(-215:断言失败)cv::imread函数'cv::cvtColor'中的!_src.Empty()

2022-03-27 00:00:00 python cv2 ocr tesseract python-tesseract

问题描述

我正在尝试从图像中识别文本,然后将文本输出; 但是,此错误显示为:

回溯(最近一次呼叫): 文件"C:/Users/Benji的Beast/AppData/Local/Programs/Python/Python37-32/imageDet.py",行41,位于 print(get_string(src_path+"cont.jpg")) 文件"C:/Users/Benji的Beast/AppData/Local/Programs/Python/Python37-32/imageDet.py",行15,在GET_STRING中 img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) cv2.error:函数‘cv::cvtColor’中的openCV(3.4.4)C:projectsopencv-pythonopencvmodulesimgprocsrccolor.cpp:181:错误:(-215:断言失败)!_src.Empty()

图像分辨率为1371x51。 我尝试将src_path上的"/"更改为"",但没有成功。 有什么想法吗?

以下是我的代码:

import cv2
import numpy as np
import pytesseract
from PIL import Image
from pytesseract import image_to_string

# Path of working folder on Disk
src_path = "C:/Users/Benji's Beast/Desktop/image.PNG"

def get_string(img_path):
    # Read image with opencv
    img = cv2.imread(img_path)

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

    # Apply dilation and erosion to remove some noise
    kernel = np.ones((1, 1), np.uint8)
    img = cv2.dilate(img, kernel, iterations=1)
    img = cv2.erode(img, kernel, iterations=1)

    # Write image after removed noise
    cv2.imwrite(src_path + "removed_noise.png", img)

    #  Apply threshold to get image with only black and white
    #img = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)

    # Write the image after apply opencv to do some ...
    cv2.imwrite(src_path + "thres.png", img)

    # Recognize text with tesseract for python
    result = pytesseract.image_to_string(Image.open(src_path + "thres.png"))

    # Remove template file
    #os.remove(temp)

    return result


print('--- Start recognize text from image ---')
print(get_string(src_path + "cont.jpg") )

print("------ Done -------")
我不知道如何解决这个问题, 谢谢。


解决方案

这表示您正在将未初始化的变量传递给

> cv2.cvtColor()

此语句后:

# Read image with opencv
img = cv2.imread(img_path)

您是否可以在传递给cv2.cvtColor()函数之前尝试打印img变量

> print(img) or print(img.shape)

确保读取图像的函数调用成功

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