Granite
MNN
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Granite
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[Beginner] Blending behaves strangely
I'm currently writing my first Vulkan rendering abstraction. I'm using Granite as a reference, and following along vulkan tutorial's steps. I deviated from their design by using the Vulkan Memory Allocator and the dynamic rendering extension. I implemented Vertex buffers, index buffers, UBOs, push constants and samplers. The only thing I still need to do is depth buffering.
- Handling materials in a render graph system?
MNN
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[D][R] Deploying deep models on memory constrained devices
However, I am looking on this subject through the problem of training/finetuning deep models on the edge devices, being increasingly available thing to do. Looking at tflite, alibaba's MNN, mit-han-lab's tinyengine etc..
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What’s New in TensorFlow 2.10?
There are a ton of mobile deployment options that support PyTorch+TF models. It's hard to argue TFLite is the best.
https://github.com/alibaba/MNN
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Newbie having error code of cannot build selected target abi x86 no suitable splits configured
I found a solution on GitHub check your app's build.gradle, defaultConfig section - you need to add x86 to your ndk abiFilters ndk.abiFilters 'armeabi-v7a','arm64-v8a', 'x86' GitHub Hope it will help. You have to find that file and edit it as given here
What are some alternatives?
3d-game-shaders-for-beginners - 🎮 A step-by-step guide to implementing SSAO, depth of field, lighting, normal mapping, and more for your 3D game.
tensorflow - An Open Source Machine Learning Framework for Everyone
selenite-db - Persistence Layer for your Crystal Application
TNN - TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
stal-crystal - Set algebra solver for Redis
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
kemalyst-model
ML-examples - Arm Machine Learning tutorials and examples
dxvk - Vulkan-based implementation of D3D9, D3D10 and D3D11 for Linux / Wine
oneflow - OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
Waifu2x-Extension-GUI - Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, RTX Video Super Resolution VSR, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.
serving - A flexible, high-performance serving system for machine learning models