Adjusting pytesseract parameters-CodePudding

The

My first guess is that the image_to_data parameters are not set properly.

Checking

Do you have any suggestion? Am I missing something obvious here?

EDIT:

At Ann Zen's request, here's the code used to obtain the first image:

import imutils import cv2 import matplotlib.pyplot as plt import numpy as np import pytesseract from pytesseract import Output def get_grayscale(image): return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) filename = "IMAGE.JPG" cropped_image = cv2.imread(filename) inverted_cropped_image = cv2.bitwise_not(cropped_image) gray = get_grayscale(inverted_cropped_image) thresholded_image = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY)[1] results = pytesseract.image_to_data(thresholded_image, config='--psm 11 --oem 3 -c tessedit_char_whitelist=0123456789m.', output_type=Output.DICT) color = (255, 255, 255) for i in range(0, len(results["text"])): x = results["left"][i] y = results["top"][i] w = results["width"][i] h = results["height"][i] text = results["text"][i] conf = int(results["conf"][i]) print("Confidence: {}".format(conf)) if conf > 70: print("Confidence: {}".format(conf)) print("Text: {}".format(text)) print("") text = "".join([c if ord(c) < 128 else "" for c in text]).strip() cv2.rectangle(cropped_image, (x, y), (x w, y h), color, 2) cv2.putText(cropped_image, text, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX,1.2, color, 3) cv2.imshow('Image', cropped_image) cv2.waitKey(0)

CodePudding user response：

I have been working with Tesseract for quite some time, so let me clarify something for you. Tesseract is extremely helpful if you're trying to recognize text in documents more than any other computer vision projects. It usually needs a binarized image to get a good output. Therefore, you will always need some image pre-processing.

However, after several trials in the past with all page segmentation modes, I realized that it fails when font size differs on the same line without having a space. Sometimes PSM 6 is helpful if the difference is low, but in your condition, you may try an alternative. If you don't care about the decimals, you may try the following solution:

img = cv2.imread(r'E:\Downloads\Iwzrg.png') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) img_blur = cv2.GaussianBlur(gray, (3,3),0) _,thresh = cv2.threshold(img_blur,200,255,cv2.THRESH_BINARY_INV) # If using a fixed camera new_img = thresh[0:100, 80:320] text = pytesseract.image_to_string(new_img, lang='eng', config='--psm 6 --oem 3 -c tessedit_char_whitelist=0123456789')

OUTPUT: 1227

CodePudding user response：

I would like to recommend applying another image processing method.

Because I am dealing with a dark background, I first invert the image, before converting it to grayscale and thresholding it:

You applied global thresholding and couldn't achieve the desired result.

Then you can apply either

To be able to recognize the image as accurately as possible we can add a border to the top of the image and resize the image (Optional)

In the OCR section, check if the detected region contains a digit

if text.isdigit():

Then display on the image:

The result is nearly the desired value. Now you can try with the other suggested methods to find the exact value.

The problem is .938 recognized as 235, maybe resizing using different values might improve the result.

Code:

from cv2 import imread, cvtColor, COLOR_BGR2HSV as HSV, inRange, getStructuringElement, resize from cv2 import imshow, waitKey, MORPH_RECT, dilate, bitwise_and, rectangle, putText from cv2 import copyMakeBorder as addBorder, BORDER_CONSTANT as CONSTANT, FONT_HERSHEY_SIMPLEX from numpy import array from pytesseract import image_to_data, Output bgr = imread("Iwzrg.png") resized = resize(bgr, (800, 600), fx=0.75, fy=0.75) bordered = addBorder(resized, 200, 0, 0, 0, CONSTANT, value=0) hsv = cvtColor(bordered, HSV) mask = inRange(hsv, array([0, 0, 250]), array([179, 255, 255])) kernel = getStructuringElement(MORPH_RECT, (50, 30)) dilated = dilate(mask, kernel, iterations=1) thresh = 255 - bitwise_and(dilated, mask) data = image_to_data(thresh, output_type=Output.DICT) for i in range(0, len(data["text"])): x = data["left"][i] y = data["top"][i] w = data["width"][i] h = data["height"][i] text = data["text"][i] if text.isdigit(): print("Text: {}".format(text)) print("") text = "".join([c if ord(c) < 128 else "" for c in text]).strip() rectangle(thresh, (x, y), (x w, y h), (0, 255, 0), 2) putText(thresh, text, (x, y - 10), FONT_HERSHEY_SIMPLEX, 1.2, (0, 0, 255), 3) imshow("", thresh) waitKey(0)