How to Quickly Extract Text from Images in Python Using ddddocr and OpenCV

This article walks through a Python OCR solution for a blank image output problem, demonstrates a working ddddocr code snippet, and suggests an alternative OpenCV preprocessing step, providing clear screenshots and concise explanations for effective image text extraction.

Python Crawling & Data Mining
Python Crawling & Data Mining
Python Crawling & Data Mining
How to Quickly Extract Text from Images in Python Using ddddocr and OpenCV

1. Introduction

A user posted a Python image‑processing issue where the OCR result was empty. The problematic screenshot is shown below:

The output image was blank:

2. Implementation

A working solution was provided using the ddddocr library:

import ddddocr
ocr = ddddocr.DdddOcr()
with open('1.png', 'rb') as f:
    img_bytes = f.read()
res = ocr.classification(img_bytes)
print(res)

The OCR result was accurate, as illustrated:

Another contributor suggested preprocessing the image with opencv for binarization, which can also improve results:

3. Conclusion

The article presents a concrete Python OCR solution for the reported issue, includes a complete code example, and offers an alternative OpenCV preprocessing approach, helping readers resolve similar image‑text extraction problems efficiently.

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Computer VisionImage ProcessingOCROpenCVddddocr
Python Crawling & Data Mining
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Python Crawling & Data Mining

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