将带有文本(和图片)的图像文件分割成块 [英] Segmenting image files with text (and pictures) into blocks

问题描述

我正在尝试为图像中的文本创建边界框.下面是一个示例.

I'm trying to create bounding boxes for the text in an image I have. An example is the one below.

我想在每条This is a test行周围添加一个边框.不幸的是，我不确定为什么这种方法不能自动识别边界框

I would like to add a bounding box around each This is a test line. Unfortunately I'm not sure why this method is not automatically identifying the bounding boxes

import re
import cv2
import numpy as np
import pytesseract
from pytesseract import Output
from matplotlib import pyplot as plt


# Plot character boxes on image using pytesseract.image_to_boxes() function
image = cv2.imread('Image.jpg')
b, g, r = cv2.split(image)
image = cv2.merge([r,g,b])
d = pytesseract.image_to_data(image, output_type=Output.DICT)
print('DATA KEYS: \n', d.keys())

n_boxes = len(d['text'])
for i in range(n_boxes):
    # condition to only pick boxes with a confidence > 60%
    if int(d['conf'][i]) > 60:
        (x, y, w, h) = (d['left'][i], d['top'][i], d['width'][i], d['height'][i])
        image = cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)

b, g, r = cv2.split(image)
rgb_img = cv2.merge([r, g, b])
plt.figure(figsize=(16, 12))
plt.imshow(rgb_img)
plt.title('SAMPLE IMAGE WITH WORD LEVEL BOXES')
plt.show()

推荐答案

这是使用Python/OpenCV进行此操作的另一种方法.

Here is a different way to do that with Python/OpenCV.

• 阅读输入内容
• 转换为灰色
• (OTSU)阈值(黑色背景上的白色文本)
• 应用形态学时，水平核的扩展要长于字母间距，然后应用较小的垂直核，以去除页面中行中剩余的细水平线.
• 找到轮廓
• 在输入上绘制轮廓的边界框
• 保存结果

输入:

import cv2
import numpy as np

# load image
img = cv2.imread("test_text.jpg")

# convert to gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# threshold the grayscale image
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# use morphology erode to blur horizontally
#kernel = np.ones((500,3), np.uint8)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (250, 3))
morph = cv2.morphologyEx(thresh, cv2.MORPH_DILATE, kernel)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 17))
morph = cv2.morphologyEx(morph, cv2.MORPH_OPEN, kernel)

# find contours
cntrs = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cntrs = cntrs[0] if len(cntrs) == 2 else cntrs[1]

# Draw contours
result = img.copy()
for c in cntrs:
    x,y,w,h = cv2.boundingRect(c)
    cv2.rectangle(result, (x, y), (x+w, y+h), (0, 0, 255), 2)

# write result to disk
cv2.imwrite("test_text_threshold.png", thresh)
cv2.imwrite("test_text_morph.png", morph)
cv2.imwrite("test_text_lines.jpg", result)

cv2.imshow("GRAY", gray)
cv2.imshow("THRESH", thresh)
cv2.imshow("MORPH", morph)
cv2.imshow("RESULT", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

阈值图像:

Thresholded image:

放大的图像:

结果:

这篇关于将带有文本(和图片)的图像文件分割成块的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！