Commit bd4c8ec2 authored by Nathaniel Callens's avatar Nathaniel Callens
Browse files

comments added

parent 7ca6a8bd
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+10 −9
Original line number Original line Diff line number Diff line
@@ -17,7 +17,6 @@ import os
import sys
import sys
from PIL import Image
from PIL import Image


print("hi")


def file_extractor(dirname="/media/elphel/SSD3-4GB/lwir16-proc/captures/teasdale/scenes"):
def file_extractor(dirname="/media/elphel/SSD3-4GB/lwir16-proc/captures/teasdale/scenes"):
    files = os.listdir(dirname)
    files = os.listdir(dirname)
@@ -70,20 +69,22 @@ if __name__ == '__main__':
 
 
    diff = []
    diff = []
    for ii in range(len(tiff1)):
    for ii in range(len(tiff1)):
        image = Image.open(tiff1[ii])
        image = Image.open(tiff1[ii])    #Open the image and read it as an Image object
        image = np.array(image)[1:,:]
        image = np.array(image)[1:,:]    #Convert to an array, leaving out the first row because the first row is just housekeeping data
        ar1, ar2 = image.shape
        ar1, ar2 = image.shape
       
       
        ind1, ind2 = np.random.randint(0,ar1), np.random.randint(0,ar2)
        ind1, ind2 = np.random.randint(0,ar1), np.random.randint(0,ar2) #ind1 randomly selects a row, ind2 randomly selects a column, 
        surrounding = []
                                                                        #this is now a random pixel selection within the image
        for i,j in product(np.arange(-1,2), repeat=2):
        
            if i == 0 and j == 0:
        surrounding = []                                                #initialize a list to be filled the 8 surrounding pixels
        for i,j in product(np.arange(-1,2), repeat=2):                  #Iterate through the combinations of surrounding pixel indices
            if i == 0 and j == 0:                                       #Avoid the target pixel
                continue
                continue
            else:
            else:
                surrounding.append(image[ind1+i, ind1+j])
                surrounding.append(image[ind1+i, ind1+j])               #Add the other 8 pixels to the list
        diff.append(np.max(surrounding)-np.min(surrounding))
        diff.append(np.max(surrounding)-np.min(surrounding))
    
    
    print("Hello World")