stable-diffusion-tensorflow
diffusionbee-stable-diffusion-ui
stable-diffusion-tensorflow | diffusionbee-stable-diffusion-ui | |
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18 | 141 | |
1,569 | 11,941 | |
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0.0 | 4.4 | |
9 months ago | 2 months ago | |
Python | JavaScript | |
GNU General Public License v3.0 or later | GNU Affero General Public License v3.0 |
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stable-diffusion-tensorflow
- Keras model SD or similar I can train from scratch?
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Anyone attempted to convert stablediffusion tensorflow to tf lite?
was curious if someone attempted the conversion? I tried here https://github.com/divamgupta/stable-diffusion-tensorflow/issues/58 but having some input shapes error. First time trying the conversion here, would love to run it on a edge tpu.
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Stable Diffusion Tensorflow to TF Lite
Checking here is someone tried to convert the tensorflow diffusion model into a tf lite?https://github.com/divamgupta/stable-diffusion-tensorflow/issues/58
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SD on intel arc?
Actually I was just on GitHub trying to submit issues related to me testing Intel's PyTorch and Tensorflow extensions when I saw this; it seems that someone has already ported SD over to the tensorflow framework and so you can probably start using intel's extension for tensorflow with it immediately; and according to this article you can use Intel's extension within WSL under windows as well. But unfortunately given how the guy whose issue I linked to has been facing pretty serious performance issues of inferencing taking many minutes longer than it should when using an A770 to do SD-related inferencing, you might be better off waiting for intel's extension for tensorflow versions 1.2 and greater or something like that, so that when it's your turn to use it, Intel has already ironed out most of the major bugs within the software :)
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Stable Diffusion with AMDGPU on WSL
tensorflow-stable-diffusion
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Image2Image with AMD hardware?
# clone git clone https://github.com/divamgupta/stable-diffusion-tensorflow.git cd stable-diffusion-tensorflow # create venv python -m venv --prompt sdtf-windows-directml venv venv\Scripts\activate # verify venv is installed and activated pip --version # install deps pip install -r requirements.txt pip install tensorflow-directml-plugin # you should see DML debug output and at least one GPU python -c 'import tensorflow as tf; print(tf.config.list_physical_devices())' # run (show help) python text2image.py --help python text2image.py --prompt "a fluffy kitten"
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I have no PC. Just DLed this for iOS
(Answers based on stable-diffusion open model) If you have a M1 processor: https://github.com/divamgupta/diffusionbee-stable-diffusion-ui (I've tested it) Or this claimed faster with TensorFlow: https://github.com/divamgupta/stable-diffusion-tensorflow
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Keras Inpainting Colab
Added inpainting support to the original keras implementation: https://github.com/divamgupta/stable-diffusion-tensorflow Colab: https://colab.research.google.com/drive/1Bf-bNmAdtQhPcYNyC-guu0uTu9MYYfLu Github page: https://github.com/ShaunXZ/stable-diffusion-tensorflow
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[N] Stable Diffusion reaches new record (with explanation + colab link)
I wonder if you mean 13 seconds per image because this implementation reports ~10s per image with mixed precision.
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High-performance image generation using Stable Diffusion in KerasCV
On intel MacBookPro, CPU-only, the original one[1] using pytorch only utilized one core. A tensorflow implementation[2] with oneDNN support which utilized most of the cores ran at ~11sec/iteration. Another OpenVINO based implementation[3] ran at ~6.0sec/iteration.
[1] https://github.com/CompVis/stable-diffusion/
[2] https://github.com/divamgupta/stable-diffusion-tensorflow/
[3] https://github.com/bes-dev/stable_diffusion.openvino/
diffusionbee-stable-diffusion-ui
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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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Easy Stable Diffusion XL in your device, offline
Interesting, will check it out to see how it compares with https://diffusionbee.com which I am using for last few months for fun.
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Google is embedding inaudible watermarks right into its AI generated music
It depends on what you are planning to do. Stable diffusion works great locally on both the dell+linux and the mac laptop I tried it on. This one was easy to use while exploring models from huggingface: https://diffusionbee.com/
- DiffusionBee - Stable Diffusion App for AI Art
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How do I install stable diffusion on my Mac Air? My midjourney subscription expired, and I don’t wanna pay another 60 a month. So I wanna try a new service.
diffusion bee is the easiest app to use.
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Are there any good and safe apps for ai art?
If you have a Mac, I highly recommend DiffusionBee. It’s an app you can install on your computer and use as much as you want (even offline) for free. The website has older downloads but if you go here you can get the latest beta with more features: https://github.com/divamgupta/diffusionbee-stable-diffusion-ui/releases
- Diffusion Bee for Mac new version 2 beta out
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Stable Diffusion Intel Mac?
Try these first: 1. https://drawthings.ai/ 2. https://diffusionbee.com/
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Useful Links
Diffusion Bee
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How do you guys go about making art for your releases?
If you have a Mac, you can try this out too offline for free - https://diffusionbee.com (Go into the settings to make it the largest image size and you can also upscale it afterward - helpful for submitting larger artwork dimensions to distributors).
What are some alternatives?
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]
a1111-sd-webui-tagcomplete - Booru style tag autocompletion for AUTOMATIC1111's Stable Diffusion web UI
AITemplate - AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.
stable-diffusion-webui-docker - Easy Docker setup for Stable Diffusion with user-friendly UI
keras-cv - Industry-strength Computer Vision workflows with Keras
MochiDiffusion - Run Stable Diffusion on Mac natively
intel-extension-for-tensorflow - Intel® Extension for TensorFlow*
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.
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models