Joe Young joeking11829

Convert Binary Data to OpenCV Image Format

在影像處理時，常常會讀取影像資料(binary data)後轉成影像格式(cv::Mat)，在進行影像操作。

那我們如何轉成可用的OpenCV影像格式呢?

首先讀取檔案後得到binary data，在進行解碼轉成cv::Mat。

當然如果單純讀檔後轉成OpenCV影像格式，OpenCV是有提供cv::imread這個API可以使用。

rsync (Everyone seems to like -z, but it is much slower for me)

a: archive mode - rescursive, preserves owner, preserves permissions, preserves modification times, preserves group, copies symlinks as symlinks, preserves device files.
H: preserves hard-links
A: preserves ACLs

	#!/bin/bash

	set -o errexit

	pushd .

	### Conda

	MINIFORGE_INSTALL_PREFIX=$PWD/miniforge3

	#!/usr/bin/env python
	# -- coding: utf-8 --
	from argparse import ArgumentParser

	import torch
	import torch.distributed as dist
	from torch.nn.parallel import DistributedDataParallel as DDP
	from torch.utils.data import DataLoader, Dataset
	from torch.utils.data.distributed import DistributedSampler
	from transformers import BertForMaskedLM

	#!/bin/bash

	# ssh-cipher-benchmark.sh - Assesses speed of SSH encryption between specific hosts.
	# Usage:
	# ssh-cipher-benchmark.sh <remotehost> [ciphers]
	# Default ciphers: all we can find...
	#
	# Note: In some cases, the first cipher tested runs faster than the others, regardless of order.
	# Cause of this is not known, but changing the order of testing shows it to be true. Run the
	# first one twice if you suspect this. Perhaps it is due to buffering?

	#!/bin/sh
	# Install cuDNN V2 on NVIDIA Jetson TK1
	# Register as a NVIDIA developer and download the cuDNN package
	# Package is named cudnn-6.5-linux-ARMv7-V2.tgz
	# This script and the cuDNN package should be in the same directory, usually ~/Downloads
	# This script places the library and include files for cudnn in the CUDA 6.5 directories
	# Make sure this is executing as root
	if [ $(id -u) != 0 ]; then
	echo "This script requires root permissions"
	echo "$ sudo "$0""

	#!/bin/sh
	# Fresh install for CUDA 6.5 on Jetson TK1 for Linux for Tegra (L4T) 21.1
	# CUDA 6.5 REQUIRES L4T 21.1 !!!
	sudo apt-add-repository universe
	sudo apt-get update
	# This is for L4T r21.1 ; Update for your L4T i.e. r21.3
	wget http://developer.download.nvidia.com/compute/cuda/6_5/rel/installers/cuda-repo-l4t-r21.1-6-5-prod_6.5-14_armhf.deb

	# Install the CUDA repo metadata that you downloaded
	# This is for L4T 21.1 ; Update for your L4T i.e. 21.3