How can i extract images/logo from word document using python and store them in a folder. Following code converts docx to html but it doesn't extract images from the html. Any pointer/suggestion will be of great help.
profile_path = <file path>
result=mammoth.convert_to_html( profile_path)
f = open(profile_path, 'rb')
b = open(profile_html, 'wb')
document = mammoth.convert_to_html(f)
b.write(document.value.encode('utf8'))
f.close()
b.close()
You can use the docx2txt library, it will read your .docx document and export images to a directory you specify (must exist).
!pip install docx2txt
import docx2txt
text = docx2txt.process("/path/your_word_doc.docx", '/home/example/img/')
After execution you will have the images in /home/example/img/ and the variable text will have the document text. They would be named image1.png ... imageN.png in order of appearance.
Note: Word document must be in .docx format.
Extract all the images in a docx file using python
1. Using docxtxt
import docx2txt
#extract text
text = docx2txt.process(r"filepath_of_docx")
#extract text and write images in Temporary Image directory
text = docx2txt.process(r"filepath_of_docx",r"Temporary_Image_Directory")
2. Using aspose
import aspose.words as aw
# load the Word document
doc = aw.Document(r"filepath")
# retrieve all shapes
shapes = doc.get_child_nodes(aw.NodeType.SHAPE, True)
imageIndex = 0
# loop through shapes
for shape in shapes :
shape = shape.as_shape()
if (shape.has_image) :
# set image file's name
imageFileName = f"Image.ExportImages.{imageIndex}_{aw.FileFormatUtil.image_type_to_extension(shape.image_data.image_type)}"
# save image
shape.image_data.save(imageFileName)
imageIndex += 1
Native without any lib
To extract the source Images from the docx (which is a variation on a zip file) without distortion or conversion.
shell out to OS and run
tar -m -xf DocxWithImages.docx word/media
You will find the source images Jpeg, PNG WMF or others in the word media folder extracted into a folder of that name. These are the unadulterated source embedment's without scale or crop.
You may be surprised that the visible area may be larger then any cropped version used in the docx itself, and thus need to be aware that Word does not always crop images as expected (A source of embarrassing redaction failure)
Look the Alderven's answer at Extract all the images in a docx file using python
The zipfile works for more image formats than the docx2txt. For example, EMF images are not extracted by docx2txt but can be extracted by zipfile.
Related
I have this piece of code in Python that makes use of pytesseract (method pytesseract.image_to_data).
This gives me great text information and coordinates that are saved in a text file that is fed to a third party software. It works perfectly for PDF files that have been scanned
data = pytesseract.image_to_data(Image.open('file-001-page-001.png')))
The issue now is that I have a demand for output in the exact same structure for PDFs that already contain text. It's possible to keep the same code and continue as if the PDF had no text, extracting images and doing OCR, but it doesn't seem like the right solution...
Is it possible to achieve this with pytesseract?
Suggestions are welcome
You can use this:
import pytesseract
from PIL import Image
# Open the PDF file
with open('file.pdf', 'rb') as f:
# Extract text from the PDF file and save it to a variable
text = pytesseract.image_to_pdf_or_hocr(f, extension='hocr', lang='eng', config='--oem 3 --psm 6')
# Save the extracted text to a file in the desired format
with open('output.hocr', 'w')as f:
f.write(text)
I need to convert lots of jpg/png files to docx files & then to pdf. My sole concern is to write the data in an image to a pdf file & if I need to edit any text manually, I can do that in word & save it in the corresponding pdf file.
I've tried using API but failed as the text is not correctly matching.
My image files contain only texts & not anything else.
I already have docx to pdf conversion code in Python.
from docx2pdf import convert
input = 'INPUT_FILE_NAME.docx'
output = 'OUTPUT_FILE_NAME.pdf'
convert(input)
convert(input, output)
convert("Output")
Kindly suggest me how to convert a png/jpg file to docx. Thanks.
EDIT --------------
I've successfully made this code run. I've uploaded in my github repo.
from PIL import Image
from pytesseract import pytesseract
#Define path to tessaract.exe
path_to_tesseract = r'C:\Program Files\Tesseract-OCR\tesseract.exe'
#Define path to image
path_to_image = 'texttoimage.png'
#Point tessaract_cmd to tessaract.exe
pytesseract.tesseract_cmd = path_to_tesseract
#Open image with PIL
img = Image.open(path_to_image)
#Extract text from image
text = pytesseract.image_to_string(img)
print(text)
I have several powerpoints that I need to shuffle through programmatically and extract images from. The images then need to be converted into OpenCV format for later processing/analysis. I have done this successfully for images in the pptx, using:
for slide in presentation:
for shape in slide.shapes
if 'Picture' in shape.name:
pic_list.append(shape)
for extraction, and:
img = cv2.imdecode(np.frombuffer(page[i].image.blob, np.uint8), cv2.IMREAD_COLOR)
for python-pptx Picture to OpenCV conversion. However, I am having a lot of trouble extracting and manipulating the backgrounds in a similar fashion.
slide.background
is sufficient to extract a "_Background" object, but I have not found a good way to convert it into a OpenCV object similar to Pictures. Does anyone know how to do this? I am using python-pptx for extraction, but am not adverse to other packages if it's not possible with that package.
