Develop Reference

PIL image shows OK but saves black

Using PIL Image to binarize an image to optimize OCR shows good results on-screen but saves all black PNG. And when passing the image object to process with pytesseract it also returns no text...
Note: I don't really need to save the processed image as long as the OCR works.
basepath = 'img_bin/'
image_list = os.listdir(basepath)
for file in image_list:
if os.path.isfile(os.path.join(basepath, file)):
print(file)
img = Image.open(basepath+file).convert("L")
img = ImageOps.invert(img)
threshold = 20
table = []
pixelArray = img.load()
for y in range(img.size[1]): # binaryzate it
List = []
for x in range(img.size[0]):
if pixelArray[x,y] > threshold:
List.append(0)
else:
List.append(255)
table.append(List)
img = Image.fromarray(np.array(table))
img.show()
img.save(basepath+'processed.png')
img_lines = pytesseract.image_to_string(img)
print(len(img_lines))
print(img_lines)
OUTPUTS:
print(len(img_lines)) -> 1
print(img_lines) -> <0x0c>
img.show():
saved 'processed.png'

You need to convert the image mode to RGB:
if img.mode != 'RGB':
img = img.convert('RGB')
img.save(basepath+'processed.png')
That's because the save method assumes RGB mode.

Get all images in a PDF page from diferent PDF files

I want to download all images from the last page on diferent pdf files.
With the follow code i'm getting only the first image on that page.
for filename in os.listdir(directory):
if filename.endswith(".pdf"):
path = os.path.join(directory,filename)
doc = fitz.open(path)
for i in range(len(doc)-1,len(doc)):
for img in doc.getPageImageList(i):
xref = img[0]
pix = fitz.Pixmap(doc, xref)
if pix.n < 5: # this is GRAY or RGB
pix.writePNG("%s-%s-%s.png" % (i, xref, filename))
else: # CMYK: convert to RGB first
pix1 = fitz.Pixmap(fitz.csRGB, pix)
pix1.writePNG("%s-%s-%s.png" % (i, xref,filename))
pix1 = None
pix = None
else:

new in python. I want to apply an algorithm to different images from a folder and save the new ones in another folder. Biology research images

I want to inverse colors in a black and white image and then change the background in transparent, with the following codes:
imgg = Image.open('HSPl4_E5_LP8.png')
data = np.array(imgg)
converted = np.where(data == 255, 0, 255)
imgg = Image.fromarray(converted.astype('uint8'))
imgg.save('new HSPl4_E5_LP8.png')
and
from PIL import Image
img = Image.open('new HSPl4_E5_LP8.png')
img = img.convert("RGBA")
datas = img.getdata()
newData = []
for item in datas:
if item[0] == 255 and item[1] == 255 and item[2] == 255:
newData.append((255, 255, 255, 0))#0 és la alfa de rgba i significa 0 opacity.
else:
newData.append(item)
img.putdata(newData)
img.save("HSPl4_E5_LP8 transparent.png", "PNG")
Then I would like to iterate this in a several number of images that are in a folder. Then I would like to save the new images with the changes in another folder. But I do not find a way to make it work.

Not sure I understand your question properly but I think you can do the following.
First you bundle both operations into one function:
from PIL import Image
def imageTransform(imgfile,destfolder):
img = Image.open(imgfile)
data = np.array(img)
converted = np.where(data == 255, 0, 255)
img = Image.fromarray(converted.astype('uint8'))
img = img.convert("RGBA")
datas = img.getdata()
newData = []
for item in datas:
if item[0] == 255 and item[1] == 255 and item[2] == 255:
newData.append((255, 255, 255, 0))
else:
newData.append(item)
img.putdata(newData)
img.save(destfolder+"/"+imgfile, "PNG")
This function will open an image, apply the changes you mentioned and then save it in the specified path. You can then make this process automatic by using the following code:
import os
originalfolder = "folderpath" #place your folder path as string
destfolder = "folderpath" #place your destination path as string
directory = os.fsencode(originalfolder)
for file in os.listdir(directory):
filename = os.fsdecode(file)
imageTransform(file, destfolder)
"originalfolder" is the folder where your original images are. The format should be something like "C:/Users/yourfolder"
"desfolder" is the folder where the new images will be stored. The format should be something like "C:/Users/yournewfolder"

You can use pathlib for this, assuming apply_algo is a function that takes input a path object for input image and returns transformed PIL.Image object this should work.
from pathlib import Path
def process_files(source: str, dstn: str):
dstn = Path(dstn)
source = Path(source)
# check if input strings are directories or not.
if not (source.is_dir() and dstn.is_dir()):
raise Exception("Source and Dstn must be directories")
# use rglob if you want to pick files from subdirectories as well
for path in source.glob("*"):
if path.is_file():
output_img = apply_algo(path)
output_img.save(dstn / path.name(), "PNG")

