from Ocr import Paper
|
from sklearn.externals import joblib
|
|
from glob import glob
|
|
settings = {"sid_mask": "64xx0xxx", "answer_treshold": 0.25}
|
classifier = joblib.load("filename.joblib")
|
|
#p = Paper(filename="testpage300dpi_scan1.png")
|
#p=Paper(filename='sizif111.tif', sid_classifier=classifier, settings={"sid_mask": "11xx0xxx", "answer_treshold": 0.25})
|
#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)
|
pa = [
|
"processed_scans/20141016095134535_0006.tif",
|
"processed_scans/20141016095134535_0028.tif",
|
"processed_scans/20141016095134535_0028.tif",
|
"processed_scans/20141016095134535_0037.tif",
|
"processed_scans/20141021095744144_0005.tif",
|
"processed_scans/20141021095744144_0009.tif",
|
"processed_scans/20141028095553745_0018.tif",
|
"processed_scans/20151013180545275_0011.tif"
|
]
|
p=Paper(filename=pa[7], 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 sorted(filelist):
|
print("processing: {}".format(f))
|
print(
|
f,
|
Paper(
|
filename=f, sid_classifier=classifier, settings=settings
|
).get_paper_ocr_data(),
|
)
|
