From 0436f6a7caac71fc119c6e70a8b0cd1a8fe1f9d7 Mon Sep 17 00:00:00 2001
From: Samo Penic <samo.penic@gmail.com>
Date: Fri, 16 Nov 2018 19:33:59 +0000
Subject: [PATCH] Added template and created some return value for ocr.
---
aoiOcr.py | 25 +++++++-----
Ocr.py | 37 ++++++++++++++++++
2 files changed, 50 insertions(+), 12 deletions(-)
diff --git a/Ocr.py b/Ocr.py
index 970fb70..f680669 100644
--- a/Ocr.py
+++ b/Ocr.py
@@ -10,9 +10,10 @@
self.filename = filename
self.invalid = None
self.QRData = None
- self.settings = settings
+ self.settings={'answer_treshold':0.25,} if settings is None else settings
self.errors = []
self.warnings = []
+ self.sid=None
self.sid_classifier = sid_classifier
if filename is not None:
self.loadImage(filename)
@@ -228,3 +229,37 @@
sid_mask
)
return es
+
+
+ def get_code_data(self):
+ qrdata = bytes.decode(self.QRData, 'utf8')
+ if self.QRDecode[0].type=='EAN13':
+ return {'exam_id': int(qrdata[0:7]),
+ 'page_no': int(qrdata[7]),
+ 'paper_id': int(qrdata[-5:-1]),
+ 'faculty_id': None,
+ 'sid': None
+ }
+ else:
+ data=qrdata.split(',')
+ retval={'exam_id': int(data[1]),
+ 'page_no': int(data[3]),
+ 'paper_id':int(data[2]),
+ 'faculty_id':int(data[0]),
+ }
+ if(len(data)>4):
+ retval['sid']=data[4]
+
+ return retval
+
+ def get_paper_ocr_data(self):
+ data=self.get_code_data()
+ data['qr']=self.QRData
+ data['errors']=self.errors
+ data['warnings']=self.warnings
+ data['up_position']=(list(self.xMarkerLocations[1]/self.imgWidth), list(self.yMarkerLocations[1]/self.imgHeight))
+ data['right_position']=(list(self.xMarkerLocations[1]/self.imgWidth), list(self.yMarkerLocations[1]/self.imgHeight))
+ data['ans_matrix']=((np.array(self.answerMatrix)>self.settings['answer_treshold'])*1).tolist()
+ if data['sid'] is None:
+ data['sid']=self.get_enhanced_sid()
+ return data
diff --git a/aoiOcr.py b/aoiOcr.py
index 5a27df0..74e4fdb 100644
--- a/aoiOcr.py
+++ b/aoiOcr.py
@@ -2,18 +2,21 @@
from sklearn.externals import joblib
-settings={'sid_mask':'11xx0xxx',}
-classifier = joblib.load('filename.joblib')
+settings = {"sid_mask": "11xx0xxx", "answer_treshold": 0.25}
+classifier = joblib.load("filename.joblib")
-#p=Paper(filename='testpage300dpi_scan1.png')
+#p = Paper(filename="testpage300dpi_scan1.png")
p=Paper(filename='sizif111.tif', sid_classifier=classifier, settings=settings)
-#p=Paper(filename='processed_scans/20141016095134535_0028.tif')
+# p=Paper(filename='processed_scans/20141016095134535_0028.tif')
-print(p.QRData)
-print(p.errors)
+# print(p.QRData)
+# print(p.errors)
-print(p.getSkewAngle())
-print(p.locateUpMarkers())
-print(p.locateRightMarkers())
-print(p.answerMatrix)
-p.get_enhanced_sid()
+# print(p.getSkewAngle())
+# print(p.locateUpMarkers())
+# print(p.locateRightMarkers())
+# print(p.answerMatrix)
+# p.get_enhanced_sid()
+
+
+print(p.get_paper_ocr_data())
--
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