Bulb ramping is not 100% flicker-free and it will never be, since it measures the exposure from previous shots and it won't account for natural flicker. At fast shutter speeds, the flicker comes from the discrete shutter speeds enforced by Canon firmware.
So, I'm trying to get a script which should do perfect deflicker, based on robust statistics (median) and RAW image data. It should work even if you simply shoot in Auto or Manual, without any ramping.
Version 0.3 - added a Windows GUI (might work on Mac too).
Contact me if you'd like to try it.
Version 0.2 - tested on 800 pictures (video below) and added a real-time deflicker graph.
Version 0.1 - only tested on 10 pictures, with very promising results.
You need Python 2.x, numpy/scipy/matplotlib, dcraw, ufraw, imagemagick... and hopefully that's all.
Usage: create a folder named "raw" and another one named "jpg", paste your CR2 files under "raw" and run the script.
# RAW deflickering script
# Copyright (2012) a1ex. License: GPL.
from __future__ import division
import os, sys, re, time, datetime, subprocess, shlex
from math import *
from pylab import *
def progress(x, interval=1):
global _progress_first_time, _progress_last_time, _progress_message, _progress_interval
try:
p = float(x)
init = False
except:
init = True
if init:
_progress_message = x
_progress_last_time = time.time()
_progress_first_time = time.time()
_progress_interval = interval
elif x:
if time.time() - _progress_last_time > _progress_interval:
print >> sys.stderr, "%s [%d%% done, ETA %s]..." % (_progress_message, int(100*p), datetime.timedelta(seconds = round((1-p)/p*(time.time()-_progress_first_time))))
_progress_last_time = time.time()
def change_ext(file, newext):
if newext and (not newext.startswith(".")):
newext = "." + newext
return os.path.splitext(file)[0] + newext
def get_median(file):
cmd1 = "dcraw -c -D -4 -o 0 '%s'" % file
cmd2 = "convert - -type Grayscale -scale 500x500 -format %c histogram:info:-"
#~ print cmd1, "|", cmd2
p1 = subprocess.Popen(shlex.split(cmd1), stdout=subprocess.PIPE)
p2 = subprocess.Popen(shlex.split(cmd2), stdin=p1.stdout, stdout=subprocess.PIPE)
lines = p2.communicate()[0].split("\n")
X = []
for l in lines[1:]:
p1 = l.find("(")
if p1 > 0:
p2 = l.find(",", p1)
level = int(l[p1+1:p2])
count = int(l[:p1-2])
X += [level]*count
m = median(X)
return m
ion()
progress("Analyzing RAW exposures...");
files = sorted(os.listdir("raw"))
i = 0;
M = [];
for k,f in enumerate(files):
m = get_median(os.path.join('raw', f))
M.append(m);
E = [-log2(m/M[0]) for m in M]
E = detrend(array(E))
cla(); stem(range(1,len(E)+1), E);
xlabel('Image number')
ylabel('Exposure correction (EV)')
title(f)
draw();
progress(k / len(files))
progress("Developing JPG images...");
i = 0;
for k,f in enumerate(files):
ec = 2 + E[k];
cmd = "ufraw-batch --out-type=jpg --overwrite --clip=film --saturation=2 --exposure=%s '%s' --output='jpg/%s'" % (ec, os.path.join("raw", f), change_ext(f, ".jpg"))
os.system(cmd)
progress(k / len(files))
