ROCm_Documentation
dream-textures
| ROCm_Documentation | dream-textures | |
|---|---|---|
| 2 | 72 | |
| 108 | 7,611 | |
| - | - | |
| 2.8 | 5.8 | |
| 11 months ago | 15 days ago | |
| CSS | Python | |
| - | GNU General Public License v3.0 only |
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ROCm_Documentation
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AI Seamless Texture Generator Built-In to Blender
https://rocmdocs.amd.com/en/latest/Deep_learning/Deep-learni...
RadeonOpenCompute/ROCm_Documentation: https://github.com/RadeonOpenCompute/ROCm_Documentation
ROCm-Developer-Tools/HIPIFYhttps://github.com/ROCm-Developer-Tools/HIPIFY :
> hipify-clang is a clang-based tool for translating CUDA sources into HIP sources. It translates CUDA source into an abstract syntax tree, which is traversed by transformation matchers. After applying all the matchers, the output HIP source is produced.
ROCmSoftwarePlatform/gpufort: https://github.com/ROCmSoftwarePlatform/gpufort :
> GPUFORT: S2S translation tool for CUDA Fortran and Fortran+X in the spirit of hipify
ROCm-Developer-Tools/HIP https://github.com/ROCm-Developer-Tools/HIP:
> HIP is a C++ Runtime API and Kernel Language that allows developers to create portable applications for AMD and NVIDIA GPUs from single source code. [...] Key features include:
> - HIP is very thin and has little or no performance impact over coding directly in CUDA mode.
> - HIP allows coding in a single-source C++ programming language including features such as templates, C++11 lambdas, classes, namespaces, and more.
> - HIP allows developers to use the "best" development environment and tools on each target platform.
> - The [HIPIFY] tools automatically convert source from CUDA to HIP.
> - * Developers can specialize for the platform (CUDA or AMD) to tune for performance or handle tricky cases.*
- Why is ROCm still such a dog's breakfast?
dream-textures
- Donut done with Artificial Intelligence and Blender
- 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
- Using AI for 3d Game art
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ControlNet fully integrated with Blender using nodes!
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
- Using DALL-E 2 to create brick and water textures in Unity.
- 3D animation attempt using Sketchup screenshots and ControlNet
- Blender 3.5
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Master AI Texture Projection for Blender 3
Dream AI latest release: https://github.com/carson-katri/dream-textures/releases
What are some alternatives?
clang-ocl - OpenCL compilation with clang compiler.
stable-diffusion-webui - Stable Diffusion web UI
gpufort - GPUFORT: S2S translation tool for CUDA Fortran and Fortran+X in the spirit of hipify
stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
stable-diffusion-nvidia-docker - GPU-ready Dockerfile to run Stability.AI stable-diffusion model v2 with a simple web interface. Includes multi-GPUs support.
DeepBump - Normal & height maps generation from single pictures
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]
stable-diffusion
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
Blender-GPT - An all-in-one Blender assistant powered by GPT3/4 + Whisper integration
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image