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from Ocr import Paper |
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from sklearn.externals import joblib |
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from glob import glob |
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settings = {"sid_mask": "61xx0xxx", "answer_treshold": 0.25} |
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classifier = joblib.load("filename.joblib") |
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#p = Paper(filename="testpage300dpi_scan1.png") |
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#p=Paper(filename='sizif111.tif', sid_classifier=classifier, settings=settings) |
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#p=Paper(filename='processed_scans/20141016095134535_0006.tif', sid_classifier=classifier, settings=settings) |
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#p=Paper(filename='processed_scans/20151111080408825_0001.tif', sid_classifier=classifier, settings=settings) |
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p=Paper(filename='processed_scans/20151028145444607_0028.tif', sid_classifier=classifier, settings=settings) |
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# print(p.QRData) |
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# print(p.errors) |
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# print(p.getSkewAngle()) |
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# print(p.locateUpMarkers()) |
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# print(p.locateRightMarkers()) |
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# print(p.answerMatrix) |
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# p.get_enhanced_sid() |
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print(p.get_paper_ocr_data()) |
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exit(0) |
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filelist = glob("processed_scans/*.tif") |
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for f in filelist: |
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print(f,Paper(filename=f, sid_classifier=classifier, settings=settings).get_paper_ocr_data()) |
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