Commit 9187e090 authored by Nathaniel Callens's avatar Nathaniel Callens
Browse files

updated .py file

parent dae4680c
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+27 −5
Original line number Diff line number Diff line
@@ -12,7 +12,7 @@ images and extract important statistics from them.

import numpy as np
from matplotlib import pyplot as plt

from itertools import product
import os
import sys
from PIL import Image
@@ -41,7 +41,31 @@ def image_extractor(scenes):
    return images #returns a list of file paths to .tiff files in the specified directory given in file_extractor

if __name__ == '__main__':
    scene_names = file_extractor()
    
    
    image = Image.open("practice_tiff.tiff")
    image2 = Image.open("practice2.tiff")
    imarray2 = np.array(image2)
    imarray = np.array(image)
    work = imarray2[:,:,0]
    ind1, ind2 = np.random.randint(0,434), np.random.randint(0,650)
    surrounding = []
    for i,j in product(np.arange(-1,2), repeat=2):
        if i == 0 and j == 0:
            continue
        else:
            surrounding.append(work[ind1+i, ind1+j])
    diff = []
    diff.append(np.max(surrounding)-np.min(surrounding))
    print(surrounding)
    print(diff)
    
    """For boundary cases: Start by grabbing the shape of the images and saving those
    as variables. Then, if statements for if row == 0 or row == maximum and if
    col == 0 or col == maximum. Then grab corresponding open pixels. Then proceed to do
    an and statement that handles the corners"""
    
    """scene_names = file_extractor()
    images = image_extractor(scene_names)
    im = Image.open(images[0])
    imarray = np.array(im)
@@ -50,8 +74,6 @@ if __name__ == '__main__':
    image_array = []
    for r in randos:
        image_array.append(np.array(Image.open(images[r])))
    indices = [val[i][j] for val in image_array]
    

    indices = [val[i][j] for val in image_array]"""

    
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practice2.tiff

0 → 100644
+1.08 MiB
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practice_tiff.tiff

0 → 100644
+4.99 MiB
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