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@Ayke
Ayke / DetectrononTX2.md
Created February 14, 2020 23:57
Configure Detectron 2 on nvidia TX2

Install Detectron 2

As it says here, https://github.com/facebookresearch/detectron2/blob/master/INSTALL.md we need to install a few modules before installing detectron.

The only part can be difficult is to install pytorch on TX2 since TX2 is aarch64 architecture, the installation instructions on pytorch website do not work. We need to install via this page: https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/

To upgrade pyyaml, just pip3 install pyyaml --ignore-installed

Also you might want to keep using python3 and pip3 to avoid using python2

@winnerineast
winnerineast / install_caffe.sh
Created October 3, 2017 17:52 — forked from doctorpangloss/install_caffe.sh
Installing Caffe on Mac 10.11.5 and later in the 10.11 series, and 10.12.1 and later in the 10.12 series
#!/bin/sh
# Install brew
/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
# Apple hides old versions of stuff at https://developer.apple.com/download/more/
# Install the latest XCode (8.0).
# We used to install the XCode Command Line Tools 7.3 here, but that would just upset the most recent versions of brew.
# So we're going to install all our brew dependencies first, and then downgrade the tools. You can switch back after
# you have installed caffe.
# Install CUDA toolkit 8.0 release candidate
# Register and download from https://developer.nvidia.com/cuda-release-candidate-download
@philster
philster / tensorflow_macos_sse41_sse42_avx_avx2_fma_cuda.md
Last active January 8, 2019 11:21
Build TensorFlow 1.3 with SSE4.1/SSE4.2/AVX/AVX2/FMA and NVIDIA CUDA support on macOS Sierra 10.12

Build TensorFlow 1.3 with SSE4.1/SSE4.2/AVX/AVX2/FMA and NVIDIA CUDA support on macOS Sierra 10.12 (updated October 5, 2017)

These instructions were inspired by Mistobaan's gist, ageitgey's gist, and mattiasarro's tutorial.

Background

I always encountered the following warnings when running my scripts using the precompiled TensorFlow Python package:

W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] Th
@mommi84
mommi84 / awesome-kge.md
Last active April 14, 2025 11:27
Awesome Knowledge Graph Embedding Approaches
@howar31
howar31 / Markdown_Cheatsheet.md
Last active July 24, 2023 07:43
Markdown Cheatsheet
@sebleier
sebleier / NLTK's list of english stopwords
Created August 27, 2010 22:04
i
me
my
myself
we
our
ours
ourselves
you
your