Python library for image extraction

Yes I hate myself for asking a pretty simple question.
I was hoping to get some advice for the best python library to extract images (of varying type) from a PDF.
I'm trying to take a PDF Drawing, save an image and it's position on the PDF from it, then place the saved image at the right position on a set of other PDFs.
I have tried afew to date but got stuck by various errors and the research I've done indicates there is no clear and obvious choice.
I have tried PyPDF2 but got an error around PNG filter 3 being unsupported.
I have tried PDFMiner but it's constrained to JPEGs which while isn't a deal breaker I still can't get it to extract a JPEG.
I have also tried fitz module from PyMuPDF and got 1 of 3 images on my PDF, however it was inverted colour, backwards, upside down. Though I'm sure there is post-processing for this
The code I have used, to be honest, is examples that people far smarter than me have come up with and I have modified them as necessary.
Fitz below
doc = fitz.open(pdf)
for i in range(len(doc)):
for img in doc.getPageImageList(i):
xref = img[0]
pix = fitz.Pixmap(doc, xref)
if pix.n < 5: # this is GRAY or RGB
pix.writePNG("p%s-%s.png" % (i, xref))
else: # CMYK: convert to RGB first
pix1 = fitz.Pixmap(fitz.csRGB, pix)
pix1.writePNG("p%s-%s.png" % (i, xref))
pix1 = None
pix = None
PyPDF2 below
if __name__ == '__main__':
input1 = PyPDF2.PdfFileReader(pdf)
page0 = input1.getPage(0)
if '/XObject' in page0['/Resources']:
xObject = page0['/Resources']['/XObject'].getObject()
for obj in xObject:
if xObject[obj]['/Subtype'] == '/Image':
size = (xObject[obj]['/Width'], xObject[obj]['/Height'])
data = xObject[obj].getData()
if xObject[obj]['/ColorSpace'] == '/DeviceRGB':
mode = "RGB"
else:
mode = "P"
if '/Filter' in xObject[obj]:
if xObject[obj]['/Filter'] == '/FlateDecode':
img = Image.frombytes(mode, size, data)
img.save(obj[1:] + ".png")
elif xObject[obj]['/Filter'] == '/DCTDecode':
img = open(obj[1:] + ".jpg", "wb")
img.write(data)
img.close()
elif xObject[obj]['/Filter'] == '/JPXDecode':
img = open(obj[1:] + ".jp2", "wb")
img.write(data)
img.close()
elif xObject[obj]['/Filter'] == '/CCITTFaxDecode':
img = open(obj[1:] + ".tiff", "wb")
img.write(data)
img.close()
else:
img = Image.frombytes(mode, size, data)
img.save(obj[1:] + ".png")
If you're reading this and you wrote either of the above, thanks for getting me this far haha. The
More looking for advice on what is the best library to proceed with rather than someone hold my hand with the code.
Appreciate any imparting of wisdom
Pete

PyPDF2 can (now) do this. Straight from the docs:
from PyPDF2 import PdfReader
reader = PdfReader("example.pdf")
page = reader.pages[0]
count = 0
for image_file_object in page.images:
with open(str(count) + image_file_object.name, "wb") as fp:
fp.write(image_file_object.data)
count += 1

Extract images from PDF without resampling, in python?

How might one extract all images from a pdf document, at native resolution and format? (Meaning extract tiff as tiff, jpeg as jpeg, etc. and without resampling). Layout is unimportant, I don't care were the source image is located on the page.
I'm using python 2.7 but can use 3.x if required.

You can use the module PyMuPDF. This outputs all images as .png files, but worked out of the box and is fast.
import fitz
doc = fitz.open("file.pdf")
for i in range(len(doc)):
for img in doc.getPageImageList(i):
xref = img[0]
pix = fitz.Pixmap(doc, xref)
if pix.n < 5: # this is GRAY or RGB
pix.writePNG("p%s-%s.png" % (i, xref))
else: # CMYK: convert to RGB first
pix1 = fitz.Pixmap(fitz.csRGB, pix)
pix1.writePNG("p%s-%s.png" % (i, xref))
pix1 = None
pix = None
see here for more resources
Here is a modified the version for fitz 1.19.6:
import os
import fitz # pip install --upgrade pip; pip install --upgrade pymupdf
from tqdm import tqdm # pip install tqdm
workdir = "your_folder"
for each_path in os.listdir(workdir):
if ".pdf" in each_path:
doc = fitz.Document((os.path.join(workdir, each_path)))
for i in tqdm(range(len(doc)), desc="pages"):
for img in tqdm(doc.get_page_images(i), desc="page_images"):
xref = img[0]
image = doc.extract_image(xref)
pix = fitz.Pixmap(doc, xref)
pix.save(os.path.join(workdir, "%s_p%s-%s.png" % (each_path[:-4], i, xref)))
print("Done!")

