dream-textures
Pytorch
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dream-textures | Pytorch | |
---|---|---|
72 | 333 | |
7,534 | 76,925 | |
- | 2.6% | |
5.8 | 10.0 | |
14 days ago | 3 days ago | |
Python | Python | |
GNU General Public License v3.0 only | BSD 1-Clause License |
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dream-textures
- Tell HN: The next generation of videogames will be great with midjourney
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After Diffusion, an After Effects Extension Integrating the SD web UI seamlessly.
I'm a long time advanced AE user and would gladly give feedback according to how I envision a nice workflow to be if you want. I recently got into dream textures for blender, which I think is a great reference for the direction things could be heading. It's still not viable for consistent video, but I love how they expose multiple control nets and their weights to be animatable for example. I also suggested them exposed (animatable) prompt weights, which the author now also plans for future release. I see you have such things planned as well for this plugin so big thumbs up!
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Resources for artists interesting in using StableDiffusion as a tool?
Dream Textures (SD for Blender) - https://github.com/carson-katri/dream-textures
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ControlNet fully integrated with Blender using nodes!
ControlNet is fully supported in the latest version of the Dream Textures add-on for Blender. You can get it from GitHub: https://github.com/carson-katri/dream-textures/releases/tag/0.2.0
It doesn’t use A1111 or venv, it’s all self contained in the addon, and really easy to setup. Here are the setup instructions: https://github.com/carson-katri/dream-textures/wiki/Setup
More likely there will be an A1111 backend in the future that would just call into their api: https://github.com/carson-katri/dream-textures/issues/604
We support inpainting and outpainting: https://github.com/carson-katri/dream-textures/wiki/Inpaint-and-Outpaint
Yes, and it can also automatically bake the texture onto the original UV map instead of the projected UVs. The guide is here: https://github.com/carson-katri/dream-textures/wiki/Texture-Projection
- Blender 3.5
Pytorch
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Element-wise vs Matrix vs Dot multiplication
In PyTorch with * or mul(). ` or mul()` can multiply 0D or more D tensors by element-wise multiplication:
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Bash Debugging
When I was at Facebook, I wrote a Python script to extract shell scripts from GitHub Actions workflows, so we could run them all through ShellCheck: https://github.com/pytorch/pytorch/blob/69e0bda9996865e319db...
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
PyTorch: An open-source deep learning framework that facilitates dynamic computational graphs, making it flexible and efficient for research and production.
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How To Implement Data Streaming In PyTorch From A Remote Database
In this blog post, we will go through a full example and setup a data stream to PyTorch from a playground dataset on a remote database.
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Introducing Flama for Robust Machine Learning APIs
PyTorch
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Beyond Backpropagation - Higher Order, Forward and Reverse-mode Automatic Differentiation for Tensorken
This post describes how I added automatic differentiation to Tensorken. Tensorken is my attempt to build a fully featured yet easy-to-understand and hackable implementation of a deep learning library in Rust. It takes inspiration from the likes of PyTorch, Tinygrad, and JAX.
What are some alternatives?
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
flax - Flax is a neural network library for JAX that is designed for flexibility.
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
tensorflow - An Open Source Machine Learning Framework for Everyone
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
stable-diffusion-webui - Stable Diffusion web UI
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
tesseract-ocr - Tesseract Open Source OCR Engine (main repository)