After a fair bit of work I discovered how to do this -- i.e., you don't. As far as I can tell, there is no way to directly extract the backgrounds with either python-pptx or Aspose. Powerpoint -- which, as it turns out, is an archive that can be unzipped with 7zip -- keeps its backgrounds disassembled in the ppt/media (pics), ppt/slideLayouts and ppt/slideMasters (text, formatting), and they are only put together by the Powerpoint renderer. This means that to extract the backgrounds as displayed, you basically need to run Powerpoint and take pics of the slides after removing text/pictures/etc. from the foreground.
I did not need to do this, as I just needed to extract text from the backgrounds. This can be done by checking slideLayouts and slideMasters XMLs using BeautifulSoup, at the <a:t> tag. The code to do this is pretty simple:
import zipfile
with zipfile.ZipFile(pptx_path, 'r') as zip_ref:
zip_ref.extractall(extraction_directory)
This will extract the .pptx into its component files.
from glob import glob
layouts = glob(os.path.join(extr_dir, 'ppt\slideLayouts\*.xml'))
masters = glob(os.path.join(extr_dir, 'ppt\slideMasters\*.xml'))
files = layouts + masters
This gets you the paths for slide layouts/masters.
from bs4 import BeautifulSoup
text_list = []
for file in files:
with open(file) as f:
data = f.read()
bs_data = BeautifulSoup(data, "xml")
bs_a_t = bs_data.find_all('a:t')
for a_t in bs_a_t:
text_list.append(str(a_t.contents[0]))
This will get you the actual text from the XMLs.
Hopefully this will be useful to someone else in the future.
I want to extract text from the PDF files but the layout of text in the PDF should be maintained, like the images below. Images show results from the [github.com/JonathanLink/PDFLayoutTextStripper].
I tried the below code but it doesn't maintain the Layout. I want get results exactly the same way as shown in the images by using any of the Python libraries like PyPDF2, PDFPlumber, PDFminer etc. I tried all these libraries but didn't get the desired results. I need help in extracting the text from the PDF file exactly as is shown in the images.
from pdfminer.high_level import extract_text`
text = extract_text('test.pdf')
print(text)
You can preserve layout/indentation using PDFtotext package.
import pdftotext
with open("target_file.pdf", "rb") as f:
pdf = pdftotext.PDF(f)
# All pages
for text in pdf:
print(text)
Context:
I have PDF files I'm working with.
I'm using an ocr to extract the text from these documents and to be able to do that I have to convert my pdf files to images.
I currently use the convert_from_path function of the pdf2image module but it is very time inefficient (9minutes for a 9page pdf).
Problem:
I am looking for a way to accelerate this process or another way to convert my PDF files to images.
Additional info:
I am aware that there is a thread_count parameter in the function but after several tries it doesn't seem to make any difference.
This is the whole function I am using:
def pdftoimg(fic,output_folder):
# Store all the pages of the PDF in a variable
pages = convert_from_path(fic, dpi=500,output_folder=output_folder,thread_count=9, poppler_path=r'C:\Users\Vincent\Documents\PDF\poppler-21.02.0\Library\bin')
image_counter = 0
# Iterate through all the pages stored above
for page in pages:
filename = "page_"+str(image_counter)+".jpg"
page.save(output_folder+filename, 'JPEG')
image_counter = image_counter + 1
for i in os.listdir(output_folder):
if i.endswith('.ppm'):
os.remove(output_folder+i)
Link to the convert_from_path reference.
I found an answer to that problem using another module called fitz which is a python binding to MuPDF.
First of all install PyMuPDF:
The documentation can be found here but for windows users it's rather simple:
pip install PyMuPDF
Then import the fitz module:
import fitz
print(fitz.__doc__)
>>>PyMuPDF 1.18.13: Python bindings for the MuPDF 1.18.0 library.
>>>Version date: 2021-05-05 06:32:22.
>>>Built for Python 3.7 on win32 (64-bit).
Open your file and save every page as images:
The get_pixmap() method accepts different parameters that allows you to control the image (variation,resolution,color...) so I suggest that you red the documentation here.
def convert_pdf_to_image(fic):
#open your file
doc = fitz.open(fic)
#iterate through the pages of the document and create a RGB image of the page
for page in doc:
pix = page.get_pixmap()
pix.save("page-%i.png" % page.number)
Hope this helps anyone else.