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How to list an image sequence in an efficient way? Numercial sequence comparison in Python


I have a directory of 9 images:

image_0001, image_0002, image_0003
image_0010, image_0011
image_0011-1, image_0011-2, image_0011-3
image_9999

I would like to be able to list them in an efficient way, like this (4 entries for 9 images):

(image_000[1-3], image_00[10-11], image_0011-[1-3], image_9999)

Is there a way in python, to return a directory of images, in a short/clear way (without listing every file)?

So, possibly something like this:

list all images, sort numerically, create a list (counting each image in sequence from start). When an image is missing (create a new list), continue until original file list is finished. Now I should just have some lists that contain non broken sequences.

I'm trying to make it easy to read/describe a list of numbers. If I had a sequence of 1000 consecutive files It could be clearly listed as file[0001-1000] rather than file['0001','0002','0003' etc...]

Edit1(based on suggestion): Given a flattened list, how would you derive the glob patterns?

Edit2 I'm trying to break the problem down into smaller pieces. Here is an example of part of the solution: data1 works, data2 returns 0010 as 64, data3 (the realworld data) doesn't work:

# Find runs of consecutive numbers using groupby.  The key to the solution
# is differencing with a range so that consecutive numbers all appear in
# same group.
from operator import itemgetter
from itertools import *

data1=[01,02,03,10,11,100,9999]
data2=[0001,0002,0003,0010,0011,0100,9999]
data3=['image_0001','image_0002','image_0003','image_0010','image_0011','image_0011-2','image_0011-3','image_0100','image_9999']

list1 = []
for k, g in groupby(enumerate(data1), lambda (i,x):i-x):
    list1.append(map(itemgetter(1), g))
print 'data1'
print list1

list2 = []
for k, g in groupby(enumerate(data2), lambda (i,x):i-x):
    list2.append(map(itemgetter(1), g))
print '\ndata2'
print list2

returns:

data1
[[1, 2, 3], [10, 11], [100], [9999]]

data2
[[1, 2, 3], [8, 9], [64], [9999]]

Solution

  • Here is a working implementation of what you want to achieve, using the code you added as a starting point:

    #!/usr/bin/env python
    
    import itertools
    import re
    
    # This algorithm only works if DATA is sorted.
    DATA = ["image_0001", "image_0002", "image_0003",
            "image_0010", "image_0011",
            "image_0011-1", "image_0011-2", "image_0011-3",
            "image_0100", "image_9999"]
    
    def extract_number(name):
        # Match the last number in the name and return it as a string,
        # including leading zeroes (that's important for formatting below).
        return re.findall(r"\d+$", name)[0]
    
    def collapse_group(group):
        if len(group) == 1:
            return group[0][1]  # Unique names collapse to themselves.
        first = extract_number(group[0][1])  # Fetch range
        last = extract_number(group[-1][1])  # of this group.
        # Cheap way to compute the string length of the upper bound,
        # discarding leading zeroes.
        length = len(str(int(last)))
        # Now we have the length of the variable part of the names,
        # the rest is only formatting.
        return "%s[%s-%s]" % (group[0][1][:-length],
            first[-length:], last[-length:])
    
    groups = [collapse_group(tuple(group)) \
        for key, group in itertools.groupby(enumerate(DATA),
            lambda(index, name): index - int(extract_number(name)))]
    
    print groups
    

    This prints ['image_000[1-3]', 'image_00[10-11]', 'image_0011-[1-3]', 'image_0100', 'image_9999'], which is what you want.

    HISTORY: I initially answered the question backwards, as @Mark Ransom pointed out below. For the sake of history, my original answer was:

    You're looking for glob. Try:

    import glob
    images = glob.glob("image_[0-9]*")
    

    Or, using your example:

    images = [glob.glob(pattern) for pattern in ("image_000[1-3]*",
        "image_00[10-11]*", "image_0011-[1-3]*", "image_9999*")]
    images = [image for seq in images for image in seq]  # flatten the list