Thursday, September 12th, 2019 (Discussion Critical Images with Silvan, Labeling App)

Axel, Ulf, Silvan, Subir, Michael, Malin, Maren, Katha, Josefine, Luana

Discussion points of today:

  • label app - some decisions still open

  • discuss critical images - Silvan’s opinion

  • tasks for the next weeks

Presentation of the lableapp:

  • shows all hree images of one asparagus, the pictures are preprocessed

  • labels go into a csv file

  • select a folder/datei to save the data

  • then open labeling dialog to hand label assistant

  • aswer the qustions asked with yes/no

  • display additional information

  • peak in the back to of the figure as indicator to detect violet

  • Katha and Malin are going to write a manual for the labeling process

  • aim: doublelable some of the images

  • we still have to decide on how we handle intra personal differences in labeling

discussion lapeling app:

  • possible to show only the violett colour chanel - check pixels in the violet range

  • take out violet question

  • take out thickness questions

  • double labelling with label app for “labeled folders” first - before we do other stuff

  • possibility to zoom?

  • float for some 0 and 1?

general remarks concerning sorting by Silvan

  • sort 1A anna more conservatively

  • aim to have more than 50% of the first class in the end

  • minimal violett —> violett , even if we detect a tiny bit of violet, it already counts as violet

  • minimal rust -> not rusty, but still first class, only if rust is at head or really bad, it counts as rust

discussion in general / for deep learning:

  • data augmentation : mirroring maybe not so useful (as miror right image might be very similar to left image)

  • maybe normalise the data —> network can be simpler

  • rotation of pieces

  • training different nets (one with background one without)

  • we want to learn features, and not final labels

  • from manual labelling we get impression what features are important, what not! —> use this for nets , we can better “understand”

  • in one of the next sessions ulf can present sth about neural nets

    • also: for technical questions we can always come to his office

TASKS:

  • finish labeling app

  • label images

  • continue manual feature extraction

  • for next step: research on why to use different approaches for deep learning nets - not TOO many approaches

    • each who does net training: looks around what model & technique to use

  • decision: do we want to use tensorflow?

  • rz logins to Ulf

NEXT STEP/ SUGGESTIONS:

  • maybe in future also make it possible that machine can detect class only from one picture - maybe machine is not able to always take 3 pictures - and then can’t classify with only one!?!