refactored and debugged.

Samo Penic

2018-11-16 762a5e258a90387922d6c6eb3ecc9a7ca7c96144

 Ocr.py

@@ -1,17 +1,19 @@
from pyzbar.pyzbar import decode
from sid_process import enhanceSID
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, settings=None):
        self.filename = filename
        self.invalid = None
        self.QRData = None
        self.settings = settings
        self.errors = []
        self.warnings = []
        self.sid_classifier = sid_classifier
        if filename is not None:
            self.loadImage(filename)
            self.runOcr()
@@ -137,8 +139,8 @@
            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)
@@ -213,5 +215,16 @@
            self.answerMatrix.append(oneline)

    def get_enhanced_sid(self):
        es= enhanceSID(self.img[int(0.04*self.imgHeight):int(0.08*self.imgHeight), int(0.7*self.imgWidth):int(0.99*self.imgWidth)])
        cv2.imwrite("enhancedSID.png",es)
        if self.sid_classifier is None:
            return "x"
        if self.settings is not None:
            sid_mask=self.settings.get("sid_mask", None)
        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,
            sid_mask
        )
        return es