We Keep Coding

How do I edit multiple files in PIL

I was trying to edit alot of images at the same time using pil and python it shows me this error:
my code so far is below
import glob
import PIL
from PIL import Image
image = glob.glob('./*.png')
img = Image.open(image)
img.putalpha(127)
img.save("")

you may try this:
import glob
import PIL
from PIL import Image
for i in glob.glob('./*.png'):
img = Image.open(i)
img.putalpha(127)
img.save("")

Converting Image to Bytearray with Python

I want to convert Image file to Bytearray. I extracted image from pdf file with minecart lib, but I cant find a way to convert it to bytearray. This is my code:
import minecart
from PIL import Image
import io
pdffile = open('sample6.pdf', 'rb')
doc = minecart.Document(pdffile)
for page in doc.iter_pages():
print(page)
img = page.images[0].as_pil()
print(img) # <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=1641x2320 at 0x7FBDF02E6A00>
print(type(img)) # <class 'PIL.JpegImagePlugin.JpegImageFile'>
I have tried to use bytearray(img) but It does not work.
Do you have solution for this (solution that does not consume to much time)?

Create io.BytesIO buffer and write to it using PIL.Image.save. Set appropriate quality and other parameters as per requirement.
import io
from PIL import Image
def convert_pil_image_to_byte_array(img):
img_byte_array = io.BytesIO()
img.save(img_byte_array, format='JPEG', subsampling=0, quality=100)
img_byte_array = img_byte_array.getvalue()
return img_byte_array
References:
Why is the quality of JPEG images produced by PIL so poor?

A clean way to read a multi-band tiff file from URL?

I have a web service from which I want to load a multi-band image in-memory inside a Python script (ultimately I'll be converting the image into a numpy array). As far as I know packages such as PIL and imageio don't support this.
What is the preferred way of doing this? I want to avoid saving and reading images to disk.
If I save the file to disk and then load as a multi-band tiff with tifffile package things work fine (see code below); but, as I said, I want to avoid reading/writing from/to disk.
import requests
import tifffile as tiff
TMP = 'tmp.tiff'
def save_img(url, outfilename):
resp = requests.get(url)
with open(outfilename, 'wb') as f:
f.write(resp.content)
def read_img(url):
save_img(url, TMP)
return tiff.imread(TMP)

The following snippet does the trick. (Note that one should do some additional error checking on response object.)
import requests
import tifffile as tiff
import io
def read_image_from_url(url):
resp = requests.get(url)
# Check that request succeeded
return tiff.imread(io.BytesIO(resp.content))

I'm not sure about multi-band images -- if Pillow (née PIL) supports them, fine -- but this is the basic method to load images from URLs in-memory using Requests and Pillow:
import requests
from PIL import Image
from io import BytesIO
resp = requests.get('https://i.imgur.com/ZPXIw.jpg')
resp.raise_for_status()
sio = BytesIO(resp.content) # Create an in-memory stream of the content
img = Image.open(sio) # And load it
print(img)
outputs
<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=605x532>

Read a base 64 encoded image from memory using OpenCv python library

I'm working on an app that to do some facial recognition from a webcam stream. I get base64 encoded data uri's of the canvas and want to use it to do something like this:
cv2.imshow('image',img)
The data URI looks something like this:
data:image/gif;base64,R0lGODlhEAAQAMQAAORHHOVSKudfOulrSOp3WOyDZu6QdvCchPGolfO0o/XBs/fNwfjZ0frl3/zy7////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACH5BAkAABAALAAAAAAQABAAAAVVICSOZGlCQAosJ6mu7fiyZeKqNKToQGDsM8hBADgUXoGAiqhSvp5QAnQKGIgUhwFUYLCVDFCrKUE1lBavAViFIDlTImbKC5Gm2hB0SlBCBMQiB0UjIQA7
So, for clarity I've shown what the image looks like so the base64 string is not broken.
<img src="data:image/gif;base64,R0lGODlhEAAQAMQAAORHHOVSKudfOulrSOp3WOyDZu6QdvCchPGolfO0o/XBs/fNwfjZ0frl3/zy7////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACH5BAkAABAALAAAAAAQABAAAAVVICSOZGlCQAosJ6mu7fiyZeKqNKToQGDsM8hBADgUXoGAiqhSvp5QAnQKGIgUhwFUYLCVDFCrKUE1lBavAViFIDlTImbKC5Gm2hB0SlBCBMQiB0UjIQA7">
The official doc says, that imread accepts a file path as the argument. From this SO answer, if I do something like:
import base64
imgdata = base64.b64decode(imgstring) #I use imgdata as this variable itself in references below
filename = 'some_image.jpg'
with open(filename, 'wb') as f:
f.write(imgdata)
The above code snippet works and the image file gets generated properly. However I don't think so many File IO operations are feasible considering I'd be doing this for every frame of the stream. I want to be able to read the image into the memory directly creating the img object.
I have tried two solutions that seem to be working for some people.
Using PIL reference:
pilImage = Image.open(StringIO(imgdata))
npImage = np.array(pilImage)
matImage = cv.fromarray(npImage)
I get cv not defined as I have openCV3 installed which is available to me as cv2 module. I tried img = cv2.imdecode(npImage,0), this returns nothing.
Getting the bytes from decoded string and converting it into an numpy array of sorts
file_bytes = numpy.asarray(bytearray(imgdata), dtype=numpy.uint8)
img = cv2.imdecode(file_bytes, 0) #Here as well I get returned nothing
The documentation doesn't really mention what the imdecode function returns. However, from the errors that I encountered, I guess it is expecting a numpy array or a scalar as the first argument. How do I get a handle on that image in memory so that I can do cv2.imshow('image',img) and all kinds of cool stuff thereafter.
I hope I was able to make myself clear.

