stable-diffusion-webui-depthmap-script
stable-diffusion
stable-diffusion-webui-depthmap-script | stable-diffusion | |
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64 | 383 | |
1,594 | 65,739 | |
- | 1.3% | |
8.3 | 0.0 | |
2 months ago | about 4 hours ago | |
Python | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
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stable-diffusion-webui-depthmap-script
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PATCHFUSION is really impressive. High resolution depth maps in 16bit. I've been waiting for this. https://github.com/zhyever/PatchFusion
The guide on the github page for the extension is OK: https://github.com/thygate/stable-diffusion-webui-depthmap-script
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Extension not showing. Depthmap help 馃檹
New to SD. I'm trying to get an extension to work (https://github.com/thygate/stable-diffusion-webui-depthmap-script) but opposite to the tutorials the "depth" tab doesn't show after installation. Anyone who can help locate the problem? Thanks!
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Is anyone working on stereoscopic 3D SD? Is it even possible?
You can use this extension to generate stereoscopic images . . . I don't (yet) dabble in video, so I don't know what it'll do there. I've done a ton of stereo pics with it. My fascination sort of comes and goes. You can do cross-eyed or parllel view as well as red/cyan anaglyphs.
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GUIDE: Ways to generate consistent environments for comics, novels, etc
Option 8. Use img2img of existing 360 HDRIs, extract their depth maps with the depth extension. Use that as a displacement map on a sphere in Blender, similarly to this, with the refurbished HDRI as an image texture, then take screenshots from a position close to the center of the sphere. You are limited to staying close to the center in order to avoid distortion, but now you have 360 degrees of consistent freedom for a particular scene. If you have 2 or more HDRIs of the same place, even better. You could also combine this with the 3D environments of the other options to use 360 renders as bases for the img2img.
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Another Ai image to 3d
you have another automatic 1111 extension that allow you to create there also the 3d file, but this consume a lot of vram https://github.com/thygate/stable-diffusion-webui-depthmap-script
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Get a 16-Bit Controlnet Depth
If you're using A1111 webui there is the depthmap2mask extension which you can install from the extensions tab. It will add a depth tab which will allow you to create 16-bit depth maps among many other things.
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180 VR - Blue Techno World - (Stable Diffusion + Deforum) stereo video
actually it is very easy to do. What you need is install extension for Stable Diffusion webUI (https://stable-diffusion-art.com/install-windows/) . This extension will generate stereo for you automatically. Name is Depth. (https://github.com/thygate/stable-diffusion-webui-depthmap-script)
- Is it possible for me to approximate a depth map from a generated image and make a 3D model?
- Thanks for loving our Star Wars video! We created a new one for Lord of the Rings. Enjoy this mid-journey to Middle-Earth.
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Found this site through twitter that slightly animates images. Throwing Stable Diffusion generations into it is pretty awesome. Site in comments.
You can do this inside of a1111 as well with this extension https://github.com/thygate/stable-diffusion-webui-depthmap-script
stable-diffusion
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Top 7 Text-to-Image Generative AI Models
Stable Diffusion: It is based on a kind of diffusion model called a latent diffusion model, which is trained to remove noise from images in an iterative process. It is one of the first text-to-image models that can run on consumer hardware and has its code and model weights publicly available.
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Go is bigger than crab!
Which is a 1-click install of Stable Diffusion with an alternative web interface. You can choose a different approach but this one is pretty simple and I am new to this stuff.
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Why & How to check Invisible Watermark
an invisible watermarking of the outputs, to help viewers identify the images as machine-generated.
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How to create an Image generating AI?
It sounds like you just want to set up Stable Diffusion to run locally. I don't think your computer's specs will be able to do it. You need a graphics card with a decent amount of VRAM. Stable diffusion is in Python as is almost every AI open source project I've seen. If you can get your hands on a system with an Nvidia RTX card with as much VRAM as possible, you're in business. I have an RTX 3060 with 12 gigs of VRAM and I can run stable diffusion and a whole variety of open source LLMs as well as other projects like face swap, Roop, tortoise TTS, sadtalker, etc...
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Two video cards...one dedicated to Stable Diffusion...the other for everything else on my PC?
Use specific GPU on multi GPU systems 路 Issue #87 路 CompVis/stable-diffusion 路 GitHub
- Automatic1111 - Multiple GPUs
- Ist Google inzwischen einfach unbrauchbar?
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Why are people so against compensation for artists?
I dealt with this in one of my posts. At least SD 1.1 till 1.5 are all trained on a batch size of 2048. The version pretty much everyone uses (1.5) is first pretrained at a resolution of 256x256 for 237K steps on laion2B-en, at the end of those training steps it will have seen roughly 500M images in laion2B-en. After that it is pre-trained for 194K steps on laion-high-resolution at a resolution of 512x512, which is a subset of 170M images from laion5B. Finally it is trained for 1.110K steps on LAION aesthetic v2 5+. This is easily verified by taking a glance at the model card of SD 1.5. Though that one doesn't specify for part of the training exactly which aesthetic set was used for part of the training, for that you have to look at the CompVis github repo. Thus at the end of it all both the most recent images and the majority of images will have come from LAION aesthetic v2 5+ (seeing every image approx 4 times). Realistically a lot of the weights obtained from pretraining on 2B will have been lost, and only provided a good starting point for the weights.
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Is SDXL really open-source?
stable diffusion 路 CompVis/stable-diffusion@2ff270f 路 GitHub
- I want to ask the AI to draw me as a Pokemon anime character then draw six of Pokemon of my choice next to me. What are my best free, 15$ or under and 30$ or under choices?
What are some alternatives?
MiDaS - Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
a1111-sd-zoe-depth - a1111 sd WebUI extention version of ZoeDepth
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
multi-subject-render - Generate multiple complex subjects all at once!
diffusers-uncensored - Uncensored fork of diffusers
Thin-Plate-Spline-Motion-Model - [CVPR 2022] Thin-Plate Spline Motion Model for Image Animation.
diffusers - 馃 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
depthmap2mask - Create masks out of depthmaps in img2img
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
point-e - Point cloud diffusion for 3D model synthesis
onnx - Open standard for machine learning interoperability