We Keep Coding

Unable to convert imgkit image to PIL image

I am trying to convert an imgkit image into a PIL image to modify it. imgkit successfully converted the html to image when I tried to use a file. When I use BytesIO and try to convert to a PIL image, im getting an error.
Here is my code:
img = imgkit.from_string(template.render(a=elements, r=range(len(elements))), False, config=config)
bytesImg = BytesIO(img)
bytesImg.seek(0)
image = Image.open(bytesImg) #error here
PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x102082680>
I already saw this and this.
Am I incorrectly converting the imgkit image to bytes or is there some other error?
Using Pillow 8.1 Python 3.9 and imgkit 1.0.2

Am I incorrectly converting the imgkit image to bytes or is there some other error?
I would start from checking if your bytes represents image understand by your Pillow. Built-in module imghdr should suffice if you are excepting one of format known by it (see table in docs). Usage in this case:
import imghdr
...
print(imghdr.what(None, h=img))
If it does identify format then check if it is supported by your Pillow, else you would need to manually check file signature (few starting bytes).

imgkit was converting the html to pdf because the config variable was messed up.
use
which wkhtmltoimage
to find path to wkhtmltoimage and set
config = imgkit.config(wkhtmltoimage="path found")

How to get size and resolution on image that already in bytes

i want to know if there some way to get the size and resolution of the image that already in bytes in python, i tried to search about it and it was using an external library.. did you know how to do it by external libraries or not.
thanks

you can use PIL (pillow).
to install it run "pip install pillow" on your terminal:
from PIL import Image
import io
image_data = ... # byte values of the image
image = Image.open(io.BytesIO(image_data))
print(f'{image.height}, {image.width}')

Reading a binary image directly to OpenCV Mat / numpy mat

Through some http requests I have been able to receive an image in binary form as
b'\xff\xd8\xff\xe0\x00\...
and with:
with open('image.jpg', 'wb') as out_file:
out_file.write(binary_content)
where binary_content is a string containing the data received through request I saved an image into a file.
Afterwards I can read this image with OpenCV methods. But I wanted to do a direct pass from binary string to OpenCV Mat without any in-betweens. cv2.decode method didn't work.

io.BytesIO and PIL worked well. Closing this q.

If you want to stay in the SciPy ecosystem, then the imageio library (previously part of SciPy) works well.
from imageio import imread
image_array = imread("image_path.jpg")
The code above gives you an uint8 array, if you want a float array, you can cast it easily
from imageio import imread
image_array = imread("image_path.jpg").astype(float)

cv2 to tesseract directly without saving

import pytesseract
from pdf2image import convert_from_path, convert_from_bytes
import cv2,numpy
def pil_to_cv2(image):
open_cv_image = numpy.array(image)
return open_cv_image[:, :, ::-1].copy()
path='OriginalsFile.pdf'
images = convert_from_path(path)
cv_h=[pil_to_cv2(i) for i in images]
img_header = cv_h[0][:160,:]
#print(pytesseract.image_to_string(Image.open('test.png'))) I only found this in tesseract docs
Hello, is there a way to read the img_header directly using pytesseract without saving it,
pytesseract docs

pytesseract.image_to_string() input format
As documentation explains pytesseract.image_to_string() needs a PIL image as input.
So you can convert your CV image into PIL one easily, like this:
from PIL import Image
... (your code)
print(pytesseract.image_to_string(Image.fromarray(img_header)))
if you really don't want to use PIL!
see:
https://github.com/madmaze/pytesseract/blob/master/src/pytesseract.py
pytesseract is an easy wrapper to run the tesseract command def run_and_get_output() line, you'll see that it saves your image into an temporary file, and then gives the address to the tesseract to run.
hence, you can do the same with opencv, just rewrite the pytesseract only .py file to do it with opencv, although; i don't see any performance improvements whatsoever.

The fromarray function allows you to load the PIL document into tesseract without saving the document to disk, but you should also ensure that you don`t send a list of pil images into tesseract. The convert_from_path function can generate a list of pil images if a pdf document contains multiple pages, therefore you need to send each page into tesseract individually.
import pytesseract
from pdf2image import convert_from_path
import cv2, numpy
def pil_to_cv2(image):
open_cv_image = numpy.array(image)
return open_cv_image[:, :, ::-1].copy()
doc = convert_from_path(path)
for page_number, page_data in enumerate(doc):
cv_h= pil_to_cv2(page_data)
img_header = cv_h[:160,:]
print(f"{page_number} - {pytesseract.image_to_string(Image.fromarray(img_header))}")

Using python to save a JPG image that was edited in the script

Referring to the answer to this question, I tried to save my own JPG image files, after some basic image processing. I've only applied a rotation and a shear. This is my code:
import numpy as np
import sys
from skimage import data, io, filter, color, exposure
import skimage.transform as tf
from skimage.transform import rotate, setup, AffineTransform
from PIL import Image
mypath = PATH_TO_FILENAME
readfile = FILENAME
img = color.rgb2gray(io.imread(mypath + readfile))
myimg = rotate(img, angle=10, order=2)
afine_tf = tf.AffineTransform(shear=0.1)
editedimg = tf.warp(myimg, afine_tf)
# IF I UNCOMMENT THE TWO LINES BELOW, I CAN SEE THE EDITED IMAGE AS EXPECTED
#io.imshow(editedimg)
#io.show()
saveimg= np.array(editedimg)
result = Image.fromarray((saveimg).astype(np.uint8))
newfile = "edited_" + readfile
result.save(path+newfile)
I know that the image processing was fine because if I display it before saving, it's just the original image with a bit of rotation and shearing, as expected. But I'm doing something wrong while saving it. I tried without the astype(np.uint8)) part but got an error. Then I removed some of the code from the link mentioned above because I guessed it was particularly for Fourier Transforms, since when I included some of their code, then I got an image that was all gray but with white lines in the direction of the shear I'd applied. But now the image that gets saved is just 2KB of nothing but blackness.
And when I tried something as simple as:
result = Image.fromarray(editedimg)
result.save(path+newfile)
then I got this error:
raise IOError("cannot write mode %s as JPEG" % im.mode)
IOError: cannot write mode F as JPEG
I don't really need to use PIL, if there's another way to simply save my image, I'm fine with that.

Look into the PIL fork, Pillow, is is not as outdated and what you should probably be using for this.
Also depending on your operating system you may need a few other libraries to compile PIL with JPEG support properly, see here
This may also help Says you need to convert your image to RGB mode before saving.
Image.open('old.jpeg').convert('RGB').save('new.jpeg')