Created
November 7, 2013 19:41
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Graph the corresponding pixel values in a sequence of images to assert linearity.
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from __future__ import division | |
from argparse import ArgumentParser | |
import math | |
import os | |
import sys | |
import matplotlib.pyplot as plt | |
import numpy as np | |
import cv2 | |
arg_parser = ArgumentParser() | |
arg_parser.add_argument('-k', '--like') | |
arg_parser.add_argument('-s', '--sample', action='append') | |
arg_parser.add_argument('-a', '--all-channels', action='store_true') | |
arg_parser.add_argument('-r', '--reference', type=int, default=-1) | |
arg_parser.add_argument('-c', '--count', type=int, default=5) | |
arg_parser.add_argument('-t', '--title') | |
arg_parser.add_argument('src', nargs=1) | |
arg_parser.add_argument('dst', nargs='?') | |
args = arg_parser.parse_args() | |
src = args.src[0] | |
max_value = 2.0 ** 16 | |
images = [cv2.imread(os.path.join(src, name), -1) for name in os.listdir(src)] | |
images = [img / max_value for img in images] | |
args.reference = args.reference if args.reference >= 0 else len(images) // 2 | |
ax = plt.axes() | |
plt.xlabel('Relative Camera Exposure (1/3 stops)') | |
plt.ylabel('Relative Pixel Values (log2)') | |
if args.title: | |
plt.title(args.title) | |
sample_coords = [(x, y) for x in xrange(1, images[0].shape[0] - 1) for y in xrange(1, images[0].shape[1] - 1)] | |
if args.like: | |
selector = np.array([float(x) for x in args.like.split(',')]) | |
selector_inv = 1 - selector | |
def score(coord): | |
x, y = coord | |
color = images[args.reference][x, y] | |
score = np.sum(color * selector - color * selector_inv) / np.sum(color) | |
return score | |
sample_coords.sort(key=score, reverse=True) | |
sample_coords = sample_coords[:args.count] | |
print 'Samples:' | |
for x, y in sample_coords: | |
print '\t%d, %d' % (x, y) | |
if args.sample: | |
sample_coords = [[int(x) for x in s.split(',')] for s in args.sample] | |
indices = range(len(images)) | |
for x, y in sample_coords: | |
if args.all_channels: | |
for c in (0, 1, 2): | |
values = [np.log2(images[i][x, y, c]) for i in indices] | |
color = [int(i == c) for i in (0, 1, 2)] | |
ax.plot(indices, values, '-', color=color) | |
else: | |
values = [np.log2(np.sum(images[i][x, y]) / 3) for i in indices] | |
color = images[args.reference][x, y] | |
ax.plot(indices, values, '-', color=color) | |
plt.xlim(0, len(images) - 1) | |
if args.dst: | |
plt.savefig(args.dst, bbox_inches=0) | |
else: | |
plt.show() |
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