msis

1. File > Open ...
2. Launch new terminal instance: New > Terminal
3. tarball the folder:

tar czvhf coursera.tar.gz *

3. a. split it (usually this file might be too large for your instance to allow download)

split -b 500M -d coursera.tar.gz coursera.

msis

1. ssh to the remote instance (based on Ubuntu Deeplearning AMI) with port* redirection:

ssh -L 8888:127.0.0.1:8888 ubuntu@IP

2. activate the environment (here we're using tensorflow_p36):

source activate tensorflow_p36

3. launch jupyter:

msis

Extract frames from video source

ffmpeg -i myvideo.mp4 -vf fps=4 frm%06d.jpg

Change frame rate of h264 video source

ffmpeg -y -i source.mp4 -r 25 -c:v libx264 -b:v 3M -strict -2 -movflags faststart destination.mp4

msis

Install nvidia repo packages:

1. Download nvidia machine learning repo package:

wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb

2. Install that package:

sudo dpkg -i nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb

msis

# things

gpsd -G -n /dev/ttyUSB0
gpspipe -d -r -t -o /home/user/`date -Iminutes`.nmea

# rest of the things
# always end with `exit 0`

msis

from django.core.management.base import BaseCommand, CommandError
from annotator.models import Video
import os
import json
import re
import os
import shutil

# referring to https://stackoverflow.com/questions/5967500/how-to-correctly-sort-a-string-with-a-number-inside for "human sorting"
def atoi(text):

msis

python -m ipykernel install --user --name=XXX

msis

Video conversion with FFmpeg

Command basics

Most basic conversion using Terminal: ffmpeg -i input.mov output.webm.

Strip audio

Flag: -an.

msis

Keybase proof

I hereby claim:

• I am msis on github.
• I am msis (https://keybase.io/msis) on keybase.
• I have a public key ASBZJq2TgOf1QhpCevN0y80xAFS4_1EhJKfAlUlmM_cIWQo

To claim this, I am signing this object:

msis

find $SOURCE -type f | xargs -n1 -P4 -I% rsync -ahPv % $DESTINATION