Hi
user
Admin Login:
Username:
Password:
Name:
An Introduction to Image Classification
--client
pyconza
--show
pyconza2015
--room room211 10320 --force
Next: 11 A little scripting goes a long way: automating data processing in science
show more...
Marks
Author(s):
Abuobayda Shabat
Location
Room 211
Date
oct Thu 01
Days Raw Files
Start
11:00
First Raw Start
10:57
Duration
01:30:00
Offset
0:02:54
End
12:30
Last Raw End
12:13
Chapters
00:00
Total cuts_time
71 min.
https://za.pycon.org/talks/21/
raw-playlist
raw-mp4-playlist
encoded-files-playlist
host
archive
public
tweet
mp4
svg
png
assets
release.pdf
An_Introduction_to_Machine_Learning_in_Python.json
logs
Admin:
episode
episode list
cut list
raw files day
marks day
marks day
image_files
State:
---------
borked
edit
encode
push to queue
post
richard
review 1
email
review 2
make public
tweet
to-miror
conf
done
Locked:
clear this to unlock
Locked by:
user/process that locked.
Start:
initially scheduled time from master, adjusted to match reality
Duration:
length in hh:mm:ss
Name:
Video Title (shows in video search results)
Emails:
email(s) of the presenter(s)
Released:
has someone authorised pubication
Unknown
Yes
No
Normalise:
Channelcopy:
m=mono, 01=copy left to right, 10=right to left, 00=ignore.
Thumbnail:
filename.png
Description:
markdown
In this tutorial, two main areas will be covered using Textural Images Dataset: <ol> <li>Textural Features Methods: (Grey Level Co-occurrence Matrix(GLCM), Local Binary Pattern(LBP) and Local Directional Pattern(LDP))</li> <li>Classification using Support Vector Machine (SVM) and Naive Bayes(NB).</li> </ol> Both Features Extraction and Classification will be implemented using Python. Texture is a very important factor in computer vision; it represents the first level of spatial properties that can be extracted from digital image. Texture can be defined as relationship between gray level in neighboring pixels.
Comment:
production notes
2015-10-01/10_57_06.dv
Apply:
10:57:06 - 11:01:50 ( 00:04:44 )
S:
10:57:06 -
E:
11:01:50
D:
00:04:44
show more...
vlc ~/Videos/veyepar/pyconza/pyconza2015/dv/room211/2015-10-01/10_57_06.dv :start-time=00.0 --audio-desync=0
Raw File
Cut List
10:57:06
seconds: 0.0
Wall: 10:57:06
Duration
00:04:44
11:01:50
seconds: 0.0
Wall: 10:57:06
Comments:
mp4
mp4.m3u
dv.m3u
Split:
Sequence:
:
delete
2015-10-01/11_01_51.dv
Apply:
11:01:51 - 12:13:10 ( 01:11:19 )
S:
11:01:51 -
E:
12:13:10
D:
01:11:19
show more...
vlc ~/Videos/veyepar/pyconza/pyconza2015/dv/room211/2015-10-01/11_01_51.dv :start-time=00.0 --audio-desync=0
Raw File
Cut List
11:01:51
seconds: 0.0
Wall: 11:01:51
Duration
01:11:19
12:13:10
seconds: 0.0
Wall: 11:01:51
Comments:
mp4
mp4.m3u
dv.m3u
Split:
Sequence:
:
delete
2015-10-01/12_13_10.dv
Apply:
12:13:10 - 12:13:25 ( 00:00:15 )
S:
12:13:10 -
E:
12:13:25
D:
00:00:15
show more...
vlc ~/Videos/veyepar/pyconza/pyconza2015/dv/room211/2015-10-01/12_13_10.dv :start-time=00.0 --audio-desync=0
Raw File
Cut List
12:13:10
seconds: 0.0
Wall: 12:13:10
Duration
00:00:15
12:13:25
seconds: 0.0
Wall: 12:13:10
Comments:
mp4
mp4.m3u
dv.m3u
Split:
Sequence:
:
delete
Rf filename:
root is .../show/dv/location/, example: 2013-03-13/13:13:30.dv
Sequence:
get this:
check and save to add this
2015-10-01/10_57_06.dv
2015-10-01/11_01_51.dv
2015-10-01/12_13_10.dv
Veyepar
Video Eyeball Processor and Review
