[P] Awesome Image Segmentation Project Based on Deep Learning (5.6k star)

Submitted by Effective_Tax_2096 t3_y68dzn in MachineLearning

Hi, I'd like to introduce PaddleSeg, which provides the ability of designing, training and deploying segmentation models.

This might be some help to you. Hope you enjoy it.

Code and docs: https://github.com/PaddlePaddle/PaddleSeg

Features Set:

  • Support several tasks: Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, etc.
  • Provide 40+ state-of-art semantic segmentation models and 140+ high-quality pre-training models
  • Provide efficient interactive segmentation tool (EISeg) for annotating segmentation images
  • Release a variety of human matting and portrait segmentation models for practical application without training
  • Support 3D medical image segmentation
  • etc

https://i.redd.it/pi0pjee2ncu91.gif

https://i.redd.it/7cuiqre3ncu91.gif

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Comments

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cairon t1_isoeh1x wrote

this looks really well documented, thanks!

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thelastpizzaslice t1_isp3rj7 wrote

Got a colab where I can use this? I'd love to do some image matting to pre-prep masks for stable diffusion.

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thelastpizzaslice t1_ispl47u wrote

Replying to fraktall (#126,346)

For img2img, if I could generate of one those masks that matches up to the various objects in the image, that would help a lot. Otherwise, I need to draw them or make them myself every time. Would be great as a feature in automatic1111's UI to auto-generate maskable regions to use in stable diffusion.

Also, I'd be interested in removing backgrounds and then re-generating them inside of different contexts to feed into dreambooth, i.e. to remove an object that is a part of a subject from its context and put it in a different one. For example, if I wanted to make a prosthetic arm that sits on a table, or if I want to make fried rice but remove the plate from the background and give it additional possible backgrounds instead. This will probably break dreambooth instead of doing what I want, but if it works, it's going to be some awesome witchcraft that lets me turn one object into a very different one.

I could just as well run it on my computer locally, but I do work on that machine and don't like using 100% of my GPU processing in the background.

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not_mahi t1_isr0p3q wrote

Are there any open-label segmentation model included in this repo, like Detic or LSeg?

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Effective_Tax_2096 OP t1_israu1k wrote

Replying to thelastpizzaslice (#125,582)

The repo provides matting module consisting of SOTA models, open-source code for training and evaluation. Besides, there are well-trained out-of-the-box matting models for human, thus you can just use these human matting models in applications without training. If want to do image matting for other things or stuffs, you need to collect images, label images and train model. I will also convey your demand to the developers.

code: https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting

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CommonDopant t1_isrhozo wrote

Can I ask: are you in Cs6515 GA at Georgia Tech? Exam next week includes image segmentation (using min st cut)… so I’ve been googling a bunch on image segmentation

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viveksnh t1_it5lr0l wrote

Wow, this is really cool. Also, 5.6k starts is pretty massive. I remember not that long ago, Gatsby repo had 8k stars. So, nice freaking work!

If you are looking for a platform to house demos (including compute!) and friendly codebase with examples, DM me! :)

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Best-Neat-9439 t1_itl8uxb wrote

Replying to [deleted] (#134,719)

The positive/negative clicks feature seems interesting (I guess it's slower but more accurate for weird objects than things like one-click annotation). Do you know of other free, easy to install locally (so, no Hasty, for example) tools like this?

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