I have converted set of images to ndarray and stored it, now i have to convert them back to images without saving it to disk. I tried with " toimage() " function, but it is displaying only 1 image.
toimage(resizedlist.values()[0]).show()
resizedlist.values contains the ndarray of 49 images. Is there any way to display images randomly??
Thanks in advance!
To plot an ndarray as an image you can use matplotlib:
import numpy as np
import matplotlib.pyplot as plt
random = np.random.normal(0,1,size=[100,100])
plt.imshow(random,aspect="auto")
plt.show()
If your image data is stored RGBA, imshow will plot the image with the correct colours etc.
For reference, all this information can be found here:
http://matplotlib.org/1.3.1/users/image_tutorial.html
Related
How can I view images stored with a .npy extension and save my own files in that format?
.npy is the file extension for numpy arrays - you can read them using numpy.load:
import numpy as np
img_array = np.load('filename.npy')
One of the easiest ways to view them is using matplotlib's imshow function:
from matplotlib import pyplot as plt
plt.imshow(img_array, cmap='gray')
plt.show()
You could also use PIL or pillow:
from PIL import Image
im = Image.fromarray(img_array)
# this might fail if `img_array` contains a data type that is not supported by PIL,
# in which case you could try casting it to a different dtype e.g.:
# im = Image.fromarray(img_array.astype(np.uint8))
im.show()
These functions aren't part of the Python standard library, so you may need to install matplotlib and/or PIL/pillow if you haven't already. I'm also assuming that the files are either 2D [rows, cols] (black and white) or 3D [rows, cols, rgb(a)] (color) arrays of pixel values.
Thanks Ali_m. In my case I inspect the npy file to check how many images was in the file with:
from PIL import Image
import numpy as np
data = np.load('imgs.npy')
data.shape
then I plotted the images in a loop:
from matplotlib import pyplot as plt
for i in range(len(data)):
plt.imshow(data[i], cmap='gray')
plt.show()
I'm working on an python program to display images of stars. The images are 16-bit grayscale tiffs.
If I try to display them in an extern program, e.g. ImageMagick they are correct but if I load them in python and then use 'show()' or implement them in a canvas in Tkinter they are, unless a few pixel, totally white.
So I estimate python sets every pixel above 255 to white but I don't know why. If I load the image and then save it as tiff again, ImageMagick can show it correct.
Thanks for help.
Try to convert the image to a numpy array and display that:
import Image
import matplotlib.pyplot as plt
import numpy as np
img = Image.open('image.tiff')
arr = np.asarray(img.getdata()).reshape(img.size[1], img.size[0])
plt.imshow(arr)
plt.show()
You can change the color mapping too:
from matplotlib import cm
plt.imshow(arr, cmap=cm.gray)
I want to try view the image using spyder python as in:
skydrive share
the image is:
uint16 (10-bit)
width:1376 pixel, height: 960 pixel
no header
bayer pattern blue-green, green-red
What python script is suitable?
Thanks.
Here is one way.
Start with imports
from matplotlib import pyplot as plt
import numpy as np
Now allocate the space
image = np.empty((1376,960), np.uint16)
Read the image into your array:
image.data[:] = open('20_1-20ms.raw').read()
Display it:
plt.imshow(image)
I'm trying to display a PNG file using matplotlib and of course, python. For this test, I've generated the following image:
Now, I load and transform the image into a multidimensional numpy matrix:
import numpy as np
import cv2
from matplotlib import pyplot as plt
cube = cv2.imread('Graphics/Display.png')
plt.imshow(cube)
plt.ion()
When I try to plot that image in matplotlib, the colors are inverted:
If the matrix does not have any modifications, why the colors in the plot are wrong?
Thanks in advance.
It appears that you may somehow have RGB switched with BGR. Notice that your greens are retained but all the blues turned to red. If cube has shape (M,N,3), try swapping cube[:,:,0] with cube[:,:,2]. You can do that with numpy like so:
rgb = numpy.fliplr(cube.reshape(-1,3)).reshape(cube.shape)
From the OpenCV documentation:
Note: In the case of color images, the decoded images will have the
channels stored in B G R order.
Try:
plt.imshow(cv2.cvtColor(cube, cv2.COLOR_BGR2RGB))
As others have pointed out, the problem is that numpy arrays are in BGR format, but matplotlib expects the arrays to be ordered in a different way.
You are looking for scipy.misc.toimage:
import scipy.misc
rgb = scipy.misc.toimage(cube)
Alternatively, you can use scipy.misc.imshow().
Color image loaded by OpenCV is in BGR mode. However, Matplotlib displays in RGB mode.
So we need to convert the image from BGR to RGB:
plt.imshow(cv2.cvtColor(cube, cv2.COLOR_BGR2RGB))
I am looking for a way to rescale the matrix given by reading in a png file using the matplotlib routine imread,
e.g.
from pylab import imread, imshow, gray, mean
from matplotlib.pyplot import show
a = imread('spiral.png')
#generates a RGB image, so do
show()
but actually I want to manually specify the dimension of $a$, say 200x200 entries, so I need some magic command (which I assume exists but cannot be found by myself) to interpolate the matrix.
Thanks for any useful comments : )
Cheers
You could try using the PIL (Image) module instead, together with numpy. Open and resize the image using Image then convert to array using numpy. Then display the image using pylab.
import pylab as pl
import numpy as np
from PIL import Image
path = r'\path\to\image\file.jpg'
img = Image.open(path)
img.resize((200,200))
a = np.asarray(img)
pl.imshow(a)
pl.show()
Hope this helps.