frame-entropy.py

#!/usr/bin/env python

import sys
import videocapture
import numpy
from scipy import ndimage
import math
import multiprocessing

c = videocapture.Capture(sys.argv[1])
prevframe = None
diffs = []

def _get_sobelized_entropy(i):
    frame = c.get_frame(i, True).astype('float')
    frame = ndimage.median_filter(frame, 3)

    dx = ndimage.sobel(frame, 0)  # horizontal derivative
    dy = ndimage.sobel(frame, 1)  # vertical derivative
    frame = numpy.hypot(dx, dy)  # magnitude
    frame *= 255.0 / numpy.max(frame)  # normalize (Q&D)

    histogram = numpy.histogram(frame, bins=256)[0]
    histogram_length = sum(histogram)
    samples_probability = [float(h) / histogram_length for h in histogram]
    entropy = -sum([p * math.log(p, 2) for p in samples_probability if p != 0])

    return entropy

pool = multiprocessing.Pool(processes=4)
res = pool.map(_get_sobelized_entropy, range(1, c.num_frames+1))
for (i, entropy) in enumerate(res):
    print "%s,%s" % (i, entropy)