In Python with PyPDF2 and Pillow libraries it is simple:
PyPDF2>=2.10.0
from PyPDF2 import PdfReader
reader = PdfReader("example.pdf")
for page in reader.pages:
for image in page.images:
with open(image.name, "wb") as fp:
fp.write(image.data)
PyPDF2<2.10.0
from PIL import Image
from PyPDF2 import PdfReader
def extract_image(pdf_file_path):
reader = PdfReader(pdf_file_path)
page = reader.pages[0]
x_object = page["/Resources"]["/XObject"].getObject()
for obj in x_object:
if x_object[obj]["/Subtype"] == "/Image":
size = (x_object[obj]["/Width"], x_object[obj]["/Height"])
data = x_object[obj].getData()
if x_object[obj]["/ColorSpace"] == "/DeviceRGB":
mode = "RGB"
else:
mode = "P"
if x_object[obj]["/Filter"] == "/FlateDecode":
img = Image.frombytes(mode, size, data)
img.save(obj[1:] + ".png")
elif x_object[obj]["/Filter"] == "/DCTDecode":
img = open(obj[1:] + ".jpg", "wb")
img.write(data)
img.close()
elif x_object[obj]["/Filter"] == "/JPXDecode":
img = open(obj[1:] + ".jp2", "wb")
img.write(data)
img.close()

Often in a PDF, the image is simply stored as-is. For example, a PDF with a jpg inserted will have a range of bytes somewhere in the middle that when extracted is a valid jpg file. You can use this to very simply extract byte ranges from the PDF. I wrote about this some time ago, with sample code: Extracting JPGs from PDFs.

In Python with PyPDF2 for CCITTFaxDecode filter:
import PyPDF2
import struct
"""
Links:
PDF format: http://www.adobe.com/content/dam/Adobe/en/devnet/acrobat/pdfs/pdf_reference_1-7.pdf
CCITT Group 4: https://www.itu.int/rec/dologin_pub.asp?lang=e&id=T-REC-T.6-198811-I!!PDF-E&type=items
Extract images from pdf: http://stackoverflow.com/questions/2693820/extract-images-from-pdf-without-resampling-in-python
Extract images coded with CCITTFaxDecode in .net: http://stackoverflow.com/questions/2641770/extracting-image-from-pdf-with-ccittfaxdecode-filter
TIFF format and tags: http://www.awaresystems.be/imaging/tiff/faq.html
"""
def tiff_header_for_CCITT(width, height, img_size, CCITT_group=4):
tiff_header_struct = '<' + '2s' + 'h' + 'l' + 'h' + 'hhll' * 8 + 'h'
return struct.pack(tiff_header_struct,
b'II', # Byte order indication: Little indian
42, # Version number (always 42)
8, # Offset to first IFD
8, # Number of tags in IFD
256, 4, 1, width, # ImageWidth, LONG, 1, width
257, 4, 1, height, # ImageLength, LONG, 1, lenght
258, 3, 1, 1, # BitsPerSample, SHORT, 1, 1
259, 3, 1, CCITT_group, # Compression, SHORT, 1, 4 = CCITT Group 4 fax encoding
262, 3, 1, 0, # Threshholding, SHORT, 1, 0 = WhiteIsZero
273, 4, 1, struct.calcsize(tiff_header_struct), # StripOffsets, LONG, 1, len of header
278, 4, 1, height, # RowsPerStrip, LONG, 1, lenght
279, 4, 1, img_size, # StripByteCounts, LONG, 1, size of image
0 # last IFD
)
pdf_filename = 'scan.pdf'
pdf_file = open(pdf_filename, 'rb')
cond_scan_reader = PyPDF2.PdfFileReader(pdf_file)
for i in range(0, cond_scan_reader.getNumPages()):
page = cond_scan_reader.getPage(i)
xObject = page['/Resources']['/XObject'].getObject()
for obj in xObject:
if xObject[obj]['/Subtype'] == '/Image':
"""
The CCITTFaxDecode filter decodes image data that has been encoded using
either Group 3 or Group 4 CCITT facsimile (fax) encoding. CCITT encoding is
designed to achieve efficient compression of monochrome (1 bit per pixel) image
data at relatively low resolutions, and so is useful only for bitmap image data, not
for color images, grayscale images, or general data.
K < 0 --- Pure two-dimensional encoding (Group 4)
K = 0 --- Pure one-dimensional encoding (Group 3, 1-D)
K > 0 --- Mixed one- and two-dimensional encoding (Group 3, 2-D)
"""
if xObject[obj]['/Filter'] == '/CCITTFaxDecode':
if xObject[obj]['/DecodeParms']['/K'] == -1:
CCITT_group = 4
else:
CCITT_group = 3
width = xObject[obj]['/Width']
height = xObject[obj]['/Height']
data = xObject[obj]._data # sorry, getData() does not work for CCITTFaxDecode
img_size = len(data)
tiff_header = tiff_header_for_CCITT(width, height, img_size, CCITT_group)
img_name = obj[1:] + '.tiff'
with open(img_name, 'wb') as img_file:
img_file.write(tiff_header + data)
#
# import io
# from PIL import Image
# im = Image.open(io.BytesIO(tiff_header + data))
pdf_file.close()

