image_pipeline
DALI
image_pipeline | DALI | |
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1 | 5 | |
752 | 4,917 | |
0.4% | 1.0% | |
8.6 | 9.6 | |
3 days ago | 2 days ago | |
C++ | C++ | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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image_pipeline
DALI
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[D] Will data augmentations work faster on TPUs?
Another option is DALI https://github.com/NVIDIA/DALI For my project while training EfficientNet2, it was a game changer. But it a way harder to implement in code than TorchVision or Kornia.
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DirectStorage - Loading data to GPU *directly* from the SSD drive, almost without using CPU
Check out https://github.com/nvidia/DALI
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mmap_ninja: Speedup your training dramatically by using memory-mapped files for your dataset
Small question if you are using GPU: How to this compare to GPUDirect Storage from Nvidia? can you have even more speedup by using both? I never toy with it, but the DALI project from Nvidia seem to tackle the same data loading problem.
- [D] Efficiently loading videos in PyTorch without extracting frames
What are some alternatives?
eos - A lightweight 3D Morphable Face Model library in modern C++
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
pinocchio - A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
Blurry - Blurry is an easy blur library for Android
OpenCV - Open Source Computer Vision Library
vision - Datasets, Transforms and Models specific to Computer Vision
OpenImageIO - Reading, writing, and processing images in a wide variety of file formats, using a format-agnostic API, aimed at VFX applications.
executorch - On-device AI across mobile, embedded and edge for PyTorch
GDCM - Grassroots DICOM read-only mirror. Only for Pull Request. Please report bug at http://sf.net/p/gdcm
DREAMPlace - Deep learning toolkit-enabled VLSI placement
MegEngine - MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架
ocaml-torch - OCaml bindings for PyTorch