How to differentiate the scanned PDF and native PDF in Python?
Because both the documents having the extension with PDF only.
Is it possible to find whether the document is scanned PDF or native PDF by its properties?
I'mnot sure about the propeties, but if you zoom the page and curves still remain smooth - it's a Native PDF, if become uneven - it's scanned, because scanned PDF is no more than an image and don't have code that allows them to be edited.
Related
I have a pdf document containing several images. I want to retrieve the names of these images.
I know that ExtractImages extracts images from PDF. I feel that this will somewhere have the functionality to fetch the name of the image.
How to achieve this using python
So I have these PDFs that are scanned copies of a structured feedback form. The form has these checkboxes and spaces for hand written notes. I am trying to extract the data from these PDFs and save it to an unstructured CSV file.
Now using pytesseract I am able to grab the printed text (by first converting the PDF to image) but I am not able to capture the handwritten content. Is there any of doing it.
I am enclosing a sample form for reference.
!https://imgur.com/a/2FYqWJf
PyTesseract is an OCR program. It has not been trained or designed to recognize handwriting. So you have two options: 1) Retrain it for handwriting (this would be quite time-consuming and complicated though) 2) Use another library actually meant for recognizing handwriting and not printed text like this one: https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/quickstarts/python-hand-text
I’m using the python library PyPDF2 to crop many PDF files to cut out the useless information on top and bottom of academic papers (i.e. page numbers and journal information at the bottom). Then I used the library textract to extract the texts from the cropped PDF files to txt files. However, the output txt files still contains the cropped out information despite the cropping.
This also applies to pdfminer, another text extraction library (not OCR). It seems that for text extraction, as opposed to OCR, the text cannot be eliminated by simply cropping. Can anyone explain why this is the case? Any idea on how else to eliminate useless information in PDF files for text extraction?
I need to find a tool (python, adobe suite, some cmd line utility, etc) that can extract images from a PDF as individual PDF files - not jpegs, pngs, etc.
Does such a thing exist? Seems like there is a bunch of stuff out there for extracting image files to png, jpeg, etc, but nothing for extracting the images as PDFs. A strange request I know.
I am working with a large set of PDFs that contain images that are comprised of all kinds of different images formats, bitmaps, vectors, etc. If there was some way to programmatically pull out images as pdfs it would save me a lot of time.
Right now I am selecting a portion of the page in the PDF in acrobat pro, choosing to edit in illustrator, and then saving as PDF.
Very time consuming.
Any ideas?
You could use poppler's pdfimages utility to extract all bitmap images as-is from a PDF. In a second step, you can convert these bitmaps back to PDFs. img2pdf seems like a good candidate for this.
I am using from google.appengine.api import conversion
To allow me to convert an HTML email into a PDF file. The code is below and it works.
However the width of the PDF document slices off the right hand side of my document.
Amy clues how to fix this
asset = conversion.Asset("text/html", message.html, "test.html")
conversion_obj = conversion.Conversion(asset, "application/pdf")
result = conversion.convert(conversion_obj)
if result.assets:
for asset in result.assets:
message.attachments=message.attachments+[(BnPresets.email_filename[0:BnPresets.email_filename.find('.')]+".pdf",asset.data)]
Unfortunately it looks like you cannot control the width (or dimensions) of converted PDF documents. Seems like you can only do this with .png images. Some extra conversion options:
The width of output images (*.png only)
A specific page or page range to output to an image (*.png only)
The language of source text for OCR operations (*.txt, *.html, and *.pdf only)
Note that one way around this could be to convert your html page to a png image (with the correct width), and then re-convert this png image to a pdf document. I wouldn't advise you to use this method because you would end up using two API calls per conversion, which gets expensive really quickly.
A better way would be to structure the dimensions of your input html page properly such that one-off conversions to PDF documents end up being pretty much identical.