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/sid_process.py | 17 +++++++++--------
1 files changed, 9 insertions(+), 8 deletions(-)
diff --git a/aoi_ocr/sid_process.py b/aoi_ocr/sid_process.py
index d8798f1..dac85e4 100644
--- a/aoi_ocr/sid_process.py
+++ b/aoi_ocr/sid_process.py
@@ -4,7 +4,7 @@
import pkg_resources
-templatefile = '/template-8.png' # always use slash
+templatefile = "/template-8.png" # always use slash
template8 = pkg_resources.resource_filename(__name__, templatefile)
@@ -15,14 +15,14 @@
return np.ones((x, y), np.uint8)
-def find_biggest_blob(image, original_image,sid_mask):
+def find_biggest_blob(image, original_image, sid_mask):
if sid_mask[0] == "1":
move_left = 35
elif sid_mask[0] == "x":
move_left = 40
else:
move_left = 0
- # Remove noise
+ # Remove noise
image2 = cv2.morphologyEx(
original_image, cv2.MORPH_OPEN, kernel(2, 2), iterations=3
)
@@ -40,6 +40,7 @@
image = image[y : y + h, x + 25 - move_left : x + w - 40] # +25,-25
return image
+
def sid_compare(sid_no, sid_mask):
"""
Function compares student id number with student id mask if the recognised number is valid according to the mask
@@ -53,7 +54,7 @@
return True
-def segment_by_contours(image, original_image, classifier,sid_mask):
+def segment_by_contours(image, original_image, classifier, sid_mask):
"""
First algorithm. it segments numerals with contours. It works with numbers where individual numerals does not touch.
:param image:
@@ -63,8 +64,8 @@
"""
sid_no = ""
- image=find_biggest_blob(image,original_image,sid_mask)
- cv2.imwrite("/tmp/sid_contour1.png",image)
+ image = find_biggest_blob(image, original_image, sid_mask)
+ cv2.imwrite("/tmp/sid_contour1.png", image)
im2, ctrs, hier = cv2.findContours(
image.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
)
@@ -100,7 +101,7 @@
"""
sid_no = ""
sid_len = len(sid_mask)
- image=find_biggest_blob(image,original_image,sid_mask)
+ image = find_biggest_blob(image, original_image, sid_mask)
cv2.imwrite("/tmp/sidblock2.png", image)
imgHeight, imgWidth = image.shape[0:2]
numWidth = int(imgWidth / (sid_len))
@@ -190,7 +191,7 @@
cv2.imwrite("/tmp/enSID0.png", image)
# Remove noise
- #image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel(2, 2), iterations=3)
+ # image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel(2, 2), iterations=3)
# Closing. Connect non connected parts
image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel(5, 1), iterations=4)
--
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