https://jip.debeer.it/friends-season-1-an-average-episode

average_frames.py

# references used:
# http://stackoverflow.com/questions/17291455/how-to-get-an-average-picture-from-100-pictures-using-pil
# http://stackoverflow.com/questions/16135677/efficient-way-to-find-median-value-of-a-number-of-rgb-images

import os, numpy, PIL
from PIL import Image

start_frame = 0 # the frame number starts at 0
jpgs_in_dir = {}
max_frames_in_dir = {}
max_frames = 0
w = 0
h = 0
output_folder = 'median_output'

def get_immediate_subdirectories(a_dir):
    return [name for name in os.listdir(a_dir)
            if os.path.isdir(os.path.join(a_dir, name)) and name != output_folder]

def path_to_sub_dir(sub_dir):
    return os.getcwd() + '/' + sub_dir

def path_to_jpg(sub_dir, filename):
    return path_to_sub_dir(sub_dir) + '/' + filename

# average pixels
# def process_images(imlist, N, x):
#     # Create a numpy array of floats to store the average (assume RGB images)
#     arr=numpy.zeros((h,w,3),numpy.float)
#
#     # Build up average pixel intensities, casting each image as an array of floats
#     for im in imlist:
#         imarr=numpy.array(Image.open(im),dtype=numpy.float)
#         arr=arr+imarr/N
#
#     # Round values in array and cast as 8-bit integer
#     arr=numpy.array(numpy.round(arr),dtype=numpy.uint8)
#
#     # Generate, save and preview final image
#     out=Image.fromarray(arr,mode="RGB")
#     out.save(os.getcwd() + "/" + output_folder + "/" + str(x) + ".jpg")
#     #out.show()

# median pixels
def process_images(imlist, N, x):

    # read the images into a stack
    stack = []
    for im in imlist:
        stack.append(numpy.array(Image.open(im),dtype=numpy.uint8))

    # flatten the images in the stack (so RGB values are no longer in a multidimensional list)
    Y = numpy.vstack((im.ravel() for im in stack))
    # calculate the median
    median = numpy.median(Y,axis = 0)
    # reshape back to the correct dimensions and depth (RGB)
    median = numpy.uint8(median.reshape(h,w,3))

    # Generate, save and preview final image
    out=Image.fromarray(median,mode="RGB")
    out.save(os.getcwd() + "/" + output_folder + "/" + str(x) + ".png")
    #out.show()

sub_dirs = get_immediate_subdirectories(os.getcwd())

if not os.path.exists(os.getcwd() + "/" + output_folder):
    os.makedirs(os.getcwd() + "/" + output_folder)

for dir in sub_dirs:
   # Access all files in the chosen sub-directory
   allfiles = os.listdir(path_to_sub_dir(dir))
   # filter out only JPG files
   imlist = [filename for filename in allfiles if  filename[-4:] in [".jpg",".JPG"]]

   # if the width and height haven't been defined yet and there is an image in the dir, define w and h
   if ((not w or not h) and len(imlist) > 0):
       # Assuming all images are the same size, get dimensions of first image
       w,h=Image.open(path_to_jpg(dir, imlist[0])).size

   # store all JPG filenames in the dictionary
   jpgs_in_dir[dir] = imlist
   max_frames_in_dir[dir] = len(imlist)
   print "max frames in dir " + str(dir) + ": " + str(max_frames_in_dir[dir])

# extract the max number of frames, so we know when to stop processing
max_frames = max(max_frames_in_dir.values())
print max_frames
print w,h

# process all frames
for x in range(start_frame, max_frames):
    print x
    # the number of frames to average at this time step
    N = len(sub_dirs)
    imlist = []
    y = 0
    while (y < N):
        dir = sub_dirs[y]
        # we have processed all the frames in this directory
        if ((max_frames_in_dir[dir]-1) < x):
            # don't process this directory again, remove it
            print "pop " + dir
            print sub_dirs.pop(y)
            # the number of frames to average has decreased
            N = N-1
            # don't increase y, because of .pop() we will already address
            # the next element in the next iteration
        else:
            # add the filename of the dir to process
            imlist.append(path_to_jpg(dir, jpgs_in_dir[dir][x]))
            y += 1

    process_images(imlist, N, x)
print