python - 从图像中删除颜色

Question

我想从下面的图像中删除颜色，由于这种颜色，我无法从图像中清楚地提取文本。



我正在使用下面的代码，但我没有得到明文，

import numpy as np
from PIL import Image

im = Image.open('my_file.tif')
im = im.convert('RGBA')
data = np.array(im)
# just use the rgb values for comparison
rgb = data[:,:,:3]
color = [246, 213, 139]   # Original value
black = [0,0,0, 255]
white = [255,255,255,255]
mask = np.all(rgb == color, axis = -1)
# change all pixels that match color to white
data[mask] = white

# change all pixels that don't match color to black
##data[np.logical_not(mask)] = black
new_im = Image.fromarray(data)
new_im.save('new_file.tif')

和

def black_and_white(input_image_path,
                output_image_path):
color_image = Image.open(input_image_path)
bw = color_image.convert('L')
bw.save(output_image_path)

请在这件事上给予我帮助...

图 2:

Answer 1

我假设你想提取报价。为此，您可以进行一系列过滤操作以去除非文本轮廓。获得处理结果后，您可以使用 Pytesseract 等 OCR 工具进行文本提取。



OCR 的结果

On behalf of the hundreds of ACLU activists who
called on Governor Walker to veto House Bill
156, we are disappointed that he did not put
students or the Constitution first today.”
—Joshua A. Decker
Executive Director

代码

import cv2
import pytesseract

pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"

# Load image and threshold
image = cv2.imread('1.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

# Connect text with a horizontal shaped kernel
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (10,3))
dilate = cv2.dilate(thresh, kernel, iterations=3)

# Remove non-text contours using aspect ratio filtering
cnts = cv2.findContours(dilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    x,y,w,h = cv2.boundingRect(c)
    aspect = w/h
    if aspect < 3:
        cv2.drawContours(thresh, [c], -1, (0,0,0), -1)

# Invert image and OCR
result = 255 - thresh
data = pytesseract.image_to_string(result, lang='eng',config='--psm 6')
print(data)

cv2.imshow('result', result)
cv2.waitKey()