| #!/bin/bash | |
| # install CUDA Toolkit v8.0 | |
| # instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network)) | |
| CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb" | |
| wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG} | |
| sudo dpkg -i ${CUDA_REPO_PKG} | |
| sudo apt-get update | |
| sudo apt-get -y install cuda |
| # Copyright 2015 The TensorFlow Authors. All Rights Reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| kubectl get pods | grep Evicted | awk '{print $1}' | xargs kubectl delete pod |
Here you'll learn how to build Tensorflow for the raspberry pi 3 with either the Python API or as a standalone shared library which can be interfaced from the C++ API and eventually as a library which can be used in other languages.
For the C++ library this tutorial will show you how extract tensorflow library and headers to use in any environment you want.
(This tutorial couldn't be possible without the help of the people from the References section)
| /* | |
| * Extract multiple screenshots/frames from a video URL | |
| * Params | |
| * - vidURL : video URL | |
| * - frOffsets : array of timestamps | |
| * - frameWidth : screenshot width (default: video width) | |
| * Returns | |
| * - frames: object with offset => {imgUrl, blob} | |
| * | |
| * An multiple-frame extension of http://cwestblog.com/2017/05/03/javascript-snippet-get-video-frame-as-an-image/ |