| | |
|---|
| | | from Ocr import Paper |
|---|
| | | from aoi_ocr.Ocr import Paper |
|---|
| | | from sklearn.externals import joblib |
|---|
| | | import pkg_resources |
|---|
| | | path = '/filename.joblib' # always use slash |
|---|
| | | filepath = pkg_resources.resource_filename('aoi_ocr', path) |
|---|
| | | |
|---|
| | | classifier = joblib.load('filename.joblib') |
|---|
| | | from glob import glob |
|---|
| | | |
|---|
| | | #p=Paper(filename='testpage300dpi_scan1.png') |
|---|
| | | p=Paper(filename='sizif111.tif', sid_classifier=classifier) |
|---|
| | | #p=Paper(filename='processed_scans/20141016095134535_0028.tif') |
|---|
| | | settings = {"sid_mask": "11x0xxxx", "answer_threshold": 0.25} |
|---|
| | | classifier = joblib.load(filepath) |
|---|
| | | |
|---|
| | | print(p.QRData) |
|---|
| | | print(p.errors) |
|---|
| | | #p = Paper(filename="testpage300dpi_scan1.png") |
|---|
| | | #p=Paper(filename='sizif111.tif', sid_classifier=classifier, settings={"sid_mask": "11xx0xxx", "answer_threshold": 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", |
|---|
| | | "processed_scans/20160408140801098_0004.tif", |
|---|
| | | "processed_scans/20160510075445995_0026.tif" |
|---|
| | | ] |
|---|
| | | #p=Paper(filename=pa[9], sid_classifier=classifier, settings=settings) |
|---|
| | | p=Paper(filename='test3.tif', sid_classifier=classifier, settings=settings) |
|---|
| | | |
|---|
| | | print(p.getSkewAngle()) |
|---|
| | | print(p.locateUpMarkers()) |
|---|
| | | print(p.locateRightMarkers()) |
|---|
| | | print(p.answerMatrix) |
|---|
| | | p.get_enhanced_sid() |
|---|
| | | # 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") |
|---|
| | | wrong_sid=0; |
|---|
| | | total=0 |
|---|
| | | for f in sorted(filelist): |
|---|
| | | print("processing: {}".format(f)) |
|---|
| | | p=Paper(filename=f, sid_classifier=classifier, settings=settings).get_paper_ocr_data() |
|---|
| | | print(f,p) |
|---|
| | | if(p['page_no']==0): |
|---|
| | | total+=1 |
|---|
| | | if(len(p['errors'])!=0): |
|---|
| | | wrong_sid+=1 |
|---|
| | | if total%10 == 0: |
|---|
| | | print("Total:{}, wrong SID: {}".format(total,wrong_sid)) |
|---|
| | | |
|---|
| | | print("Total:{}, wrong SID: {}".format(total,wrong_sid)) |
|---|
