from Ocr import Paper
from sklearn.externals import joblib

from glob import glob

settings = {"sid_mask": "61xx0xxx", "answer_treshold": 0.25}
classifier = joblib.load("filename.joblib")

#p = Paper(filename="testpage300dpi_scan1.png")
#p=Paper(filename='sizif111.tif', sid_classifier=classifier, settings=settings)
#p=Paper(filename='processed_scans/20141016095134535_0006.tif', sid_classifier=classifier, settings=settings)
#p=Paper(filename='processed_scans/20151111080408825_0001.tif', sid_classifier=classifier, settings=settings)
p=Paper(filename='processed_scans/20151028145444607_0028.tif', sid_classifier=classifier, settings=settings)

# print(p.QRData)
# print(p.errors)

# print(p.getSkewAngle())
# print(p.locateUpMarkers())
# print(p.locateRightMarkers())
# print(p.answerMatrix)
# p.get_enhanced_sid()


print(p.get_paper_ocr_data())
exit(0)
filelist = glob("processed_scans/*.tif")
for f in filelist:
    print(f,Paper(filename=f, sid_classifier=classifier, settings=settings).get_paper_ocr_data())