DeepDanbooru
stable-diffusion-webui
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DeepDanbooru | stable-diffusion-webui | |
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8 | 2,808 | |
2,485 | 129,299 | |
- | - | |
0.0 | 9.9 | |
6 months ago | 6 days ago | |
Python | Python | |
MIT License | MIT |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
DeepDanbooru
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Discussion Thread
Okay, it turns out that someone has trained an image classifier on danbooru as a dataset.
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LAION publishes open source version of Google CoCa models ( SOTA on image captioning task )
First of all - DeepDanbooru is the exclusive project of KichangKim, who aimed to train models based on (variants of) the ResNet architecture to output Danbooru tags.
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Can i get some help installing deep danbooru?
> pip install -r requirements.txt Like what does this mean, where do i put the files i got from https://github.com/KichangKim/DeepDanbooru ? The whole process is confusing me
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i tried to install "Animator script" and "DeepDanbooru" into AUTOMATIC1111 did not work?
For: https://github.com/KichangKim/DeepDanbooru I see the "Put your deepbooru release project folder here.txt" file so I "git clone" it into this folder, moved it up and so on but the button did not show and in the console are no errors. Also I restarted the UI after each moving of the project.
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DeepDanbooru interrogator implemented in Automatic1111
if not is_installed("deepdanbooru") and deepdanbooru: run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
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[Hobby Scuffles] Week of August 29, 2022 (Poll)
i think you could make an argument that training an art-generator model falls afoul of the "market for the original work" prong of fair use in a pretty severe way. but something like DeepDanbooru where the output is not the image but a descriptor of it would be a much easier sell as fair use.
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“Smart” or “AI” assisted Media management system that detects and auto-tags files?
DeepDanbooru is suprisingly good for tagging photos and drawings.
stable-diffusion-webui
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Show HN: I made an app to use local AI as daily driver
* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.
- https://diffusionbee.com/
- https://github.com/comfyanonymous/ComfyUI
- https://github.com/AUTOMATIC1111/stable-diffusion-webui
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
I would love to be able to have a native stable diffusion experience, my rx 580 takes 30s to generate a single image. But it does work after following https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki...
I got this up and running on my windows machine in short order and I don't even know what stable diffusion is.
But again, it would be nice to have first class support to locally participate in the fun.
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Ask HN: What is the state of the art in AI photo enhancement?
In Auto1111, that just uses Image.blend. :)
https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob...
- How To Increase Performance Time on MacOS
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Can anyone suggest an AI model that can help me enhance a poorly drawn logo?
I used SDXL in automatic1111 webui for both images. Now that I think about it, the procedure I described was how I made this one, but the one that looks like an illustration was done in two steps. I used the canny ControlNet as I said for the outer part of the logo to preserve the shape of the fonts, but I had to turn it off for the boot to give SDXL leeway to add detail and make it look more like a boot.
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Seeking out an experienced and empathetic coding buddy.
That said, please do learn coding and don't get discouraged when somebody says to learn PyTorch or recommends using a Jupiter notebook with no further information on how to translate the skill into images. I would highly recommend some short term goals. Get your feet wet by taking apart the UIs. The comfy API documentation is here and the A1111 API documentation is here. There is a difference in completeness, welcome to programming. Writing nodes or plugins is also a good way to jump into this world. Custom wildcard logic might be very attractive to you if you aren't the type that want to deal with a nested file structure to simulate logic.
- can't get it working with an AMD gpu
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SD extension that allows for setting override
Possibly Unprompted? https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8094
- Need to write an application to use Stable Diffusion on my desktop PC - which resource should I learn to use?
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4090 Speed Decrease on each Generation/Iteration
version: v1.6.1 • python: 3.10.13 • torch: 2.0.1+cu118 • xformers: 0.0.20 • gradio: 3.41.2 • checkpoint: 6e8d4871f8
What are some alternatives?
szurubooru - Image board engine, Danbooru-style.
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
stanford-tensorflow-tutorials - This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
SHARK - SHARK - High Performance Machine Learning Distribution
SW-CV-ModelZoo - Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
Keras - Deep Learning for humans
safetensors - Simple, safe way to store and distribute tensors