Description:

labelwrapper 0.1.2

Label wrapper
User friendly image bootstraping framework.
Label bootstrapping flow
Label wrapper enables label bootstrapping process:

Load first data batch
Manually label first batch
Train first segmentation model
Load second data batch
Use first trained segmentation model to predict labels
Review labels and merge first and second labelled data
train the second segmentation model
Repeat steps 4.-7. until out of raw data or review of labels is no longer required.


Technical implementation example

Load data into dataset
Export html
Label
Export to json
Import json and convert json to tfrecords
Train on tfrecords
Introduce new data
Predict with trained model to tf records
Import stored tfrecords and convert to html with labels
Review stored labels and export to json
Join reviewed json and manual json (from step 4)
Repeat 5 - 11 for n times
Run out of data to label
Measure performance

TODO

Finnish dual data dataset with gtiff (add test)
mask to shapefile (geocoded)
shapefile exporter
shapefile imporoter?
example inference step with a pretrained segmentation cnn
(maybe) constructor should take json and load it in postinit
(maybe) Add via html tests with js (selenium?)

Thanks
Label editor used is VIA 2.0.6.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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