stable-diffusion
onnx
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stable-diffusion | onnx | |
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382 | 38 | |
65,087 | 16,758 | |
1.7% | 1.8% | |
0.0 | 9.5 | |
9 days ago | 2 days ago | |
Jupyter Notebook | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
stable-diffusion
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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.
- Automatic1111 - Multiple GPUs
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Falcon 40B LLM which beats Llama license changed to Apache 2.0
Agree. The Stable Diffusion Open RAIL M license: "You agree not to use the Model or Derivatives of the Model ... To defame, disparage or otherwise harass others"
Does "disparage" have a settled meaning in law?
https://github.com/CompVis/stable-diffusion/blob/main/LICENS...
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question?
If you downloaded from https://github.com/CompVis/stable-diffusion that's the problem. It's the real Stable Diffusion, but not what you want to use to generate images. The most popular Stable Diffusion interface is https://github.com/AUTOMATIC1111/stable-diffusion-webui. Make sure to read the install instructions.
- Synthetic data generation for model training · Issue #350 · CompVis/stable-diffusion
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Not quite sure what this means practically but figured it might of interest to the community.
sure thing!
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Can I use SD to generate group pictures (of say, me and my cousin, or me and multiple cousins)?
Read the official docs for Stable Diffusion.
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Tools For AI Animation and Filmmaking , Community Rules, ect. (**FAQ**)
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)
onnx
- Onyx, a new programming language powered by WebAssembly
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From Lab to Live: Implementing Open-Source AI Models for Real-Time Unsupervised Anomaly Detection in Images
Once your model has been trained and validated using Anomalib, the next step is to prepare it for real-time implementation. This is where ONNX (Open Neural Network Exchange) or OpenVINO (Open Visual Inference and Neural network Optimization) comes into play.
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Object detection with ONNX, Pipeless and a YOLO model
ONNX is an open format from the Linux Foundation to represent machine learning models. It is becoming extensively adopted by the Machine Learning community and is compatible with most of the machine learning frameworks like PyTorch, TensorFlow, etc. Converting a model between any of those formats and ONNX is really simple and can be done in most cases with a single command.
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38TB of data accidentally exposed by Microsoft AI researchers
ONNX[0], model-as-protosbufs, continuing to gain adoption will hopefully solve this issue.
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Operationalize TensorFlow Models With ML.NET
ONNX is a format for representing machine learning models in a portable way. Additionally, ONNX models can be easily optimized and thus become smaller and faster.
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Onnx Runtime: “Cross-Platform Accelerated Machine Learning”
I would say onnx.ai [0] provides more information about ONNX for those who aren’t working with ML/DL.
[0] https://onnx.ai
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Async behaviour in python web frameworks
This kind of indirection through standardisation is pretty common to make compatibility between different kinds of software components easier. Some other good examples are the LSP project from Microsoft and ONNX to represent machine learning models. The first provides a standard so that IDEs don't have to re-invent the weel for every programming language. The latter decouples training frameworks from inference frameworks. Going back to WSGI, you can find a pretty extensive rationale for the WSGI standard here if interested.
- Pickle safety in Python
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Unpaint: a compact, fully C++ implementation of Stable Diffusion with no dependency on python
Sounds interesting, ONNX runtime - what I use - can also be run with WebAssembly and on CPU, on all major GPUs, and it supports many programming languages, though C++ is its direct form.
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AMD Accelerates AI Adoption on Windows 11 With New Developer Tools for Ryzen AI
No, it's that AMD doesn't fucking need to. If anything, it the owners of ONNX that needs to convince developers that their technology is worth learning and using it to implement solutions, whether it's on laptops or phones or Raspberry Fucking Pi.
What are some alternatives?
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
stable-diffusion-webui - Stable Diffusion web UI
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
diffusers-uncensored - Uncensored fork of diffusers
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
dalle-mini - DALL·E Mini - Generate images from a text prompt
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models