Image Text Extraction and Named Entity Recognition (NER) using Tesseract OCR and spaCy
🔍 *Extracting Text from Images and Performing Named Entity Recognition (NER) with Python*
GitHub Link: https://lnkd.in/gazFg69y
In a recent project, I explored the capabilities of Tesseract OCR and spaCy for text extraction and Named Entity Recognition (NER) from images. Here's a breakdown of the process:
1️⃣ **Image Text Extraction using Tesseract OCR**:
Tesseract OCR is a powerful tool for extracting text from images.
Using Python and OpenCV, we read the image (`news1.jpg`) and extract text from it.
2️⃣ **Saving Extracted Text to Document**:
The extracted text is then saved to a Word document using `python-docx`.
3️⃣ **Named Entity Recognition (NER) using spaCy**:
We leverage spaCy for NER to identify entities like organizations, dates, and locations within the extracted text.
ℹ️ **Why it Matters**:
This workflow showcases practical applications of OCR and NLP techniques.
It's useful for automating text extraction tasks and extracting valuable insights from documents.
🚀 **Key Takeaway**:
By combining Tesseract OCR and spaCy's NLP capabilities, we can unlock powerful text-processing functionalities for various applications including document analysis, data extraction, and more.
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