Libpoppler comes with a tool called "pdfimages" that does exactly this.
(On ubuntu systems it's in the poppler-utils package)
http://poppler.freedesktop.org/
http://en.wikipedia.org/wiki/Pdfimages
Windows binaries: http://blog.alivate.com.au/poppler-windows/

I prefer minecart as it is extremely easy to use. The below snippet show how to extract images from a pdf:
#pip install minecart
import minecart
pdffile = open('Invoices.pdf', 'rb')
doc = minecart.Document(pdffile)
page = doc.get_page(0) # getting a single page
#iterating through all pages
for page in doc.iter_pages():
im = page.images[0].as_pil() # requires pillow
display(im)

PikePDF can do this with very little code:
from pikepdf import Pdf, PdfImage
filename = "sample-in.pdf"
example = Pdf.open(filename)
for i, page in enumerate(example.pages):
for j, (name, raw_image) in enumerate(page.images.items()):
image = PdfImage(raw_image)
out = image.extract_to(fileprefix=f"{filename}-page{i:03}-img{j:03}")
extract_to will automatically pick the file extension based on how the image
is encoded in the PDF.
If you want, you could also print some detail about the images as they get extracted:
# Optional: print info about image
w = raw_image.stream_dict.Width
h = raw_image.stream_dict.Height
f = raw_image.stream_dict.Filter
size = raw_image.stream_dict.Length
print(f"Wrote {name} {w}x{h} {f} {size:,}B {image.colorspace} to {out}")
which can print something like
Wrote /Im1 150x150 /DCTDecode 5,952B /ICCBased to sample2.pdf-page000-img000.jpg
Wrote /Im10 32x32 /FlateDecode 36B /ICCBased to sample2.pdf-page000-img001.png
...
See the docs for
more that you can do with images, including replacing them in the PDF file.
While this usually works pretty well, note that there are a number of images that won’t be extracted this way:
Vector graphics, such as embedded SVG/PS/PDF; you can crop the original PDF, but I’m not aware of an easy way to do this programmatically
Certain monochrome images compressed inside the PDF using “CCITTFaxDecode, type G4, with the /EncodedByteAlign set to true”
Non-RGB/CMYK images, aka ProcessColorModel/DeviceN/HiFi, used for colour separations (Thanks mara004)

Here is my version from 2019 that recursively gets all images from PDF and reads them with PIL.
Compatible with Python 2/3. I also found that sometimes image in PDF may be compressed by zlib, so my code supports decompression.
#!/usr/bin/env python3
try:
from StringIO import StringIO
except ImportError:
from io import BytesIO as StringIO
from PIL import Image
from PyPDF2 import PdfFileReader, generic
import zlib
def get_color_mode(obj):
try:
cspace = obj['/ColorSpace']
except KeyError:
return None
if cspace == '/DeviceRGB':
return "RGB"
elif cspace == '/DeviceCMYK':
return "CMYK"
elif cspace == '/DeviceGray':
return "P"
if isinstance(cspace, generic.ArrayObject) and cspace[0] == '/ICCBased':
color_map = obj['/ColorSpace'][1].getObject()['/N']
if color_map == 1:
return "P"
elif color_map == 3:
return "RGB"
elif color_map == 4:
return "CMYK"
def get_object_images(x_obj):
images = []
for obj_name in x_obj:
sub_obj = x_obj[obj_name]
if '/Resources' in sub_obj and '/XObject' in sub_obj['/Resources']:
images += get_object_images(sub_obj['/Resources']['/XObject'].getObject())
elif sub_obj['/Subtype'] == '/Image':
zlib_compressed = '/FlateDecode' in sub_obj.get('/Filter', '')
if zlib_compressed:
sub_obj._data = zlib.decompress(sub_obj._data)
images.append((
get_color_mode(sub_obj),
(sub_obj['/Width'], sub_obj['/Height']),
sub_obj._data
))
return images
def get_pdf_images(pdf_fp):
images = []
try:
pdf_in = PdfFileReader(open(pdf_fp, "rb"))
except:
return images
for p_n in range(pdf_in.numPages):
page = pdf_in.getPage(p_n)
try:
page_x_obj = page['/Resources']['/XObject'].getObject()
except KeyError:
continue
images += get_object_images(page_x_obj)
return images
if __name__ == "__main__":
pdf_fp = "test.pdf"
for image in get_pdf_images(pdf_fp):
(mode, size, data) = image
try:
img = Image.open(StringIO(data))
except Exception as e:
print ("Failed to read image with PIL: {}".format(e))
continue
# Do whatever you want with the image

