From 5460bf601a854c842342a740df0f6d36ad785bbc Mon Sep 17 00:00:00 2001
From: Samo Penic <samo.penic@gmail.com>
Date: Wed, 21 Nov 2018 21:12:48 +0000
Subject: [PATCH] Some extra editing

---
 aoi_ocr/Ocr.py |   33 ++++++++++++++++++++-------------
 1 files changed, 20 insertions(+), 13 deletions(-)

diff --git a/aoi_ocr/Ocr.py b/aoi_ocr/Ocr.py
index f4b2eae..e022ff1 100644
--- a/aoi_ocr/Ocr.py
+++ b/aoi_ocr/Ocr.py
@@ -5,7 +5,7 @@
 import os
 import pkg_resources
 
-markerfile = '/template.png'  # always use slash
+markerfile = '/template-sq.png'  # always use slash
 markerfilename = pkg_resources.resource_filename(__name__, markerfile)
 
 
@@ -41,6 +41,7 @@
             return
         self.decodeQRandRotate()
         self.imgTreshold()
+        cv2.imwrite('/tmp/debug_threshold.png', self.bwimg)
         skewAngle = 0
         # 		try:
         # 			skewAngle=self.getSkewAngle()
@@ -96,10 +97,10 @@
         self.imgHeight, self.imgWidth = self.img.shape[0:2]
 
         # todo, make better tresholding
-
     def imgTreshold(self):
         (self.thresh, self.bwimg) = cv2.threshold(
-            self.img, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU
+            self.img, 128, 255,
+            cv2.THRESH_BINARY | cv2.THRESH_OTSU
         )
 
     def getSkewAngle(self):
@@ -135,7 +136,7 @@
     def locateUpMarkers(self, threshold=0.85, height=200):
         template = cv2.imread(markerfilename, 0)
         w, h = template.shape[::-1]
-        crop_img = self.img[0:height, :]
+        crop_img = self.bwimg[0:height, :]
         res = cv2.matchTemplate(crop_img, template, cv2.TM_CCOEFF_NORMED)
         loc = np.where(res >= threshold)
         cimg = cv2.cvtColor(crop_img, cv2.COLOR_GRAY2BGR)
@@ -172,7 +173,8 @@
     def locateRightMarkers(self, threshold=0.85, width=200):
         template = cv2.imread(markerfilename, 0)
         w, h = template.shape[::-1]
-        crop_img = self.img[:, -width:]
+        crop_img = self.bwimg[:, -width:]
+        cv2.imwrite('/tmp/debug_right.png', crop_img)
         res = cv2.matchTemplate(crop_img, template, cv2.TM_CCOEFF_NORMED)
         loc = np.where(res >= threshold)
         cimg = cv2.cvtColor(crop_img, cv2.COLOR_GRAY2BGR)
@@ -188,9 +190,13 @@
                     loc_filtered_y.append(pt[1])
                     loc_filtered_x.append(pt[0])
                     # order by y coordinate
-            loc_filtered_y, loc_filtered_x = zip(
-                *sorted(zip(loc_filtered_y, loc_filtered_x))
-            )
+            try:
+                loc_filtered_y, loc_filtered_x = zip(
+                    *sorted(zip(loc_filtered_y, loc_filtered_x))
+                )
+            except:
+                self.yMarkerLocations=[np.array([1,1]),np.array([1,2])]
+                return self.yMarkerLocations
             # loc=[loc_filtered_y,loc_filtered_x]
             # remove duplicates
             a = np.diff(loc_filtered_y) > 40
@@ -237,7 +243,7 @@
         es, err, warn = getSID(
             self.img[
                 int(0.04 * self.imgHeight) : int(0.095 * self.imgHeight),
-                int(0.7 * self.imgWidth) : int(0.99 * self.imgWidth),
+                int(0.65 * self.imgWidth) : int(0.95 * self.imgWidth),
             ],
             self.sid_classifier,
             sid_mask,
@@ -270,9 +276,10 @@
             data = qrdata.split(",")
             retval = {
                 "exam_id": int(data[1]),
-                "page_no": int(data[3])+1,
+                "page_no": int(data[3]),
                 "paper_id": int(data[2]),
                 "faculty_id": int(data[0]),
+                "sid": None
             }
             if len(data) > 4:
                 retval["sid"] = data[4]
@@ -285,11 +292,11 @@
         data["errors"] = self.errors
         data["warnings"] = self.warnings
         data["up_position"] = (
-            list(self.xMarkerLocations[1] / self.imgWidth),
-            list(self.yMarkerLocations[1] / self.imgHeight),
+            list(self.xMarkerLocations[0] / self.imgWidth),
+            list(self.xMarkerLocations[1] / self.imgHeight),
         )
         data["right_position"] = (
-            list(self.xMarkerLocations[1] / self.imgWidth),
+            list(self.yMarkerLocations[0] / self.imgWidth),
             list(self.yMarkerLocations[1] / self.imgHeight),
         )
         data["ans_matrix"] = (

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