wip:

average_map.py

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+
+import atexit
+import tempfile
+import os
+import subprocess
+from uuid import uuid4
+from shutil import rmtree
+
+import argh
+from PIL import Image
+import cv2
+import numpy
+
+
+@argh.arg('videos', nargs='*')
+def main(output_file, videos, maxlen=900):
+	image = Image.new('RGB', (maxlen, len(videos)))
+
+	tempdir = tempfile.mkdtemp()
+	atexit.register(lambda: rmtree(tempdir, ignore_errors=True))
+
+	for row, video in enumerate(videos):
+		print "Processing video {}: {}".format(row, video)
+		rowdir = os.path.join(tempdir, str(uuid4()))
+		os.mkdir(rowdir)
+		subprocess.check_call([
+			'ffmpeg', '-hide_banner',
+			'-i', video,
+			'-r', '1',
+			os.path.join(rowdir, 'frame%08d.png'),
+		])
+		for i, frame in enumerate(sorted(os.listdir(rowdir))):
+			print "Processing frame {}".format(frame)
+			filepath = os.path.join(rowdir, frame)
+			if i >= maxlen:
+				break
+
+			## resize to 1,1, mostly center pixel
+			#color = Image.open(filepath).resize((1, 1)).convert('RGB').getpixel((0, 0))
+
+			## avg without black, in python
+			#frame_im = Image.open(filepath).convert('RGB')
+			#avg_color = (0, 0, 0)
+			#count = 0
+			#for color in frame_im.getdata():
+			#	if color != [0,0,0]:
+			#		avg_color = tuple(a + b for a, b in zip(avg_color, color))
+			#		count += 1
+			#avg_color = tuple(a / count for a in avg_color)
+
+			## true avg using numpy
+			#avg_per_row = numpy.average(cv2.imread(filepath), axis=0)
+			#avg = numpy.average(avg_per_row, axis=0)
+			#image.putpixel((i, row), tuple(map(int, avg)))
+
+			## avg without black, numpy
+			im = cv2.imread(filepath)
+			non_black = im[im.sum(axis=2) != 0]
+			avg = numpy.average(non_black, axis=0)
+			try:
+				color = tuple(map(int, avg))
+			except ValueError: # avg is NaN because all pixels black
+				color = (0, 0, 0)
+			image.putpixel((i, row), color)
+
+			#image.putpixel((i, row), tuple(avg_color))
+
+		rmtree(rowdir)
+
+	image.save(output_file)
+
+
+if __name__ == '__main__':
+	argh.dispatch_command(main)