From 0b5a8decb9cc2ba96d2aed1721e48bafb751e33c Mon Sep 17 00:00:00 2001
From: Samo Penic <samo.penic@gmail.com>
Date: Fri, 16 Nov 2018 18:23:09 +0000
Subject: [PATCH] ups, forgot classifier object dump
---
Ocr.py | 20 +++++++++++++++++---
1 files changed, 17 insertions(+), 3 deletions(-)
diff --git a/Ocr.py b/Ocr.py
index ee715f0..35c6729 100644
--- a/Ocr.py
+++ b/Ocr.py
@@ -1,16 +1,18 @@
from pyzbar.pyzbar import decode
+from sid_process import getSID
import cv2
import numpy as np
import math
class Paper:
- def __init__(self, filename=None):
+ def __init__(self, filename=None, sid_classifier=None):
self.filename = filename
self.invalid = None
self.QRData = None
self.errors = []
self.warnings = []
+ self.sid_classifier=sid_classifier
if filename is not None:
self.loadImage(filename)
self.runOcr()
@@ -136,8 +138,8 @@
loc_filtered_x, loc_filtered_y = zip(
*sorted(zip(loc_filtered_x, loc_filtered_y))
)
- # loc=[loc_filtered_y,loc_filtered_x]
- # remove duplicates
+ # loc=[loc_filtered_y,loc_filtered_x]
+ # remove duplicates
a = np.diff(loc_filtered_x) > 40
a = np.append(a, True)
loc_filtered_x = np.array(loc_filtered_x)
@@ -210,3 +212,15 @@
black = totpx - cv2.countNonZero(roi)
oneline.append(black / totpx)
self.answerMatrix.append(oneline)
+
+ def get_enhanced_sid(self):
+ if self.sid_classifier is None:
+ return "x"
+ es = getSID(
+ self.img[
+ int(0.045 * self.imgHeight) : int(0.085 * self.imgHeight),
+ int(0.7 * self.imgWidth) : int(0.99 * self.imgWidth),
+ ],
+ self.sid_classifier,
+ )
+ return es
--
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