def __init__(self, img, gaussian_kernel_1d=None, size=None):
"""Create an SSIMImage.
Args:
img (str or PIL.Image): PIL Image object or file name.
gaussian_kernel_1d (np.ndarray, optional): Gaussian kernel
that was generated with utils.get_gaussian_kernel is used
to precompute common objects for SSIM computation
size (tuple, optional): New image size to resize image to.
"""
# Use existing or create a new PIL.Image
try:
self.img = img if not isinstance(img, compat.basestring) \
else compat.Image.open(img)
except IOError as e:
logging.debug("Unable to open %s" % img)
raise IOError("Image probably malformed")
# Resize image if size is defined and different
# from original image
if size and size != self.img.size:
self.img = self.img.resize(size, Image.ANTIALIAS)
# Set the size of the image
self.size = self.img.size
# If gaussian kernel is defined we create
# common SSIM objects
if gaussian_kernel_1d is not None:
self.gaussian_kernel_1d = gaussian_kernel_1d
# np.array of grayscale and alpha image
self.img_gray, self.img_alpha = to_grayscale(self.img)
if self.img_alpha is not None:
self.img_gray[self.img_alpha == 255] = 0
# Squared grayscale
self.img_gray_squared = self.img_gray**2
# Convolve grayscale image with gaussian
self.img_gray_mu = convolve_gaussian_2d(self.img_gray,
self.gaussian_kernel_1d)
# Squared mu
self.img_gray_mu_squared = self.img_gray_mu**2
# Convolve squared grayscale with gaussian
self.img_gray_sigma_squared = convolve_gaussian_2d(
self.img_gray_squared, self.gaussian_kernel_1d)
# Substract squared mu
self.img_gray_sigma_squared -= self.img_gray_mu_squared
# If we don't define gaussian kernel, we create
# common CW-SSIM objects
else:
# Grayscale PIL.Image
self.img_gray = ImageOps.grayscale(self.img)
def __init__(self, img, gaussian_kernel_1d=None, size=None):
"""Create an SSIMImage.
Args:
img (str or PIL.Image): PIL Image object or file name.
gaussian_kernel_1d (np.ndarray, optional): Gaussian kernel
that was generated with utils.get_gaussian_kernel is used
to precompute common objects for SSIM computation
size (tuple, optional): New image size to resize image to.
"""
# Use existing or create a new PIL.Image
try:
self.img = img if not isinstance(img, compat.basestring) else compat.Image.open(img)
except IOError as e:
logging.debug("Unable to open %s" % img)
raise IOError("Image probably malformed")
# Resize image if size is defined and different
# from original image
if size and size != self.img.size:
self.img = self.img.resize(size, Image.ANTIALIAS)
# Set the size of the image
self.size = self.img.size
# If gaussian kernel is defined we create
# common SSIM objects
if gaussian_kernel_1d is not None:
self.gaussian_kernel_1d = gaussian_kernel_1d
# np.array of grayscale and alpha image
self.img_gray, self.img_alpha = to_grayscale(self.img)
if self.img_alpha is not None:
self.img_gray[self.img_alpha == 255] = 0
# Squared grayscale
self.img_gray_squared = self.img_gray ** 2
# Convolve grayscale image with gaussian
self.img_gray_mu = convolve_gaussian_2d(self.img_gray, self.gaussian_kernel_1d)
# Squared mu
self.img_gray_mu_squared = self.img_gray_mu ** 2
# Convolve squared grayscale with gaussian
self.img_gray_sigma_squared = convolve_gaussian_2d(self.img_gray_squared, self.gaussian_kernel_1d)
# Substract squared mu
self.img_gray_sigma_squared -= self.img_gray_mu_squared
# If we don't define gaussian kernel, we create
# common CW-SSIM objects
else:
# Grayscale PIL.Image
self.img_gray = ImageOps.grayscale(self.img)
def to_grayscale(img):
"""Convert PIL image to numpy grayscale array and numpy alpha array.
Args:
img (PIL.Image): PIL Image object.
Returns:
(gray, alpha): both numpy arrays.
"""
gray = numpy.asarray(ImageOps.grayscale(img)).astype(numpy.float)
imbands = img.getbands()
alpha = None
if 'A' in imbands:
alpha = numpy.asarray(img.split()[-1]).astype(numpy.float)
return gray, alpha
def to_grayscale(image):
"""Convert PIL image to numpy grayscale array and numpy alpha array.
Args:
im: PIL Image object.
Returns:
(gray, alpha), both numpy arrays.
"""
gray = numpy.asarray(ImageOps.grayscale(image)).astype(numpy.float)
imbands = image.getbands()
alpha = None
if "A" in imbands:
alpha = numpy.asarray(image.split()[-1]).astype(numpy.float)
return gray, alpha