def load(self, data):
"""Loads data into a Hologram object.
The data can either be a numpy array already in memory or a filename
to read from disk using opencv.
If the data is a numpy array, it is assumed to be floating point and
single channel.
If the data is a string, it is treated as a file on disk. The file is
read into an array, converted to grayscale if it is 3-channel, and
divided by 255 to convert to floating point."""
if isinstance(data, basestring):
img = cv2utils.imread(data)
if imageutils.nchannels(img) == 3:
print "Converting 3-channel image to grayscale..."
img = cv2color.bgr2gray(img)
self.data = img / 255. #converts to float, [0..1] range
elif isinstance(data, numpy.ndarray):
self.data = data
else:
raise TypeError("Must be a numpy array or a filename.")
def test_image(image_name=None):
"""Loads a test image with the closest match to the supplied name."""
test_image_dir = image_dir()
available_images = dir_by_ext(image_dir(), IMAGE_EXT)
if image_name is None:
print 'Available images are: %s' % available_images
return None
#find the matching image names
assert(isinstance(image_name, basestring))
matches = [file_name for file_name in available_images
if file_name.startswith(image_name)]
if len(matches) == 0:
print 'No name match found for %s.' % image_name
return None
elif len(matches) > 1:
print 'Multiple matches found for %s: %s.' % (image_name, matches)
return None
else:
#load the matching image
filename = os.path.join(test_image_dir, matches[0])
print 'loading: %s' % filename
return cv2utils.imread(filename)