Python Tools for Pixel-by-Pixel Image Comparison

chrome/test/functional/ispy/image_tools.py

+# Copyright (c) 2013 The Chromium Authors. All rights reserved.
+# Use of this source code is governed by a BSD-style license that can be
+# found in the LICENSE file.
+
+"""Utilities for performing pixel-by-pixel image comparison."""
+
+
+import itertools
+import math
+import PIL
+
+
+def _AreTheSameSize(images):
+  """Returns whether a set of images are the same size.
+
+  Args:
+    images: a list of images to compare
+
+  Returns:
+    boolean
+
+  Raises:
+    Exception: One image or fewer is passed in.
+  """
+  if len(images) > 1:
+    return not any(images[0].size != img.size for img in images[1:])
+  else:
+    raise Exception('No images passed in')
+
+
+def _GetColorDist(px1, px2):
+  """Returns the normalized color distance between pixels.
+
+  This function gets the color distance between two pixels and
+  returns a number between 0 and 1 where 0 is lowest distance
+  and 1 is the greatest distance.
+
+  Args:
+    px1: a 3-tuple (R,G,B)
+    px2: a 3-tuple (R,G,B)
+
+  Returns:
+    a number between 0 and 1
+  """
+  return sum(
+      (ch1 - ch2) ** 2
+      for ch1, ch2 in itertools.izip(px1[0:3], px2[0:3])
+      ) / 195075.  # 3*255**2
+
+
+def _GetColorDistAsColor(px1, px2):
+  """Computes Color Distance as a greyscale pixel.
+
+  This function gets the color distance between two pixels
+  represented as a pixel ranging in color from (0,0,0) to
+  (255,255,255).
+
+  Args:
+    px1: a 3-tuple (R,G,B)
+    px2: a 3-tuple (R,G,B)
+
+  Returns:
+    a 3-tuple between (0,0,0) and (255,255,255)
+  """
+  n = _GetColorDist(px1, px2)
+  return (int(math.ceil(255 * n)),
+          int(math.ceil(255 * n)),
+          int(math.ceil(255 * n)))
+
+
+def _Brightness(px):
+  """Gets the brightness of a pixel.
+
+  Returns the sum of a given pixel's color channels.
+
+  Args:
+    px: a 3-tuple (R,G,B)
+
+  Returns:
+    a number between 0 and 3*255
+  """
+  return sum(px)
+
+
+def _MinPixel(px1, px2):
+  """Gets the pixel with the lower brightness.
+
+  Calculates the brightness of each pixel and returns
+  the pixel with the lower brightness.
+
+  Args:
+    px1: a 3-tuple (R,G,B)
+    px2: a 3-tuple (R,G,B)
+
+  Returns:
+    a 3-tuple (R,G,B)
+  """
+  if _Brightness(px1) < _Brightness(px2):
+    return px1
+  else:
+    return px2
+
+
+def _MaxPixel(px1, px2):
+  """gets the pixel with the greater brightness.
+
+  Calculates the brightness of each pixel and returns
+  the pixel with the greater brightness.
+
+  Args:
+    px1: a 3-tuple (R,G,B)
+    px2: a 3-tuple (R,G,B)
+
+  Returns:
+    a 3-tuple (R,G,B)
+  """
+  if _Brightness(px1) < _Brightness(px2):
+    return px2
+  else:
+    return px1
+
+
+def CreateMask(images, threshold=True, cutoff=0):
+  """Computes a mask for a set of images.
+
+  Returns an image that is computed from the images
+  passed in. The mask's values are computed by calculating
+  total differences between the image, and storing them
+  such that (255,255,255) represents great difference,
+  and (0,0,0) represents no difference. If is_hard is
+  True, the resulting mask is put through a
+  thresholding pass where pixel values below the
+  cutoff become (0,0,0) and ones above become (255,255,255).
+
+  Args:
+    images: the images to compute the mask from
+    threshold: boolean, whether or not to threshold the mask
+    cutoff: number, the value to threshold the mask at
+
+  Returns:
+    an image that is a mask of the passed in images.
+
+  Raises:
+    Exception: if the images passed in are not of the same size
+  """
+  if not _AreTheSameSize(images):
+    raise Exception('All images must be the same size')
+  mask = PIL.Image.new('RGB', images[0].size)
+  mask_data = mask.getdata()
+  image_data = images[0].getdata()
+  for other_image in images[1:]:
+    mask_data = _ComputeLargestDifference(mask_data, image_data,
+                                          other_image.getdata())
+
+  if threshold:
+    mask.putdata([
+        (255, 255, 255) if _Brightness(px) > cutoff
+        else (0, 0, 0)
+        for px in mask_data
+        ])
+  else:
+    mask.putdata(list(mask_data))
+  return mask
+
+
+def _ComputeLargestDifference(mask_data, image_data1, image_data2):
+  """Modifies a mask based upon a comparision of two images.
+
+  A helper function used to generate masks. The mask, as
+  it exists when the function is called, is compared to two
+  images on a pixel-by-pixel basis. For each pixel, the
+  ColorDistance between the two images is computed as a Color,
+  and compared against the color of the mask at the same
+  pixel. The brightest of these pixels is chosen for pixel
+  in the images/mask, and a new set of pixels is returned.
+
+  Args:
+    mask_data: a list of pixels of the mask
+    image_data1: a list of pixels of an image
+    image_data2: a list of pixels of another image
+
+  Returns:
+    a list of pixels representing a modified version of the mask.
+  """
+  return (
+      _MaxPixel(m, _GetColorDistAsColor(i1, i2))
+      for m, i1, i2 in itertools.izip(mask_data, image_data1, image_data2)
+      )
+
+
+def _ThresholdColorDiff(px1, px2, cutoff):
+  """Thresholds the color distance of two pixels.
+
+  Computes a Threshold of the color distance of two pixels,
+  if the normalized color distance of px1 and px2 is greater than
+  cutoff, returns 1. otherwise returns 0.
+
+  Args:
+    px1: a 3-tuple (R,G,B)
+    px2: a 3-tuple (R,G,B)
+    cutoff: a number used as the threshold limit
+
+  Returns:
+    either 1. or 0. depending on the distance of px1 and px2.
+  """
+  diff = _GetColorDist(px1, px2)
+  if diff > cutoff:
+    return 1
+  else:
+    return 0
+
+
+def _MaskToValue(px):
+  """Converts a black or white pixel to 1. or 0.
+
+  Args:
+    px: a 3-tuple (R,G,B)
+
+  Returns:
+    1. if the pixel is (0,0,0), 0. if the pixel is (255,255,255)
+
+  Raises:
+    Exception: if the pixel is not (0,0,0) or (255,255,255)
+  """
+  if px[0:3] == (0, 0, 0):
+    return 1.
+  if px[0:3] == (255, 255, 255):
+    return 0.
+  else:
+    raise Exception('Mask may only contain black or white pixels')
+
+
+def TotalDifferentPixels(image1, image2, mask=None):
+  """Computes the number of different pixels between two images.
+
+  Args:
+    image1: the first Image to be compared
+    image2: the second Image to be compared
+    mask: an optional mask to occlude parts of the images
+     from calculation
+
+  Returns:
+    the number of differing pixels between the images.
+
+  Raises:
+    Exception: if the images to be compared and mask are not the same size.
+  """
+  if mask:
+    if _AreTheSameSize([image1, image2, mask]):
+      return sum(
+          _MaskToValue(m) * _ThresholdColorDiff(px1, px2, 0)
+          for m, px1, px2 in itertools.izip(mask.getdata(),
+                                            image1.getdata(),
+                                            image2.getdata())
+          )
+    else:
+      raise Exception('images and mask must be the same size')
+  else:
+    if _AreTheSameSize([image1, image2]):
+      return sum(
+          _ThresholdColorDiff(px1, px2, 0)
+          for px1, px2 in itertools.izip(
+              image1.getdata(),
+              image2.getdata()
+              )
+          )
+    else:
+      raise Exception('images and mask must be the same size')
+
+
+def SameImage(image1, image2, max_different_pixels=0, mask=None):
+  """Returns a boolean representing whether the images are the same.
+
+  Returns a boolean indicating whether two images
+  are similar enough to be considered the same. Essentially
+  wraps the Similarity function and adds a max_different_pixels
+  cutoff for Sameness.

