From 8dad6520729d26d90ebee48939d7f2a1fd73dd38 Mon Sep 17 00:00:00 2001
From: Samo Penic <samo.penic@gmail.com>
Date: Thu, 24 Jan 2019 15:24:06 +0000
Subject: [PATCH] Fix in pages that don't have qr code
---
aoi_ocr/sid_process.py | 46 ++++++++++++++++++++++++++--------------------
1 files changed, 26 insertions(+), 20 deletions(-)
diff --git a/aoi_ocr/sid_process.py b/aoi_ocr/sid_process.py
index 04dbc8d..5d965ec 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)
@@ -15,19 +15,19 @@
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 = 45
elif sid_mask[0] == "x":
- move_left = 55
+ move_left = 50
else:
move_left = 0
- # Remove noise
+ # Remove noise
image2 = cv2.morphologyEx(
- original_image, cv2.MORPH_OPEN, kernel(2, 2), iterations=7
+ original_image, cv2.MORPH_OPEN, kernel(2, 2), iterations=3
)
# find biggest block of pixels
- image1 = cv2.morphologyEx(image2, cv2.MORPH_DILATE, kernel(5, 25), iterations=4)
+ image1 = cv2.morphologyEx(image, cv2.MORPH_DILATE, kernel(5, 25), iterations=3)
image1 = img_as_ubyte(image1 > 50)
cv2.imwrite("/tmp/sidblock1.png", image1)
im2, ctrs, hier = cv2.findContours(
@@ -37,8 +37,9 @@
ctrs, key=lambda ctr: cv2.contourArea(ctr)
) # get bigges contour
x, y, w, h = cv2.boundingRect(sorted_ctrs[-1])
- image = image[y : y + h, x + 25 - move_left : x + w - 40] # +25,-25
+ image = image[y : y + h, x + 25 - move_left : x + w - 30] # +25,-25
return image
+
def sid_compare(sid_no, sid_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
)
@@ -74,7 +75,7 @@
# Get bounding box
x, y, w, h = cv2.boundingRect(ctr)
# Getting ROI
- if w < h / 2:
+ if w < h / 3:
sid_no = sid_no + "1"
continue
roi = image[y : y + h, x : x + w]
@@ -83,7 +84,11 @@
# cv2.rectangle(image,(x,y),( x + w, y + h ),(0,255,0),2)
cv2.imwrite("/tmp/sid_no_{}.png".format(i), roi)
- sid_no = sid_no + str(classifier.predict(roi.reshape(1, -1) / 255.0)[0])
+ sid_currno= str(classifier.predict(roi.reshape(1, -1) / 255.0)[0])
+ sid_no = sid_no + sid_currno
+ fname="/tmp/SID/"+str(sid_currno)+"/sid"+str(np.random.randint(0,1000000))+".png"
+ print("Writing all the sid images ", fname)
+ cv2.imwrite(fname, roi)
return sid_no
@@ -100,7 +105,7 @@
"""
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))
@@ -186,27 +191,28 @@
sid_err = []
image = 255 - image
image_original = image.copy()
- image = img_as_ubyte(image > 100)
+ image = img_as_ubyte(image > 70)
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(3, 3), iterations=2)
# Closing. Connect non connected parts
- image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel(5, 3), iterations=4)
+ image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel(5, 1), iterations=4)
# Again noise removal after closing
- # image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel(8, 8), iterations=1)
+ #image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel(8, 8), iterations=1)
# don't do too much noise removal.
- image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel(3, 3), iterations=1)
+ #image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel(3, 3), iterations=2)
# Skeletonization
+ #image = img_as_ubyte(morphology.skeletonize(image > 128))
image = img_as_ubyte(morphology.thin(image > 128))
cv2.imwrite("/tmp/enSID1.png", image)
# Stub removal (might not be necessary if thinning instead of skeletonize is used above
# Making lines stronger
- image = cv2.morphologyEx(image, cv2.MORPH_DILATE, kernel(5, 5), iterations=1)
+ image = cv2.morphologyEx(image, cv2.MORPH_DILATE, kernel(5, 2), iterations=1)
image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel(10, 10))
# Thining again
@@ -226,5 +232,5 @@
if not sid_compare(sid_no, sid_mask):
sid_err = ["Wrong SID!"]
-
+ cv2.imwrite("/tmp/SID_"+sid_no+".png", image)
return sid_no, sid_err, sid_warn
--
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