plot several image files in matplotlib subplots

Question

I would like to create a matrix subplot and display each BMP files, from a directory, in a different subplot, but I cannot find the appropriate solution for my problem, could somebody helping me?.

This the code that I have:

import os, sys from PIL import Image import matplotlib.pyplot as plt from glob import glob  bmps = glob('*trace*.bmp')  fig, axes = plt.subplots(3, 3)  for arch in bmps:     i = Image.open(arch)     iar = np.array(i)     for i in range(3):         for j in range(3):             axes[i, j].plot(iar)             plt.subplots_adjust(wspace=0, hspace=0) plt.show() 

I am having the following error after executing:

Answer 1

natively matplotlib only supports PNG images, see http://matplotlib.org/users/image_tutorial.html

then the way is always read the image - plot the image

read image

 img1 = mpimg.imread('stinkbug1.png')  img2 = mpimg.imread('stinkbug2.png') 

plot image (2 subplots)

 plt.figure(1)  plt.subplot(211)  plt.imshow(img1)   plt.subplot(212)  plt.imshow(img2)  plt.show() 

follow the tutorial on http://matplotlib.org/users/image_tutorial.html (because of the import libraries)

here is a thread on plotting bmps with matplotlib: Why bmp image displayed as wrong color with plt.imshow of matplotlib on IPython-notebook?

Answer 2

The bmp has three color channels, plus the height and width, giving it a shape of (h,w,3). I believe plotting the image gives you an error because the plot only accepts two dimensions. You could grayscale the image, which would produce a matrix of only two dimensions (h,w).

Without knowing the dimensions of the images, you could do something like this:

for idx, arch in enumerate(bmps):     i = idx % 3 # Get subplot row     j = idx // 3 # Get subplot column     image = Image.open(arch)     iar_shp = np.array(image).shape # Get h,w dimensions     image = image.convert('L') # convert to grayscale     # Load grayscale matrix, reshape to dimensions of color bmp     iar = np.array(image.getdata()).reshape(iar_shp[0], iar_shp[1])     axes[i, j].plot(iar)  plt.subplots_adjust(wspace=0, hspace=0)  plt.show()