CODEWITHSUNDEEP
pythonimagefor-loop
A.LeBrun
A.LeBrun

Reputation: 161

Cycle Through Images in Directory and Assign a Variable to Each result in Python

So I am trying to cycle through a set of images in a directory and I'm looking to save the output of each calculate as it's own variable, in this case d1, d2, and d3. For some reason, this only outputs d3 and none of the other values. Any help regarding what is wrong would be greatly appreciated!

filelist = ['IMG_1.jpg','IMG_2.jpg', 'IMG_3.jpg']

for imagefile in filelist:
     for i in range(1,4):
          t=Image.open(imagefile).convert('L')

arr = array(t) #Convert test image into an array
f = arr + c #Add the corrective factor to the array with the UBM
f[f > 150] = 0
value = np.sum(f) #Sum elements in array
con = np.count_nonzero(f) #Count number of nonzero elements

arraysDict = {}
arraysDict['d{0}'.format(i)] = value/con

print arraysDict

If I do it this way (below), it prints each value for d1, d2, and d3 but they are the same for some reason.

filelist = ['IMG_1604.jpg','IMG_1605.jpg', 'IMG_1606.jpg']

for imagefile in filelist:
    t=Image.open(imagefile).convert('L')   
    arr = array(t) #Convert test image into an array
    f = arr + c #Add the corrective factor to the array with the UBM
    f[f > 150] = 0 
    value = np.sum(f) #Sum elements in array
    con = np.count_nonzero(f) #Count number of nonzero elements

arraysDict = {}
for i in range(1,4):
    arraysDict['d{0}'.format(i)] = value/con

q = arraysDict.values()
print q

Upvotes: 0

Views: 252

Answers (1)

user1846747
user1846747

Reputation:

You are initialising the arraysDict = {} every time inside the for loop. Which will clear the old data. Just initialize the arraysDict = {} outside the for loop.

filelist = ['IMG_1.jpg','IMG_2.jpg', 'IMG_3.jpg']

arraysDict = {}
value = {}
con = {}
i = 1

for imagefile in filelist:
      t=Image.open(imagefile).convert('L')
      arr = array(t) #Convert test image into an array
      f = arr + c #Add the corrective factor to the array with the UBM
      f[f > 150] = 0
      value[i] = np.sum(f) #Sum elements in array
      con[i] = np.count_nonzero(f) #Count number of nonzero elements
      i += 1


arraysDict = {}
for i in range(1,4):
    arraysDict['d{0}'.format(i)] = value[i]/con[i]

q = arraysDict.values()
print q

Upvotes: 2

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