The code you provided uses Tesseract OCR with a custom configuration (-l eng+equ) to recognize English and mathematical equations (equ) in the image. However, there is a small issue with the code – pytesseract.image_to_string() expects the image in PIL (Python Imaging Library) format, not OpenCV format (NumPy array).
To fix the issue, you can convert the image from OpenCV format to PIL format before passing it to Tesseract. You can use the PIL.Image.fromarray() function to perform this conversion.
Here's the updated code:
Make sure to replace "tessa.png" with the actual path to your image file.
With this code, Tesseract OCR will attempt to recognize both English text and mathematical equations present in the image. The custom_config parameter with the value -l eng+equ instructs Tesseract to use the English and mathematical equation language data for recognition.
Please note that while Tesseract is a powerful OCR engine, recognizing complex mathematical expressions accurately might be challenging. If you encounter issues with accuracy, consider using specialized OCR libraries or APIs that are designed specifically for math recognition.
source: Chat gpt