Text = pytesseract.image_to_string(Image.open(filename)) # load the image as a PIL/Pillow image, apply OCR, and then delete
.jpg "pdf extract text from image")
We can enhance the accuracy of the output by fine tuning the parameters but the objective is to show text extraction. We currently perform this step for a single image, but this can be easily modified to loop over a set of images. # write the grayscale image to disk as a temporary file so we can To extract text from the image we can use the PIL and pytesseract libraries. # make a check to see if median blurring should be done to remove # check to see if we should apply thresholding to preprocess the Gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # load the image and convert it to grayscale
#Pdf extract text from image pdf
# if it is a pdf we convert it to an image # construct the argument parse and parse the argumentsĪp.add_argument("-i", "-image", required=True,Īp.add_argument("-p", "-preprocess", type=str, default="thresh", Pages = convert_from_path("document-page%s.pdf" % i, 500) I made an attempt with Tesseract OCR with Python, it extracts some pages of a pdf text but really takes time and seems to stop at a point : # import the necessary packages # Process each page contained in the document.Ĭan you help extract text from this kind of files ? Update with Tesseract OCR
Interpreter = PDFPageInterpreter(rsrcmgr, device) With open("document-page%s.pdf" % i, "wb") as outputStream:ĭevice = TextConverter(rsrcmgr, retstr, codec=codec, laparams=laparams) Inputpdf = PdfFileReader(open(filename, "rb")) I've tried to extract text from a pdf created from the computer and it worked but I wasn't able to extract text from a scanned pdf, which you can find here, with images and several pages such as this one :įrom PyPDF2 import PdfFileWriter, PdfFileReaderįrom pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreterįrom nverter import XMLConverter, HTMLConverter, TextConverter
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