ncnn
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ncnn | swift-diffusion | |
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12 | 6 | |
19,176 | 410 | |
1.8% | - | |
9.4 | 8.4 | |
5 days ago | 22 days ago | |
C++ | Swift | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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ncnn
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
ncnn uses Vulkan for GPU acceleration, I've seen it used in a few projects to get AMD hardware support.
https://github.com/Tencent/ncnn
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[D] Best way to package Pytorch models as a standalone application
They're using NCNN to package the model. Have a look. https://github.com/Tencent/NCNN
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Realtime object detection android app
Hi. Here is my prefered android app for realtime objet detection: https://github.com/nihui/ncnn-android-nanodet ; https://github.com/Tencent/ncnn contains a lot of android demo app for a lot of models.
- ncnn: High-performance neural network inference framework optimized for mobile
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Esp32 tensorflow lite
ncnn home page: https://github.com/Tencent/ncnn
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MMDeploy: Deploy All the Algorithms of OpenMMLab
ncnn
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Draw Things, Stable Diffusion in your pocket, 100% offline and free
Yes, Android devices tend to have bigger RAMs, making running 1024x1024 possible (this is not possible at all on iPhones, which could peak around 5GiB memory with my current implementation, some serious engineering required to bring that down on iPhone devices). The problem is I am not sure about speed. I would likely switch to NCNN (https://github.com/Tencent/ncnn) as the backend which have a decent Vulkan computing kernel support. It is definitely a possibility and there is a path to do that.
- What’s New in TensorFlow 2.10?
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[Technical Article] OCR Upgrade
As the leading open-source inference framework in China and in the world, what we like are its almost zero cost cross-platform capability, high inference speed, and minimal deployment volume. (Project address: https://github.com/Tencent/ncnn)
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Is there a functioning neural netowork or backbone written in pure C language only?
If you’re not planning on training the neural net on an embedded device and just do inference, this might interest you: https://github.com/Tencent/ncnn
swift-diffusion
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Show HN: Run Stable Diffusion Directly on iPhone
I am going to put model related code we use in a public repo soon (it is very similar to https://github.com/liuliu/swift-diffusion but in NHWC format). ANE will be around 25s if it runs. DT's default only uses GPUs and 35s is on GPU (yes, like you said, upscaling would take extra 10s).
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Some notes on porting SD2 over to iPhone (or other platforms)
The text encoder uses a new vocabulary set, make sure you copied them from open_clip repo: https://github.com/mlfoundations/open_clip (I have these also available at: https://github.com/liuliu/swift-diffusion/tree/liu/unet/examples/open_clip
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Draw Things, Stable Diffusion in your pocket, 100% offline and free
Should be able too, if there is a need. I am more interested to support training hypernetwork from the app directly. The conversion script itself is open-source (https://github.com/liuliu/swift-diffusion/blob/main/examples/unet/main.swift), but not polished, and because Apple doesn't allow you to run Python on device, so I cannot make it as easy as typing a URL and get done. Need to figure out what the UX looks like without me providing a networked services ...
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Show HN: Draw Things, Stable Diffusion in your pocket, 100% offline
Hi, this is the first app in a while (probably 10 years) that I submitted to AppStore. I've done this app in 3 weeks, so there are a lot to be polished. The technology that enables this I discussed in depth in an accompanied blog post: https://liuliu.me/eyes/stretch-iphone-to-its-limit-a-2gib-mo...
Some parts of it (or major parts) is also available at https://github.com/liuliu/swift-diffusion. I plan to port more stuff back to swift-diffusion and make a CLI tool out of it (it is a bit more work than the app because I need to consider CUDA compatibility there).
AMA!
What are some alternatives?
XNNPACK - High-efficiency floating-point neural network inference operators for mobile, server, and Web
diffusionbee-stable-diffusion-ui - Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
rife-ncnn-vulkan - RIFE, Real-Time Intermediate Flow Estimation for Video Frame Interpolation implemented with ncnn library
stablediffusion - High-Resolution Image Synthesis with Latent Diffusion Models
deepdetect - Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
diffusionbee-stable-diffusion-ui - Diffusion Bee
netron - Visualizer for neural network, deep learning and machine learning models
fickling - A Python pickling decompiler and static analyzer
darknet - Convolutional Neural Networks
open_clip - An open source implementation of CLIP.
RPi_64-bit_Zero-2-image - Raspberry Pi Zero 2 W 64-bit OS image with OpenCV, TensorFlow Lite and ncnn Framework.
torch-mlir - The Torch-MLIR project aims to provide first class support from the PyTorch ecosystem to the MLIR ecosystem.