proc.py

import cv2
import numpy as np
import pytesseract
import re


def get_grayscale(image):
    return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)


# noise removal
def remove_noise(image):
    return cv2.medianBlur(image, 5)


# thresholding
def thresholding(image):
    return cv2.threshold(image, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]


# dilation
def dilate(image):
    kernel = np.ones((5, 5), np.uint8)
    return cv2.dilate(image, kernel, iterations=1)


# erosion
def erode(image):
    kernel = np.ones((5, 5), np.uint8)
    return cv2.erode(image, kernel, iterations=1)


# opening - erosion followed by dilation
def opening(image):
    kernel = np.ones((5, 5), np.uint8)
    return cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel)


# canny edge detection
def canny(image):
    return cv2.Canny(image, 100, 200)


# skew correction

def deskew(image):
    image = cv2.imread(image)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    gray = cv2.bitwise_not(gray)
    thresh = cv2.threshold(gray, 0, 255,
                           cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
    coords = np.column_stack(np.where(thresh > 0))
    angle = cv2.minAreaRect(coords)[-1]

    # the `cv2.minAreaRect` function returns values in the
    # range [-90, 0); as the rectangle rotates clockwise the
    # returned angle trends to 0 -- in this special case we
    # need to add 90 degrees to the angle
    if angle < -45:
        angle = -(90 + angle)

    # otherwise, just take the inverse of the angle to make
    # it positive
    else:
        angle = -angle

    (h, w) = image.shape[:2]
    center = (w // 2, h // 2)
    M = cv2.getRotationMatrix2D(center, angle, 1.0)
    rotated = cv2.warpAffine(image, M, (w, h),
                             flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)

    cv2.putText(rotated, "Angle: {:.2f} degrees".format(angle),
                (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)

    # show the output image
    print("[INFO] angle: {:.3f}".format(angle))
    cv2.imshow("Input", image)
    cv2.imshow("Rotated", rotated)
    cv2.waitKey(0)
    return rotated