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| | | from Ocr import Paper |
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| | | from aoi_ocr.Ocr import Paper |
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| | | from sklearn.externals import joblib |
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| | | import pkg_resources |
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| | | path = '/filename.joblib' # always use slash |
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| | | filepath = pkg_resources.resource_filename('aoi_ocr', path) |
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| | | |
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| | | from glob import glob |
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| | | |
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| | | settings = {"sid_mask": "64xx0xxx", "answer_threshold": 0.25} |
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| | | classifier = joblib.load("filename.joblib") |
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| | | settings = {"sid_mask": "11x0xxxx", "answer_threshold": 0.25} |
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| | | classifier = joblib.load(filepath) |
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| | | |
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| | | #p = Paper(filename="testpage300dpi_scan1.png") |
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| | | #p=Paper(filename='sizif111.tif', sid_classifier=classifier, settings={"sid_mask": "11xx0xxx", "answer_threshold": 0.25}) |
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| | |
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| | | "processed_scans/20160408140801098_0004.tif", |
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| | | "processed_scans/20160510075445995_0026.tif" |
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| | | ] |
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| | | p=Paper(filename=pa[9], sid_classifier=classifier, settings=settings) |
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| | | #p=Paper(filename=pa[9], sid_classifier=classifier, settings=settings) |
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| | | p=Paper(filename='test3.tif', sid_classifier=classifier, settings=settings) |
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| | | |
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| | | # print(p.QRData) |
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| | | # print(p.errors) |
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| | |
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| | | |
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| | | print(p.get_paper_ocr_data()) |
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| | | |
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| | | |
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| | | exit(0) |
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| | | filelist = glob("processed_scans/*.tif") |
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| | | wrong_sid=0; |
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| | | total=0 |
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| | |
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| | | if total%10 == 0: |
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| | | print("Total:{}, wrong SID: {}".format(total,wrong_sid)) |
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| | | |
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| | | print("Total:{}, wrong SID: {}".format(total,wrong_sid)) |
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| | | print("Total:{}, wrong SID: {}".format(total,wrong_sid)) |
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