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FabVis-Preprocess


Setup

Clone the repository

git clone https://github.com/IntellisenseLab/FabVis-RD-Preprocess.git

Create a folder to hold the base dataset

mkdir dataset

Optionally download existing data set from here and extract.


Dataset labelling

For installing up dataset labelling software run,

pip3 install labelImg

For starting dataset labelling software run,

cd dataset
labelImg

Dataset processing

For starting the dataset preprocessing process run,

python3 preprocess.py

For checking the dataset distribution after preprocessing run,

python3 checkStatistics.py

For checking the dataset for unannotated images run,

python3 checkDataset.py

Statistics


Annotated Defects

Defect Count
Slubs 44
Barre 7
Thick Yarn 0
Foreign Yarn 3
Missing Line 64
Holes 68
Knots 0
Misknit 8
Dye Spot 12
Crease line/Crush Mark 423
Stains/Dirty 380
Stop marks 0
Snagging 34
Laddering 26

Dataset Distribution

chart


Unannotated Defects

Defect Image Number
Abrasion 1
Dead Cotton 88, 89, 90