I have 2 modules in my project: first works with image in bytes format, second requires skimage object. I need to combine them.
I have this code:
import io
from PIL import Image
import skimage.io
area = (...)
image = Image.open(io.BytesIO(image_bytes))
image = Image.crop(area)
image = skimage.io.imread(image)
But i get this error:
How can i convert an image (object/variable) to skimage? I don't necessarily need PIL Image, this is just one way to work with bytes image, cause i need to crop my image
Thanks!
Scikit-image works with images stored as Numpy arrays - same as OpenCV and wand. So, if you have a PIL Image, you can make a Numpy array for scikit-image like this:
# Make Numpy array for scikit-image from "PIL Image"
na = np.array(YourPILImage)
Just in case you want to go the other way, and make a PIL Image from a Numpy array, you can do:
# Make "PIL Image" from Numpy array
pi = Image.fromarray(na)
Related
I have a piece of code that takes in image data as grayscale values, and then converts into an image using matplotlib below
import matplotlib.pyplot as plt
import numpy
image_data = image_result.GetNDArray()
numpy.savetxt('data.cvs', image_data)
# Draws an image on the current figure
image = plt.imshow(image_data, cmap='gray')
I want to be able to export this data to LabView as a .png file. So I need to save these image to a folder where LabView and display them. Is there a function with pillow or os that can do this?
plt.imsave('output.png', image)
Does this work?
If image_data is a Numpy array of shape height x width with dtype=np.uint8 or dtype=np.uint16, you can make a PIL Image and save it as a PNG like this:
from PIL import Image
# Make PIL Image from Numpy array
pImage = Image.fromarray(image_data)
pImage.save('forLabView.png')
You can equally use OpenCV to save a Numpy array as a PNG for LabView like this:
import cv2
# Save Numpy array as PNG
cv2.imwrite('forLabView.png', image_data)
Check what your array is with:
print(image_data.shape, image_data.dtype)
So I was working with skimage for some image preprocessing (i'm very new to it). I have a PIL Image object and wanted to convert to a skimage image with skimage.io.imread(). I know that I can just save the image and then run imread on that file, but I was wondering if there was a way I could read the PIL Image object from the code itself. I tried to run imread on the PIL Image object itself but I end up getting errors.
OSError: Cannot understand given URI: <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=192....
Anyone know how I can solve this in skimage.
Scikit-Image stores images as Numpy arrays, so you just need to make a Numpy array from your PIL Image:
ImageForScikit = np.array(YourPILImage)
You may review imageio documentation related to the function imread for including in your code the attribute format and code as follows just in case the image format is PNG: imageio.imread(filename, format = 'PNG')
import cv2
import numpy as np
from PIL import Image
img = Image.open("test.jpg")
imgfilename = img.filename
imgb,imgg,imgr = cv2.split(img)
count = 0
I've been getting the following error when I try to run my code - this is the error I'm getting:
File "WB.py", line 9, in <module>
imgb,imgg,imgr = cv2.split(img)
TypeError: m is not a numpy array, neither a scalar
You're generally not supposed to use PIL together with numpy, these libraries don't interact a lot.
From numpy (and opencv)'s point of view, images are just 2D or 3D arrays of any given type (2D for grayscale, 3D for color). Also cv2 uses BGR by default...
Start with cv2.imread(path, cv2.IMREAD_COLOR) instead of Image.open(path).
You should use the split function available in PIL for this purpose.
Image.split()
This is because images are interpreted differently in OpenCV and PIL. Hence you cannot you the functions available in these packages interchangeably.
For a program I'm writing, I need to convert an RGB image to grayscale and read it as a NumPy array using PIL.
But when I run the following code, it converts the image not to grayscale, but to a strange color distortion a bit like the output of a thermal camera, as presented.
Any idea what the problem might be?
Thank you!
http://www.loadthegame.com/wp-content/uploads/2014/09/thermal-camera.png
from PIL import Image
from numpy import *
from pylab import *
im = array(Image.open('happygoat.jpg').convert("L"))
inverted = Image.fromarray(im)
imshow(inverted)
show()
matplotlib's imshow is aimed at scientific representation of data - not just image data. By default it's configured to use a high constrast color palette.
You can force it to display data using grayscale by passing the following option:
import matplotlib.cm
imshow(inverted, cmap=matplotlib.cm.Greys_r)
Add this code to view/display an image:
from PIL import Image;
from numpy import *
from pylab import *
im = array(Image.open('happygoat.jpg').convert("L"));
inverted = Image.fromarray(im);
inverted
PIL has seek(frame) function to seek through multi frame file and tell() function to return the current frame number.
Is it possible to create such multiple frame TIFF image using PIL or Pillow (or using any other library)?
scikit-image and numpy packages can be used.
For example:
import from skimage.io import imread, imsave
from numpy import *
im = imread("fileName.tiff")
im_array = array_split(im, 2, axis=3) # dividing the array into 2 parts along the 3rd axis
imsave("part1.tiff", im_array[0])
imsave("part2.tiff", im_array[1])