Wei Yang bearpaw

To remove a submodule you need to:

Configuration of AWS for ELEG 5491

Most of the steps can be found in this note: Create an iPython HTML Notebook on Amazon's AWS Free Tier from scratch.
If you are more comfortable with video tutorial, don't miss this YouTube tutorial: iPython notebook on AWS
Easier way: After setting your AWS, you can easily install python and notebook by running this script

If you want to use an FTP client to transfer data between local machine and AWS server, you may be instrested in this tutorial.

	conda create -n open-mmlab python=3.7 -y
	source activate open-mmlab

	conda install -c pytorch pytorch torchvision -y
	conda install cython -y
	git clone https://github.com/open-mmlab/mmdetection.git
	cd mmdetection
	./compile.sh
	pip install -e . # "pip install ." for installation mode

	import numpy as np
	from tensorboard.backend.event_processing import event_accumulator as ea

	import matplotlib as mpl
	import matplotlib.pyplot as plt

	def plot_tensorflow_log(path):

	# Loading too much data is slow...
	tf_size_guidance = {

	var https = require('https'),
	user = process.argv[2],
	opts = parseOpts(process.argv.slice(3))

	request('/users/' + user, function (res) {
	if (!res.public_repos) {
	console.log(res.message)
	return
	}
	var pages = Math.ceil(res.public_repos / 100),

	#!/usr/bin/env bash

	cd ~
	wget https://repo.continuum.io/archive/Anaconda2-4.3.0-Linux-x86_64.sh
	bash Anaconda2-4.3.0-Linux-x86_64.sh -b
	echo 'PATH="/home/ubuntu/anaconda2/bin:$PATH"' >> .bashrc
	. .bashrc

	jupyter notebook --generate-config

	# extract 24 frames per second
	ffmpeg -i Peter-Jasko-solo-M-idzomer-2013.mp4 -r 24/1 frames/solo-dance-%04d.png

	# generate video from images, -q 0 is the highest quality
	ffmpeg -start_number 222 -i %d.png -q 0 dance_skeleton.avi

	ffmpeg -framerate 10 -start_number 0 -i %06d.png -q 0 ../h36m_triangulation.mp4