I started from the code of #sylvain
There was some flaws, like the exception NotImplementedError: unsupported filter /DCTDecode of getData, or the fact the code failed to find images in some pages because they were at a deeper level than the page.
There is my code :
import PyPDF2
from PIL import Image
import sys
from os import path
import warnings
warnings.filterwarnings("ignore")
number = 0
def recurse(page, xObject):
global number
xObject = xObject['/Resources']['/XObject'].getObject()
for obj in xObject:
if xObject[obj]['/Subtype'] == '/Image':
size = (xObject[obj]['/Width'], xObject[obj]['/Height'])
data = xObject[obj]._data
if xObject[obj]['/ColorSpace'] == '/DeviceRGB':
mode = "RGB"
else:
mode = "P"
imagename = "%s - p. %s - %s"%(abspath[:-4], p, obj[1:])
if xObject[obj]['/Filter'] == '/FlateDecode':
img = Image.frombytes(mode, size, data)
img.save(imagename + ".png")
number += 1
elif xObject[obj]['/Filter'] == '/DCTDecode':
img = open(imagename + ".jpg", "wb")
img.write(data)
img.close()
number += 1
elif xObject[obj]['/Filter'] == '/JPXDecode':
img = open(imagename + ".jp2", "wb")
img.write(data)
img.close()
number += 1
else:
recurse(page, xObject[obj])
try:
_, filename, *pages = sys.argv
*pages, = map(int, pages)
abspath = path.abspath(filename)
except BaseException:
print('Usage :\nPDF_extract_images file.pdf page1 page2 page3 …')
sys.exit()
file = PyPDF2.PdfFileReader(open(filename, "rb"))
for p in pages:
page0 = file.getPage(p-1)
recurse(p, page0)
print('%s extracted images'% number)

Well I have been struggling with this for many weeks, many of these answers helped me through, but there was always something missing, apparently no one here has ever had problems with jbig2 encoded images.
In the bunch of PDF that I am to scan, images encoded in jbig2 are very popular.
As far as I understand there are many copy/scan machines that scan papers and transform them into PDF files full of jbig2 encoded images.
So after many days of tests decided to go for the answer proposed here by dkagedal long time ago.
Here is my step by step on linux: (if you have another OS I suggest to use a linux docker it's going to be much easier.)
First step:
apt-get install poppler-utils
Then I was able to run command line tool called pdfimages like this:
pdfimages -all myfile.pdf ./images_found/
With the above command you will be able to extract all the images contained in myfile.pdf and you will have them saved inside images_found (you have to create images_found before)
In the list you will find several types of images, png, jpg, tiff; all these are easily readable with any graphic tool.
Then you will have some files named like: -145.jb2e and -145.jb2g.
These 2 files contain ONE IMAGE encoded in jbig2 saved in 2 different files one for the header and one for the data
Again I have lost many days trying to find out how to convert those files into something readable and finally I came across this tool called jbig2dec
So first you need to install this magic tool:
apt-get install jbig2dec
then you can run:
jbig2dec -t png -145.jb2g -145.jb2e
You are going to finally be able to get all extracted images converted into something useful.
good luck!

