backgroundremover
U-2-Net
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backgroundremover | U-2-Net | |
---|---|---|
86 | 30 | |
6,109 | 8,008 | |
- | - | |
6.9 | 3.1 | |
25 days ago | 3 months ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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backgroundremover
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Ask HN: What side projects landed you a job?
Not a job I took. But when I launched https://github.com/nadermx/backgroundremover I got offered a high level position in a a photo company via my email which at the time was on my GitHub profile.
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Image Upscaler AI
UI looks identical to https://backgroundremoverai.com/ ?
- Ask HN: Would you pay for a SaaS even if its open source and can be selfhosted?
- Show HN: Image background removal without annoying subscriptions
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Open source Background Remover: Remove Background from images and video using AI
I think this is what you wanted? https://github.com/nadermx/backgroundremover/tree/main/dist
Linked somewhere in the middle of the README file: https://backgroundremoverai.com/?lang=en
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BackgroundRemover 0.2.1 - Remove Background from Video and Images using AI
I appreciate that as I was trying very hard to make sure everything was up to par in the licensing department, given I am not a lawyer. Either way, I went ahead and put a link at the bottom of the read me next to the MIT license, and did upload a license to the models.
This is a website.
U-2-Net
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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 – 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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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 🤖
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
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[D] Extensions to U-nets
There's the U2 -net code paper. The paper and all the applications on the github are quite impressive. I've trained it on two different semantic segmentation tasks and found it performed well.
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Image to hand drawn
Sources: U2Net, ArtLine, Pix2PixHD, APDrawingGAN
What are some alternatives?
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
image-background-remove-tool - ✂️ Automated high-quality background removal framework for an image using neural networks. ✂️
segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
rembg-greenscreen - Rembg Video Virtual Green Screen Edition
trt_pose - Real-time pose estimation accelerated with NVIDIA TensorRT
rembg - Rembg is a tool to remove images background
Anime2Sketch - A sketch extractor for anime/illustration.
Linux-Fake-Background-Webcam - Faking your webcam background under GNU/Linux, now supports background blurring, animated background, colour map effect, hologram effect and on-demand processing.
obs-backgroundremoval - An OBS plugin for removing background in portrait images (video), making it easy to replace the background when recording or streaming.
Jitsi Meet - Jitsi Meet - Secure, Simple and Scalable Video Conferences that you use as a standalone app or embed in your web application.
deepbacksub - Virtual Video Device for Background Replacement with Deep Semantic Segmentation