This may be a little memory intensive, but I want to avoid having to write many images. If you had a recognition rate of 99 for all characters, you'll be lucky. ![]() Caveats, most of OCR works far from perfectly. Ocr_dataframe = pytesseract.image_to_data( After all, running an OCR over an image-only PDF aims to add 'searchable' text: Install pdftotext (available for Linux, Unix, Windows, Mac OS X) and then try running: pdftotext -layout some-input.pdf some-input.txt. Tesseract_image = ocr_preprocess(self.image) # Preprocess image in prep for pytesseract ocr Self.image = cv2.imread(temp_image_path, cv2.IMREAD_GRAYSCALE) Self.image_path = pathlib.Path(temp_image_path) Here is what the instance initialization looks like: def _init_(self, temp_image_path): Instead, I created a class that could hold the original image and the ocr output dataframe at the same time. The output is just rows and columns of text data. Nowhere in that data structure is the original image. Okay, so I am pretty sure that this was an impossible task I was trying to complete.īy nature produces a pandas dataframe. SmartDocumentor is an all-in-one data extraction solution that frees workers from the burden of analyzing and processing endless stacks of paper, PDFs. ![]() Is it possible to combine the output from pytesseract.image_to_data() with the original image and create some kind of bytes representation? However, I would like to avoid ocr'ing my pdfs twice. Pdf = pytesseract.image_to_pdf_or_hocr('test.png', extension='pdf') I am aware that I can use pytesseract to convert my original pdf to a searchable one (in bytes representation) using the following method: # Get a searchable PDF However, pdfplumber must be fed using one of three inputs: Now, I want to extract some tabular data from the pdf using pdfplumber. I requested that using this method: ocr_dataframe = pytesseract.image_to_data( Is it possible to write to a pdf file retroactively using pytesseract.image_to_data() output?įor my OCR pipeline, I needed granular access to my pdf's ocr'ed data.
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