This is my solution for python 3.7 and without using PIL
import base64
def readb64(uri):
encoded_data = uri.split(',')[1]
nparr = np.fromstring(base64.b64decode(encoded_data), np.uint8)
img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
return img
i hope that this solutions works for all

This worked for me on python 2, and doesn't require PIL/pillow or any other dependencies (except cv2):
Edit: for python3 use base64.b64decode(encoded_data) to decode instead.
import cv2
import numpy as np
def data_uri_to_cv2_img(uri):
encoded_data = uri.split(',')[1]
nparr = np.fromstring(encoded_data.decode('base64'), np.uint8)
img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
return img
data_uri = "data:image/jpeg;base64,/9j/4AAQ..."
img = data_uri_to_cv2_img(data_uri)
cv2.imshow(img)

You can just use both cv2 and pillow like this:
import base64
from PIL import Image
import cv2
from StringIO import StringIO
import numpy as np
def readb64(base64_string):
sbuf = StringIO()
sbuf.write(base64.b64decode(base64_string))
pimg = Image.open(sbuf)
return cv2.cvtColor(np.array(pimg), cv2.COLOR_RGB2BGR)
cvimg = readb64('R0lGODlhEAAQAMQAAORHHOVSKudfOulrSOp3WOyDZu6QdvCchPGolfO0o/XBs/fNwfjZ0frl3/zy7////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACH5BAkAABAALAAAAAAQABAAAAVVICSOZGlCQAosJ6mu7fiyZeKqNKToQGDsM8hBADgUXoGAiqhSvp5QAnQKGIgUhwFUYLCVDFCrKUE1lBavAViFIDlTImbKC5Gm2hB0SlBCBMQiB0UjIQA7')
cv2.imshow(cvimg)

I found this simple solution.
import cv2
import numpy as np
import base64
image = "" # raw data with base64 encoding
decoded_data = base64.b64decode(image)
np_data = np.fromstring(decoded_data,np.uint8)
img = cv2.imdecode(np_data,cv2.IMREAD_UNCHANGED)
cv2.imshow("test", img)
cv2.waitKey(0)
Source : https://gist.github.com/HoweChen/7cdd09b08147133d8e1fbe9b52c24768

Python image processing of picture directly from the web

I am writing python code to take an image from the web and calculate the standard deviation, ... and do other image processing with it. I have the following code:
from scipy import ndimage
from urllib2 import urlopen
from urllib import urlretrieve
import urllib2
import Image
import ImageFilter
def imagesd(imagelist):
for imageurl in imagelist:
opener1 = urllib2.build_opener()
page1 = opener1.open(imageurl)
im = page1.read()
#localfile = urlretrieve(
#img = Image.fromstring("RGBA", (1,1), page1.read())
#img = list(im.getdata())
# page1.read()
print img
#standard_deviation(p
Now I keep going back and forth because I am not sure how to take the image directly from the web, without saving it to disk, and passing it to the standard deviation function.
Any hints/help would be greatly appreciated.
Thanks.

PIL (Python Imaging Library) methods "fromstring" and "frombuffer" expect the image data in a raw, uncompacted, format.
When you do page1.read() you get the binary file data. In order to have PIL understanding it, you have to make this data mimick a file, and pass it to the "Image.open" method, which understands the file format as it is read from the web (i.e., the .jpg, gif, or .png data instead of raw pixel values)
Try something like this:
from cStringIO import StringIO
(...)
data = StringIO(page1.read())
img = Image.open(data)