Currently, I am making photo app which can segment all the things in image. I've used meta's segment anything. I've got all the masks but the boundary of masks are very bumpy. So I've tried rembg which uses u2net(salient object detection) and pymatting together. Do I have to use pymatting separately after getting segment from segment anything to improve boundary quality of my segmented output ?
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BackgroundRemover 0.2.1 - Remove Background from Video and Images using AI
Cool, thanks for sharing. It might be worth clearly attributing the models you're using, and maybe add a models/license file with the U2net license, since that license is different to the one you're using for your project, and since you're distributing the models.
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How to do Human Head Segmentation from images?
Background Removal - I'd use u2net which has a model that's specifically trained on people vs backgrounds. If that didn't work, maybe DIS which is the newer version or rembg. These are pretty easy to get running I found.
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Just a reminder that there is a new 'remove background' extension for a1111
u2net_human_seg (download, source): A pre-trained model for human segmentation.
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OMPR V0.6.10 update
Optimized β AI tweak Image background remover is now faster and enables trained model (onnx) swapping Revamp the python engine for background remover. Should be running faster than the previous build. Also added was the ability to replace the pre-trained ONNX model by the user themselves. https://github.com/xuebinqin/U-2-Net
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OMPR V0.6.8 update
-Added AI Background remover based on U2Net AI framework for Image projector. Check the Image projection "AI Tweaks" dropdown to toggle between u2net standard, u2netp β portrait, u2net-human_seg, u2net_cloth_seg, or silueta as the background remover AI model. As you can guess from the names, each of the models excels for different image subjects for background removal. For example, the portrait model is good for human portraits, cloth seg for clothing subjects and so on. Default to CUDA (Nvidia) processor, if you have an AMD card or would like to use CPU as the processor, untick the CUDA checkbox. Go here if you want to know more about the mechanics of U2Net -> https://github.com/xuebinqin/U-2-Net
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Computer Vision Free Lancer
Also checkout https://github.com/xuebinqin/U-2-Net. They have a new version in this repo: https://github.com/xuebinqin/DIS
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image segmentation using U-nets
There, the author has the same goal as you do, and has a train.py and instructions. You can reach out to the author and ask questions either in the issues section or perhaps email directly. Many times people are very helpful when you show interest in their work. The neural network it is based on (U2-net) is very easy to get running by the way, and has lots of use cases: https://github.com/xuebinqin/U-2-Net
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After much experimentation π€
really any segmentation model could work. "salient object detection" is well suited for "i have a single, obvious subject that I want to isolate from the background". This is the model I had in mind, but it wouldn't have to be this necessarily: https://github.com/xuebinqin/U-2-Net
What are some alternatives?
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
gmic - GREYC's Magic for Image Computing: A Full-Featured Open-Source Framework for Image Processing
image-background-remove-tool - βοΈ Automated high-quality background removal framework for an image using neural networks. βοΈ
ai-background-remove - Cut out objects and remove backgrounds from pictures with artificial intelligence
backgroundremover - Background Remover lets you Remove Background from images and video using AI with a simple command line interface that is free and open source.
resynthesizer - Suite of gimp plugins for texture synthesis
rembg-greenscreen - Rembg Video Virtual Green Screen Edition
stable-diffusion-webui-rembg - Removes backgrounds from pictures. Extension for webui.
trt_pose - Real-time pose estimation accelerated with NVIDIA TensorRT
Pixelitor - A desktop image editor
Anime2Sketch - A sketch extractor for anime/illustration.