first-order-model VS stablediffusion

First Order Motion Model/Thin Plate Spline (Animate Single images realistically using a driving video) https://github.com/AliaksandrSiarohin/first-order-model (FOMM - Animate still images using driving videos) https://github.com/yoyo-nb/Thin-Plate-Spline-Motion-Model (Thin Plate Spline - Likely just a repost of FOMM but with better documentation and tutorials on YouTube) https://drive.google.com/drive/folders/1PyQJmkdCsAkOYwUyaj_l-l0as-iLDgeH (FOMM/Thin Plate Checkpoints) https://disk.yandex.com/d/lEw8uRm140L_eQ (FOMM/Thin Plate Checkpoints mirror) -------3D ANIMATION--------

GitHub - AliaksandrSiarohin/first-order-model: This repository contains the source code for the paper First Order Motion Model for Image Animation

Not sure about whatever bot op is specifically using, but you can use this software to achieve the same result https://github.com/AliaksandrSiarohin/first-order-model

I think the novel and interesting tech is still happening, its just that without the colorful ads for it on TV, and without the software being packaged up and sold with pretty box art that you can physically hold, it doesn't feel as much like a capital-E Experience. It's probably the Internet's fault that we don't do things like that anymore, but the upside is that we now have access to so many ideas and applications from all over, even ones that aren't commercially viable.

Some that look exciting to me are: an AI that lets you animate still photos realistically [1], a simple website that guides you to discover new parks, eateries, and other places near you [2], an AI that colorizes old black-and-white photos/video [3], a Street View style map of the game world from "The Legend of Zelda: Breath of the Wild", with some 1st person 360 degree photos [4], and a tiny game engine that lets you distribute your whole game physically via printed QR codes [5].

If marketing and graphic design people ever felt like getting together to do some 'side projects', I vote that they should make print ads for apps/websites that they like :)

[1] https://github.com/AliaksandrSiarohin/first-order-model

[2] https://randomlocation.xyz (https://randomlocation.xyz/help.txt for customization)

[3] https://github.com/jantic/DeOldify

[4] https://nassimsoftware.github.io/zeldabotwstreetview/

[5] https://github.com/kesiev/rewtro

Ai Used https://github.com/AliaksandrSiarohin/first-order-model

First Order Model

First Order Motion Model (Easy): You can give it an input image and a source video, and the movements from the video will be copied to the image. It has some janky-ness and I would recommend using an ai upscaller afterwards because the resolution isn't that high https://github.com/AliaksandrSiarohin/first-order-model

With this tutorial's help, you can generate images with AI on your own computer with Stable Diffusion.

If your PC has a GPU(Nvidia RTX 30series+ recommended) of VRAM more than 4GB then try training your own Stable Diffusion model.

Command: "git" clone "https://github.com/Stability-AI/stablediffusion.git" "C:\Users\Naveed\Documents\A1111 Web UI Autoinstaller\stable-diffusion-webui\repositories\stable-diffusion-stability-ai"

Automatic11112 and sygil-webui aren't "distributions" of Stable Diffusion. This is a repository with some distributions of Stable Diffusion.

New stable diffusion finetune (Stable unCLIP 2.1, Hugging Face) at 768x768 resolution, based on SD2.1-768. This model allows for image variations and mixing operations as described in Hierarchical Text-Conditional Image Generation with CLIP Latents, and, thanks to its modularity, can be combined with other models such as KARLO. Comes in two variants: Stable unCLIP-L and Stable unCLIP-H, which are conditioned on CLIP ViT-L and ViT-H image embeddings, respectively. Instructions are available here.

This model will soon be open-sourced in StabilityAI’s GitHub.

Another question, if that's ok? Stable Diffusion 2.0 - https://github.com/Stability-AI/stablediffusion - if I wanted to use that, do I follow along their instructions and it will work on the M1 still, or you advise against it?

Stable Diffusion (2D Image Generation and Animation) https://github.com/CompVis/stable-diffusion (Stable Diffusion V1) https://huggingface.co/CompVis/stable-diffusion (Stable Diffusion Checkpoints 1.1-1.4) https://huggingface.co/runwayml/stable-diffusion-v1-5 (Stable Diffusion Checkpoint 1.5) https://github.com/Stability-AI/stablediffusion (Stable Difusion V2) https://huggingface.co/stabilityai/stable-diffusion-2-1/tree/main (Stable Diffusion Checkpoint 2.1) Stable Diffusion Automatic 1111 Webui and Extensions https://github.com/AUTOMATIC1111/stable-diffusion-webui (WebUI - Easier to use) PLEASE NOTE, MANY EXTENSIONS CAN BE INSTALLED FROM THE WEBUI BY CLICK "AVAILABLE" OR "INSTALL FROM URL" BUT YOU MAY STILL NEED TO DOWNLOAD THE MODEL CHECKPOINTS! https://github.com/Mikubill/sd-webui-controlnet (Control Net Extension - Use various models to control your image generation, useful for animation and temporal consistency) https://huggingface.co/lllyasviel/ControlNet/tree/main/models (Control Net Checkpoints -Canny, Normal, OpenPose, Depth, ect.) https://github.com/thygate/stable-diffusion-webui-depthmap-script (Depth Map Extension - Generate high-resolution depthmaps and animated videos or export to 3d modeling programs) https://github.com/graemeniedermayer/stable-diffusion-webui-normalmap-script (Normal Map Extension - Generate high-resolution normal maps for use in 3d programs) https://github.com/d8ahazard/sd_dreambooth_extension (Dream Booth Extension - Train your own objects, people, or styles into Stable Diffusion) https://github.com/deforum-art/sd-webui-deforum (Deforum - Generate Weird 2D animations) https://github.com/deforum-art/sd-webui-text2video (Deforum Text2Video - Generate videos from texts prompts using ModelScope or VideoCrafter)

Stable Diffusion's code : https://github.com/Stability-AI/stablediffusion

But if you want to run a 2.x-based model, you'll need to download the corresponding YAML file (either the standard one – v2-inference-v.yaml – from Github or the one that is distributed with the model, if it requires a special one), rename it to have the same name as the model, and place it in the models folder alongside the model.