Tesseract 未在 Python 上检测到 RGB 图像上的任何文本

Question

嘿，我开始使用 Tesseract OCR，但在从非常简单的 RGB 图像中获取文本时遇到问题。 它适用于 text2image 图像。 这是我的代码：

from PIL import Image
import pytesseract
import argparse
import cv2
import os
import sys


class wordExtractor():
    def __init__(self, image_path):
        self.image_path = image_path
        pytesseract.pytesseract.tesseract_cmd = r'/home/yarin/tesseract/bin/debug/tesseract'
        #self.resize_image()

def resize_image(self):
    basewidth = 800
    img = Image.open(self.image_path)
    wpercent = (basewidth/float(img.size[0]))
    hsize = int((float(img.size[1])*float(wpercent)))
    img = img.resize((basewidth,hsize), Image.ANTIALIAS)
    os.remove(self.image_path)
    img.save(self.image_path[:-4] + '.png') 
    self.image_path = self.image_path[:-4] + '.png'



def get_text(self, lang):
    # load the example image and convert it to grayscale
    image = cv2.imread(self.image_path)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    # check to see if we should apply thresholding to preprocess the
    # image
    #if args["preprocess"] == "thresh":
    gray = cv2.threshold(gray, 0, 255,
        cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
    # make a check to see if median blurring should be done to remove
    # noise
    #elif args["preprocess"] == "blur":
    #   gray = cv2.medianBlur(gray, 3)
    # write the grayscale image to disk as a temporary file so we can
    # apply OCR to it
    filename = "{}.png".format(os.getpid())
    cv2.imwrite(filename, gray)
    #load the image as a PIL/Pillow image, apply OCR, and then delete
    # the temporary file
    text = pytesseract.image_to_string(Image.open(filename), lang='eng')
    os.remove(filename)
    return text
    # show the output images
    #cv2.imshow("Image", image)
    #cv2.imshow("Output", gray)
    #cv2.waitKey(0)

w = wordExtractor('6.png')
print(w.get_text('eng'))

Tesseract 为以下图像返回空字符串：

请告诉我如何解决这个问题提前谢谢！

Answer 1

阈值化后，您可以使用 findContours 来查找每个形状的轮廓。然后您可以过滤轮廓并将您感兴趣的每个轮廓放入空白图像中。届时，您将收到信件并准备好使用 tesseract 进行处理。您可以在下面的代码中看到详细信息。

import cv2
import numpy as np
import pytesseract

# img = cv2.imread("dwLFQ.png", cv2.IMREAD_COLOR)
img = cv2.imread("NfwY4.png", cv2.IMREAD_COLOR)
# img = cv2.imread("xTH6s.png", cv2.IMREAD_COLOR)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

items = cv2.findContours(thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
contours = items[0] if len(items) == 2 else items[1]

base = np.zeros(thresh.shape, dtype=np.uint8)
base = cv2.bitwise_not(base)

max_area = 0
for i in range(len(contours)):
    x, y, w, h = cv2.boundingRect(contours[i])
    ratio = h / w
    area = cv2.contourArea(contours[i])
    cv2.drawContours(img, [contours[i]], 0, (255, 0, 0), 2)

    if 1 < ratio < 3:
        max_area = max(area, max_area)
        print("area: " + str(area) + ", max area: " + str(max_area) + ", ratio: " + str(ratio))
        # if 1000 < area < max_area / 2:
        if 1000 < area < 40000:
            mask = np.zeros(thresh.shape, dtype=np.uint8)
            cv2.drawContours(mask, [contours[i]], -1, color=255, thickness=-1)
            mean = cv2.mean(thresh, mask=mask)

            segment = np.zeros((h, w), dtype=np.uint8)
            segment[:h, :w] = thresh[y:y + h, x:x + w]

            if mean[0] > 150:
                # white, invert
                segment = cv2.bitwise_not(segment)

            base[y:y + h, x:x + w] = segment[:h, :w]
            cv2.imshow("base", base)

            cv2.drawContours(img, [contours[i]], 0, (255, 0, 0), 2)

            cv2.waitKey(0)

custom_config = r'-l eng --oem 3 --psm 6 -c tessedit_char_whitelist="ABCDEFGHIJKLMNOPQRSTUVWXYZ " '
text = pytesseract.image_to_string(base, config=custom_config)
print("detected: " + text)

cv2.imshow("img", img)
cv2.imshow("base", base)

cv2.waitKey(0)
cv2.destroyAllWindows()

结果

detected: NO
ENTRY