Opening raw images on Python resulting in a different image compared to ImageJ

Question

I wrote this script to open a raw image and do some processing.

import numpy as np 
import matplotlib.pyplot as plt
PATH = "C:\Users\Documents\script_testing_folder\\"
IMAGE_PATH = PATH +"simulation01\\15x15_output_det_00001_raw_df_00000.bin"
raw_image = np.fromfile(IMAGE_PATH, dtype=np.uint64)
raw_image.shape = (15,15)
plt.imshow(raw_image,cmap = 'gray')
total_intensity = ndimage.sum(raw_image)
print total_intensity
plt.show()

Using this script I get an Image such as this:

In contrast... when I open the same image on ImageJ(file>import>raw (64bit real, 15x15 length and width)) I have this:

I have tried looking around, but I am not sure where I am going wrong when trying to reproduce the same image on python. Any help would be greatly appreciated.

Additionally when I sum the intensity in the image using:

total_intensity = ndimage.sum(raw_image)
print total_intensity

y I get 4200794456581938015, whereas, on ImageJ I get 0.585.

I am not sure where I am going wrong on these steps...

Thanks !

Edit: The original file if anyone wants to reproduce the results I got https://www.dropbox.com/s/po82z4uf2ku7k0e/15x15_output_det_00001_raw_df_00000.bin?dl=0

Answer 1

The problem is the endianness of your data (the order of the single bytes of a 64bit float). Fortunately, numpy has the functionality to solve this issue:

import numpy as np 
import matplotlib.pyplot as plt

# load the image
raw_image = np.fromfile('15x15_output_det_00001_raw_df_00000.bin')
raw_image = np.reshape(raw_image, (15, 15))

# swap the byte order
raw_image = raw_image.byteswap()

# output the sum of the intensities to check
total_intensity = np.sum(raw_image)
print "total intensity:", total_intensity

# plot the image
plt.imshow(raw_image,cmap = 'gray', interpolation='nearest')
plt.show()

Output:

total intensity: 0.585123878711

Result: