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DeepStack utils.

Note I have moved the training data and sample model to its own repo to keep this one from becoming too large as I expand the model.

Utils

fullTest

A quick Python 2.7 test to make sure your setup is working. Including the 4 custom models in the DeepStack documentation. Note their online documentation has a lot of errors in it.

startDeepStack.sh

shell script for starting DeepStack with params needed for running tests.

updateDeepStack.sh

shell script for upfating then starting DeepStack with params needed for running tests.

testTorch.bat and testTorch.py

test that Torch setup is working and using your GPU ready to train.

localColab.bat

bat file to bring up my Jupyter Notebook for training with local GPU.

quickLabel.py

Runs pics in newPicPath against all the installed object detect models to generate tag files similar to what the labelImg would produce along with a list of all found objects (classes.txt).

chkClasses.py

Program for merging the output of quickLabel (after being verified) with the data in trainPath

rmClasses.py

Program for removing poor performing or conflicting classes from the data in trainPath