Much easier solution:
Use the poppler-utils package. To install it use homebrew (homebrew is MacOS specific, but you can find the poppler-utils package for Widows or Linux here: https://poppler.freedesktop.org/). First line of code below installs poppler-utils using homebrew. After installation the second line (run from the command line) then extracts images from a PDF file and names them "image*". To run this program from within Python use the os or subprocess module. Third line is code using os module, beneath that is an example with subprocess (python 3.5 or later for run() function). More info here: https://www.cyberciti.biz/faq/easily-extract-images-from-pdf-file/
brew install poppler
pdfimages file.pdf image
import os
os.system('pdfimages file.pdf image')
or
import subprocess
subprocess.run('pdfimages file.pdf image', shell=True)

I did this for my own program, and found that the best library to use was PyMuPDF. It lets you find out the "xref" numbers of each image on each page, and use them to extract the raw image data from the PDF.
import fitz
from PIL import Image
import io
filePath = "path/to/file.pdf"
#opens doc using PyMuPDF
doc = fitz.Document(filePath)
#loads the first page
page = doc.loadPage(0)
#[First image on page described thru a list][First attribute on image list: xref n], check PyMuPDF docs under getImageList()
xref = page.getImageList()[0][0]
#gets the image as a dict, check docs under extractImage
baseImage = doc.extractImage(xref)
#gets the raw string image data from the dictionary and wraps it in a BytesIO object before using PIL to open it
image = Image.open(io.BytesIO(baseImage['image']))
#Displays image for good measure
image.show()
Definitely check out the docs, though.

After some searching I found the following script which works really well with my PDF's. It does only tackle JPG, but it worked perfectly with my unprotected files. Also is does not require any outside libraries.
Not to take any credit, the script originates from Ned Batchelder, and not me.
Python3 code: extract jpg's from pdf's. Quick and dirty
import sys
with open(sys.argv[1],"rb") as file:
file.seek(0)
pdf = file.read()
startmark = b"\xff\xd8"
startfix = 0
endmark = b"\xff\xd9"
endfix = 2
i = 0
njpg = 0
while True:
istream = pdf.find(b"stream", i)
if istream < 0:
break
istart = pdf.find(startmark, istream, istream + 20)
if istart < 0:
i = istream + 20
continue
iend = pdf.find(b"endstream", istart)
if iend < 0:
raise Exception("Didn't find end of stream!")
iend = pdf.find(endmark, iend - 20)
if iend < 0:
raise Exception("Didn't find end of JPG!")
istart += startfix
iend += endfix
print("JPG %d from %d to %d" % (njpg, istart, iend))
jpg = pdf[istart:iend]
with open("jpg%d.jpg" % njpg, "wb") as jpgfile:
jpgfile.write(jpg)
njpg += 1
i = iend

After reading the posts using pyPDF2.
The error while using #sylvain's code NotImplementedError: unsupported filter /DCTDecode must come from the method .getData(): It is solved when using ._data instead, by #Alex Paramonov.
So far I have only met "DCTDecode" cases, but I am sharing the adapted code that include remarks from the different posts: From zilb by #Alex Paramonov, sub_obj['/Filter'] being a list, by #mxl.
Hope it can help the pyPDF2 users. Follow the code:
import sys
import PyPDF2, traceback
import zlib
try:
from PIL import Image
except ImportError:
import Image
pdf_path = 'path_to_your_pdf_file.pdf'
input1 = PyPDF2.PdfFileReader(open(pdf_path, "rb"))
nPages = input1.getNumPages()
for i in range(nPages) :
page0 = input1.getPage(i)
if '/XObject' in page0['/Resources']:
try:
xObject = page0['/Resources']['/XObject'].getObject()
except :
xObject = []
for obj_name in xObject:
sub_obj = xObject[obj_name]
if sub_obj['/Subtype'] == '/Image':
zlib_compressed = '/FlateDecode' in sub_obj.get('/Filter', '')
if zlib_compressed:
sub_obj._data = zlib.decompress(sub_obj._data)
size = (sub_obj['/Width'], sub_obj['/Height'])
data = sub_obj._data#sub_obj.getData()
try :
if sub_obj['/ColorSpace'] == '/DeviceRGB':
mode = "RGB"
elif sub_obj['/ColorSpace'] == '/DeviceCMYK':
mode = "CMYK"
# will cause errors when saving (might need convert to RGB first)
else:
mode = "P"
fn = 'p%03d-%s' % (i + 1, obj_name[1:])
if '/Filter' in sub_obj:
if '/FlateDecode' in sub_obj['/Filter']:
img = Image.frombytes(mode, size, data)
img.save(fn + ".png")
elif '/DCTDecode' in sub_obj['/Filter']:
img = open(fn + ".jpg", "wb")
img.write(data)
img.close()
elif '/JPXDecode' in sub_obj['/Filter']:
img = open(fn + ".jp2", "wb")
img.write(data)
img.close()
elif '/CCITTFaxDecode' in sub_obj['/Filter']:
img = open(fn + ".tiff", "wb")
img.write(data)
img.close()
elif '/LZWDecode' in sub_obj['/Filter'] :
img = open(fn + ".tif", "wb")
img.write(data)
img.close()
else :
print('Unknown format:', sub_obj['/Filter'])
else:
img = Image.frombytes(mode, size, data)
img.save(fn + ".png")
except:
traceback.print_exc()
else:
print("No image found for page %d" % (i + 1))

