Extract images from Excel file with python

Question

I have an Excel sheet with 100 rows. Each one has various informations, including an id, and a cell containing a photo.

I use pandas to load the data into dictionaries :

import pandas as pd

df = pd.read_excel('myfile.xlsx')

data = []

for index,row in df.iterrows():
    data.append({
        'id':row['id'],
        'field2':row['field2'],
        'field3':row['field3']
    })

For the image column, I want to extract each image, name it with the id of the row (image_row['id'].jpg) and put it into a folder. Then, I want to store the path to the image as below :

for index,row in df.iterrows():
        data.append({
            'id':row['id'],
            'field2':row['field2'],
            'field3':row['field3'],
            'image':'path/image_'+row['id']+'.jpg'
        })

I'm looking for a way to do that, or another way if better. Do you have any idea ?

I'm on Linux, so I can't use this method with pywin32.

Thanks a lot

-- EDIT

You can find here an exemple of sheet i use

Answer 1

def extract_images_from_excel(path, dir_extract=None):
    """extracts images from excel and names then with enumerated filename
    
    Args:
        path: pathlib.Path, excel filepath
        dir_extract: pathlib.Path, default=None, defaults to same dir as excel file
    
    Returns:
        new_paths: list[pathlib.Path], list of paths to the extracted images
    """
    if type(path) is str:
        path = pathlib.Path(path)
    if dir_extract is None:
        dir_extract = path.parent
    if path.suffix != '.xlsx':
        raise ValueError('path must be an xlsx file')
    name = path.name.replace(''.join(path.suffixes), '').replace(' ', '') # name of excel file without suffixes
    temp_file = pathlib.Path(source_file).parent / 'temp.xlsx' # temp xlsx
    temp_zip = temp_file.with_suffix('.zip') # temp zip
    shutil.copyfile(source_file, temp_file)
    temp_file.rename(str(temp_zip))
    extract_dir =  temp_file.parent / 'temp'
    extract_dir.mkdir(exist_ok=True)
    shutil.unpack_archive(temp_zip, extract_dir) # unzip xlsx zip file
    paths_img = sorted((extract_dir / 'xl' / 'media').glob('*.png')) # find images
    move_paths = {path: destination_dir / (name + f'-{str(n)}.png') for n, path in enumerate(paths_img)} # create move path dict 
    new_paths = [shutil.move(old, new) for old, new in move_paths.items()] # move / rename image files
    shutil.rmtree(extract_dir) # delete temp folder
    temp_zip.unlink() # delete temp file
    return new_paths

the above ^ does the following:

• copies the excel file
• unzips
• extracts images from the excel into a temp folder
• moves the images and renames them
• deletes temp folders and files

doesn't require 3rd party packages and doesn't need windows to run

Answer 2

You can unzip the renamed xlsx zip file.

$ cp a.xlsx a.zip

$ unzip a.zip

$ ls -al xl/media

Answer 3

I found a solution using openpyxl and openpyxl-image-loader modules

# installing the modules
pip3 install openpyxl
pip3 install openpyxl-image-loader

Then, in the script :

#Importing the modules
import openpyxl
from openpyxl_image_loader import SheetImageLoader

#loading the Excel File and the sheet
pxl_doc = openpyxl.load_workbook('myfile.xlsx')
sheet = pxl_doc['Sheet_name']

#calling the image_loader
image_loader = SheetImageLoader(sheet)

#get the image (put the cell you need instead of 'A1')
image = image_loader.get('A1')

#showing the image
image.show()

#saving the image
image.save('my_path/image_name.jpg')

In the end, I can store the path and the image name in my dictionaries in a loop for each row

Answer 4

There may be far better solutions, but I thought I would share what I know in case that is good enough.

---

An Excel .xlsx file is a actually a zip-file. So you can read it with 7z and probably also with Python Zipfile. Just demonstrating in Terminal:

# List contents
7z l a.xlsx

7-Zip [64] 16.02 : Copyright (c) 1999-2016 Igor Pavlov : 2016-05-21
p7zip Version 16.02 (locale=utf8,Utf16=on,HugeFiles=on,64 bits,12 CPUs x64)

Scanning the drive for archives:
1 file, 596240 bytes (583 KiB)

Listing archive: a.xlsx

--
Path = a.xlsx
Type = zip
Physical Size = 596240

   Date      Time    Attr         Size   Compressed  Name
------------------- ----- ------------ ------------  ------------------------
2020-05-27 02:36:54 .....         2371          563  xl/drawings/drawing1.xml
2020-05-27 02:36:54 .....          561          198  xl/drawings/_rels/drawing1.xml.rels
2020-05-27 02:36:54 .....         1781          565  xl/worksheets/sheet1.xml
2020-05-27 02:36:54 .....          298          179  xl/worksheets/_rels/sheet1.xml.rels
2020-05-27 02:36:54 .....         3757          808  xl/theme/theme1.xml
2020-05-27 02:36:54 .....          427          204  xl/sharedStrings.xml
2020-05-27 02:36:54 .....         2523          613  xl/styles.xml
2020-05-27 02:36:54 .....          809          330  xl/workbook.xml
2020-05-27 02:36:54 .....          697          234  xl/_rels/workbook.xml.rels
2020-05-27 02:36:54 .....          296          178  _rels/.rels
2020-05-27 02:36:54 .....       156683       156657  xl/media/image2.png
2020-05-27 02:36:54 .....        46848        46853  xl/media/image1.png
2020-05-27 02:36:54 .....       386512       386632  xl/media/image3.png
2020-05-27 02:36:54 .....         1099          320  [Content_Types].xml
------------------- ----- ------------ ------------  ------------------------
2020-05-27 02:36:54             604662       594334  14 files

You can then extract the files and look at the images with:

7z x a.xlsx

---

Another option might be to save the Excel file as a PDF, you can then run pdfimages from the Poppler package and extract the images:

pdfimages -png YourSpreadsheet.pdf extracted

Sample Output

-rw-r--r--@ 1 mark  staff   92973 27 May 10:57 extracted-000.png
-rw-r--r--@ 1 mark  staff   28074 27 May 10:57 extracted-001.png
-rw-r--r--@ 1 mark  staff     189 27 May 10:57 extracted-002.png
-rw-r--r--@ 1 mark  staff  244898 27 May 10:57 extracted-003.png