[frankf, 2013/06/17 21:48:31]

I don't thinkg Sameness has defined meaning. "Similarity" is a well-defined term
though.

[cgrimm, 2013/06/17 23:41:18]

Done.

+
+  Args:
+    image1: an Image to compare

[frankf, 2013/06/17 21:48:31]

Document how this is encoded

[cgrimm, 2013/06/17 23:41:18]

Done.

+    image2: an Image to compare
+    max_different_pixels: a number that is the cutoff for image sameness

[frankf, 2013/06/17 21:48:31]

Once you add this threshold, then this brute force algorithm might not be
sufficient. There are much more sophisticated algorithms for image similarity
that deal with "fuzziness" much better:
http://stackoverflow.com/questions/843972/image-comparison-fast-algorithm

[cgrimm, 2013/06/17 23:41:18]

resolved

+    mask: an optional Image that occludes parts of the images from
+     same-ness calculation
+
+  Returns:
+    a boolean representing if the images are the same.

[frankf, 2013/06/17 21:48:31]

"True if the images are similar, false otherwise"

[cgrimm, 2013/06/17 23:41:18]

Done.

+
+  Raises:
+    Error: if the images (and mask) are different sizes.

[frankf, 2013/06/17 21:48:31]

Is Error a type of exception?

[cgrimm, 2013/06/17 23:41:18]

This is a remnant from when I had a subclass of Exception called Error. I
noticed it shortly after I submitted the CL, it's fixed now. 

+  """
+
+  different_pixels = TotalDifferentPixels(image1, image2, mask)
+  return different_pixels <= max_different_pixels