I installed ImageMagick on my server and then run commandline-calls through Popen:
#!/usr/bin/python
import sys
import os
import subprocess
import settings
IMAGE_PATH = os.path.join(settings.MEDIA_ROOT , 'pdf_input' )
def extract_images(pdf):
output = 'temp.png'
cmd = 'convert ' + os.path.join(IMAGE_PATH, pdf) + ' ' + os.path.join(IMAGE_PATH, output)
subprocess.Popen(cmd.split(), stderr=subprocess.STDOUT, stdout=subprocess.PIPE)
This will create an image for every page and store them as temp-0.png, temp-1.png ....
This is only 'extraction' if you got a pdf with only images and no text.

I added all of those together in PyPDFTK here.
My own contribution is handling of /Indexed files as such:
for obj in xObject:
if xObject[obj]['/Subtype'] == '/Image':
size = (xObject[obj]['/Width'], xObject[obj]['/Height'])
color_space = xObject[obj]['/ColorSpace']
if isinstance(color_space, pdf.generic.ArrayObject) and color_space[0] == '/Indexed':
color_space, base, hival, lookup = [v.getObject() for v in color_space] # pg 262
mode = img_modes[color_space]
if xObject[obj]['/Filter'] == '/FlateDecode':
data = xObject[obj].getData()
img = Image.frombytes(mode, size, data)
if color_space == '/Indexed':
img.putpalette(lookup.getData())
img = img.convert('RGB')
img.save("{}{:04}.png".format(filename_prefix, i))
Note that when /Indexed files are found, you can't just compare /ColorSpace to a string, because it comes as an ArrayObject. So, we have to check the array and retrieve the indexed palette (lookup in the code) and set it in the PIL Image object, otherwise it stays uninitialized (zero) and the whole image shows as black.
My first instinct was to save them as GIFs (which is an indexed format), but my tests turned out that PNGs were smaller and looked the same way.
I found those types of images when printing to PDF with Foxit Reader PDF Printer.

As of February 2019, the solution given by #sylvain (at least on my setup) does not work without a small modification: xObject[obj]['/Filter'] is not a value, but a list, thus in order to make the script work, I had to modify the format checking as follows:
import PyPDF2, traceback
from PIL import Image
input1 = PyPDF2.PdfFileReader(open(src, "rb"))
nPages = input1.getNumPages()
print nPages
for i in range(nPages) :
print i
page0 = input1.getPage(i)
try :
xObject = page0['/Resources']['/XObject'].getObject()
except : xObject = []
for obj in xObject:
if xObject[obj]['/Subtype'] == '/Image':
size = (xObject[obj]['/Width'], xObject[obj]['/Height'])
data = xObject[obj].getData()
try :
if xObject[obj]['/ColorSpace'] == '/DeviceRGB':
mode = "RGB"
elif xObject[obj]['/ColorSpace'] == '/DeviceCMYK':
mode = "CMYK"
# will cause errors when saving
else:
mode = "P"
fn = 'p%03d-%s' % (i + 1, obj[1:])
print '\t', fn
if '/FlateDecode' in xObject[obj]['/Filter'] :
img = Image.frombytes(mode, size, data)
img.save(fn + ".png")
elif '/DCTDecode' in xObject[obj]['/Filter']:
img = open(fn + ".jpg", "wb")
img.write(data)
img.close()
elif '/JPXDecode' in xObject[obj]['/Filter'] :
img = open(fn + ".jp2", "wb")
img.write(data)
img.close()
elif '/LZWDecode' in xObject[obj]['/Filter'] :
img = open(fn + ".tif", "wb")
img.write(data)
img.close()
else :
print 'Unknown format:', xObject[obj]['/Filter']
except :
traceback.print_exc()

You could use pdfimages command in Ubuntu as well.
Install poppler lib using the below commands.
sudo apt install poppler-utils
sudo apt-get install python-poppler
pdfimages file.pdf image
List of files created are, (for eg.,. there are two images in pdf)
image-000.png
image-001.png
It works ! Now you can use a subprocess.run to run this from python.

