This document discusses applying shell scripting skills to build a time-lapse video from webcam still images of Snowdon, Wales. It describes downloading images from a webcam site over time, cleaning and renaming the image files, and using avconv to combine them into a video. The script is aimed at beginners but leaves room for improvement, such as reducing color noise and investigating better encoders. Further directions are provided to create the highest quality video possible from the still images.

1. Applied Shell Scripting
Shoaib Sufi
(part of assignment 5.5 SWC instructors course)

2. Background
• SWC instructors course
• 10 minutes of instruction (maybe more)
• Feedback
• About novice to competence (not expertise)
• Thanks for taking the time

3. Motivation
• To use shell scripting skills learned
• To build something interesting …
• …. That is open for iterative improvement
• Try to follow the data driven research cycle
– Build dataset
– Process data
– analyse results (in this example we only display)
• Area of investigation
• Scenic webcam stills to a time-lapse video

4. Caveats
• Not the clearest webcam
– Perhaps more interesting to try to improve
• Not the most perfect of scripts
– Future steps might include functions/config etc.
• Not using version control
– An example for github left for the user
• As said earlier this is a system that can be
iteratively improved
• Aimed at someone who knows the basic scripting
commands and interested to see it in practice

5. The Webcam – Snowdon, Wales, UK
http://www.fhc.co.uk/weather/images/sn_huge.jpg

6. Building a dataset
• Script
#!/bin/bash
while [ 1 -lt 3 ]
do
curl -o sn_huge_`date +%F-%T`.jpg http://www.fhc.co.uk/weather/images/sn_huge.jpg
sleep 60
done
• Running as a background task
#get_data.sh
#Ctrl-z
#bg %1

7. Stage files
• To a working directory – preserve dataset
#mkdir working-dir
#cp *.jpg working-dir

8. Clean files 1 – rem duff html files
• Remove duff html
for i in `ls *.jpg`
do
rm `file $i | grep HTML | cut -d":" -f1,2,3` 2&1 > /dev/null
done

9. Clean files 2 - duplicates
#!/bin/bash
# running this script twice should not produce any 'is a duplicate' output
declare -a SHA1BEFORE
count=0
current_sum_is_duplicate=0
#for all of the files that are pictures
for i in `ls *.jpg`
do
#get the sha1 sum of the current file
sum=`sha1sum $i | cut -d" " -f1`
echo sha1sum of file $i is $sum
#if sha1sum seen before then delete the file as it's a duplicate
for j in ${SHA1BEFORE[@]}
do
if [ $sum == $j ]
then
echo $i is a duplicate and will be deleted
rm $i
current_sum_is_duplicate=1
break
fi
done
#collect sha1sums if not seen before (if you collect all comparisons will slow down quicker)
if [ $current_sum_is_duplicate == 0 ]
then
SHA1BEFORE[$count]=$sum
count=$(( $count + 1 ))
fi
# reset the sha1sum seen before flag
current_sum_is_duplicate=0
done

10. Rename file
• To allow avconv to work
#!/bin/bash
count=1
#for all of the files that are pictures
for i in `ls *.jpg`
do
cp $i filename_${count}.jpg
count=$(( $count + 1 ))
done

11. Making the video
#!/bin/bash
avconv -i filename_%d.jpg -q:v 1 -aspect:v 4:3 output.mp4
# some problems/solutions – default command actions not always best
# video quality seems poor - blocky in parts [fixed -q:v 1 -v is the stream
specifier which is the video in this case]
# image seems stretched - i.e. not same aspect ratio as images - seems
widescreen [fixed with -aspect:v 4:3]
# not sure why frames are being dropped during encoding and no matter
what frame rate I choose the video seems to be the same length in time
to play – weird

12. An Example video
• Post on vimeo ?

13. Further directions
(aim:to get a nice as video as possible from stills)
• Histogram – flicker
– Could be a simple fix for files over 100K
– Nicer to do mathematically/analytically
• Lots of red green colour noise
– How much can this be reduced without decreasing
image sharpness
• Would morphing make for a better video
– Worth exploring maybe
• Investigate better encoder
– Better quality and smaller filesize

14. Research ?
• Possible research questions
– Anything useful about
• Erosion
• Weather
• Sunrise/sunset time detection – possible cf. HMNAO times
• Contentions
– Perhaps it’s all been done before
– Should have done a literature review
• Still useful and fun
– Applied to a nice task
– Lot’s of room for iterative improvement
• Better scripts, version control
• Interesting problems to fix (as mentioned in further directions)