finalocr.py

from skimage.filters import threshold_local
from PIL import Image
import pytesseract
import numpy as np
import argparse
import imutils
import cv2
import os

def order_points(pts):
	rect = np.zeros((4, 2), dtype = "float32")

	s = pts.sum(axis = 1)
	rect[0] = pts[np.argmin(s)]
	rect[2] = pts[np.argmax(s)]

	diff = np.diff(pts, axis = 1)
	rect[1] = pts[np.argmin(diff)]
	rect[3] = pts[np.argmax(diff)]

	return rect

def four_point_transform(image, pts):

	rect = order_points(pts)
	(tl, tr, br, bl) = rect

	widthA = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2))
	widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2))
	maxWidth = max(int(widthA), int(widthB))

	heightA = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2))
	heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2))
	maxHeight = max(int(heightA), int(heightB))

	dst = np.array([
		[0, 0],
		[maxWidth - 1, 0],
		[maxWidth - 1, maxHeight - 1],
		[0, maxHeight - 1]], dtype = "float32")

	M = cv2.getPerspectiveTransform(rect, dst)
	warped = cv2.warpPerspective(image, M, (maxWidth, maxHeight))

	return warped

ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True, help="path to input image to be OCR'd")
ap.add_argument("-p", "--preprocess", type=str, default="thresh", help="type of preprocessing to be done")
args = vars(ap.parse_args())

image = cv2.imread(args["image"])
ratio = image.shape[0] / 500.0
orig = image.copy()
image = imutils.resize(image, height = 500)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
edged = cv2.Canny(gray, 75, 200)

cnts = cv2.findContours(edged.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
cnts = sorted(cnts, key = cv2.contourArea, reverse = True)[:5]

screenCnt = np.array([ [[0 ,0]],[[0, 0]],[[0, 0]],[[0, 0]] ])
for c in cnts:
	peri = cv2.arcLength(c, True)
	approx = cv2.approxPolyDP(c, 0.02 * peri, True)

	if len(approx) == 4:
		screenCnt = approx
		break

if ( screenCnt.any() ):
	cv2.drawContours(image, [screenCnt], -1, (0, 255, 0), 2)
	warped = four_point_transform(orig, screenCnt.reshape(4, 2) * ratio)
	warped = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)
	T = threshold_local(warped, 11, offset = 10, method = "gaussian")
	warped = (warped > T).astype("uint8") * 255
    cv2.imwrite("output.jpg", imutils.resize(warped, height = 650))

else :
	img = cv2.imread(args["image"])
	cv2.imwrite("output.jpg", img)

image = cv2.imread('//home/jenim/text_rec-sum/output.jpg')
#image = img.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

if args["preprocess"] == "thresh":
	gray = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]

elif args["preprocess"] == "blur":
	gray = cv2.medianBlur(gray, 3)

filename = "{}.png".format(os.getpid())

cv2.imwrite(filename, gray)

text = pytesseract.image_to_string(Image.open(filename))
print(text)

os.remove(filename)
#os.remove('//home/jenim/text_rec-sum/output.jpg')