Try below code. it will extract all image from pdf.
import sys
import PyPDF2
from PIL import Image
pdf=sys.argv[1]
print(pdf)
input1 = PyPDF2.PdfFileReader(open(pdf, "rb"))
for x in range(0,input1.numPages):
xObject=input1.getPage(x)
xObject = xObject['/Resources']['/XObject'].getObject()
for obj in xObject:
if xObject[obj]['/Subtype'] == '/Image':
size = (xObject[obj]['/Width'], xObject[obj]['/Height'])
print(size)
data = xObject[obj]._data
#print(data)
print(xObject[obj]['/Filter'])
if xObject[obj]['/Filter'][0] == '/DCTDecode':
img_name=str(x)+".jpg"
print(img_name)
img = open(img_name, "wb")
img.write(data)
img.close()
print(str(x)+" is done")

I rewrite solutions as single python class.
It should be easy to work with. If you notice new "/Filter" or "/ColorSpace" then just add it to internal dictionaries.
https://github.com/survtur/extract_images_from_pdf
Requirements:
Python3.6+
PyPDF2
PIL

With pypdfium2 (v4):
import pypdfium2.__main__ as pdfium_cli
pdfium_cli.api_main(["extract-images", "input.pdf", "-o", "output_dir"])
There are some options to choose between different extraction strategies (see pypdfium2 extract-images --help).
Actual non-CLI Python APIs are available as well. The CLI's implementation demonstrates them (see the docs for details):
# assuming `args` is a given options set (e. g. argparse namepsace)
import pypdfium2 as pdfium
import pypdfium2.raw as pdfium_c
pdf = pdfium.PdfDocument(args.input)
images = []
for i in args.pages:
page = pdf.get_page(i)
obj_searcher = page.get_objects(
filter = (pdfium_c.FPDF_PAGEOBJ_IMAGE, ),
max_depth = args.max_depth,
)
images += list(obj_searcher)
n_digits = len(str(len(images)))
for i, image in enumerate(images):
prefix = args.output_dir / ("%s_%0*d" % (args.input.stem, n_digits, i+1))
try:
if args.use_bitmap:
pil_image = image.get_bitmap(render=args.render).to_pil()
pil_image.save("%s.%s" % (prefix, args.format))
else:
image.extract(prefix, fb_format=args.format, fb_render=args.render)
except pdfium.PdfiumError:
traceback.print_exc()
Note: Unfortunately, PDFium's public image extraction APIs are quite limited, so PdfImage.extract() is by far not as smart as pikepdf. If you only need the image bitmap and do not intend to save the image, PdfImage.get_bitmap() should be quite fine, though.
(Disclaimer: I'm the author of pypdfium2)

Following code is updated version of PyMUPDF :
doc = fitz.open("/Users/vignesh/Downloads/ViewJournal2244.pdf")
Images_per_page={}
for i in page:
images=[]
for image_box in doc[page].get_images():
rect=doc[page].get_image_rects(image_box)
page=doc[page].get_pixmap(matrix=fitz.Identity,clip=rect[0],dpi=None,colorspace=fitz.csRGB,alpha=True, annots=True)
string=page.tobytes()
images.append(string)
Images_per_page[i]=images

This worked for me:
import PyPDF2
from PyPDF2 import PdfFileReader
# Open the PDF file
pdf_file = open(r"C:\\Users\\file.pdf", 'rb')
pdf_reader = PdfFileReader(pdf_file)
# Iterate through each page
for page_num in range(pdf_reader.numPages):
page = pdf_reader.getPage(page_num)
xObject = page['/Resources']['/XObject'].getObject()
# Iterate through each image on the page
for obj in xObject:
if xObject[obj]['/Subtype'] == '/Image':
size = (xObject[obj]['/Width'], xObject[obj]['/Height'])
data = xObject[obj].getData()
# You can now save the image data to a file
with open(f'C:\\Users\\filepath\{obj}.jpg', 'wb') as img_file:
img_file.write(data)
# Close the PDF file
pdf_file.close()

First Install pdf2image
pip install pdf2image==1.14.0
Follow the below code for extraction of pages from PDF.
file_path="file path of PDF"
info = pdfinfo_from_path(file_path, userpw=None, poppler_path=None)
maxPages = info["Pages"]
image_counter = 0
if maxPages > 10:
for page in range(1, maxPages, 10):
pages = convert_from_path(file_path, dpi=300, first_page=page,
last_page=min(page+10-1, maxPages))
for page in pages:
page.save(image_path+'/' + str(image_counter) + '.png', 'PNG')
image_counter += 1
else:
pages = convert_from_path(file_path, 300)
for i, j in enumerate(pages):
j.save(image_path+'/' + str(i) + '.png', 'PNG')
Hope it helps coders looking for easy conversion of PDF files to Images as per pages of PDF.