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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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| | | |
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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": "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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| | | # 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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| | | pa = [ |
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| | | "processed_scans/20141016095134535_0006.tif", |
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| | | "processed_scans/20141016095134535_0028.tif", |
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| | | "processed_scans/20141016095134535_0028.tif", |
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| | | "processed_scans/20141016095134535_0037.tif", |
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| | | "processed_scans/20141021095744144_0005.tif", |
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| | | "processed_scans/20141021095744144_0009.tif", |
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| | | "processed_scans/20141028095553745_0018.tif", |
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| | | "processed_scans/20151013180545275_0011.tif", |
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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="test3011/sizif000.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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| | | # 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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| | | |
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| | | |
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| | | p=Paper(filename='testpage250dpi1.png') |
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| | | #p=Paper(filename='sizif111.tif') |
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| | | print(p.QRData) |
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| | | print(p.errors) |
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| | | print(p.get_paper_ocr_data()) |
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| | | |
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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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| | | #exit(0) |
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| | | filelist = glob("test3011/*.tif") |
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| | | wrong_sid = 0 |
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| | | total = 0 |
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| | | for f in sorted(filelist): |
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| | | print("processing: {}".format(f)) |
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| | | p = Paper( |
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| | | filename=f, sid_classifier=classifier, settings=settings |
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| | | ).get_paper_ocr_data() |
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| | | print(f, p) |
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| | | if p["page_no"] == 0: |
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| | | total += 1 |
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| | | if len(p["errors"]) != 0: |
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| | | wrong_sid += 1 |
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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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