def resize(self, shape, electrodes=None):
"""Resize the image
Parameters
----------
shape : (rows, cols)
Shape of the resized image
electrodes : int, string or list thereof; optional
Optionally, you can provide your own electrode names. If none are
given, electrode names will be numbered 0..N.
.. note::
The number of electrode names provided must match the number of
pixels in the grayscale image.
Returns
-------
stim : `ImageStimulus`
A copy of the stimulus object containing the resized image
"""
height, width = shape
if height < 0 and width < 0:
raise ValueError('"height" and "width" cannot both be -1.')
if height < 0:
height = int(self.img_shape[0] * width / self.img_shape[1])
if width < 0:
width = int(self.img_shape[1] * height / self.img_shape[0])
img = img_resize(self.data.reshape(self.img_shape), (height, width))
return ImageStimulus(img,
electrodes=electrodes,
metadata=self.metadata)
def _render(display, screen_img):
img2draw = img_resize(image=np.flipud(np.rot90(screen_img)),
output_shape=(500, 500),
preserve_range=True)
main_surface = pygame.surfarray.make_surface(img2draw)
display.fill(color="black")
display.blit(main_surface, [0, 0])
pygame.display.update()
def __init__(self,
source,
format=None,
resize=None,
as_gray=False,
electrodes=None,
metadata=None,
compress=False):
if metadata is None:
metadata = {}
elif type(metadata) != dict:
metadata = {'user': metadata}
if isinstance(source, str):
# Filename provided:
img = imread(source, format=format)
metadata['source'] = source
metadata['source_shape'] = img.shape
elif isinstance(source, ImageStimulus):
img = source.data.reshape(source.img_shape)
metadata.update(source.metadata)
if electrodes is None:
electrodes = source.electrodes
elif isinstance(source, np.ndarray):
img = source
else:
raise TypeError("Source must be a filename or another "
"ImageStimulus, not %s." % type(source))
if img.ndim < 2 or img.ndim > 3:
raise ValueError("Images must have 2 or 3 dimensions, not "
"%d." % img.ndim)
# Convert to grayscale if necessary:
if as_gray:
if img.ndim == 3 and img.shape[2] == 4:
# Blend the background with black:
img = rgba2rgb(img, background=(0, 0, 0))
if img.ndim == 3:
img = rgb2gray(img)
# Resize if necessary:
if resize is not None:
height, width = resize
if height < 0 and width < 0:
raise ValueError('"height" and "width" cannot both be -1.')
if height < 0:
height = int(img.shape[0] * width / img.shape[1])
if width < 0:
width = int(img.shape[1] * height / img.shape[0])
img = img_resize(img, (height, width))
# Store the original image shape for resizing and color conversion:
self.img_shape = img.shape
# Convert to float array in [0, 1] and call the Stimulus constructor:
super(ImageStimulus, self).__init__(img_as_float32(img).ravel(),
time=None,
electrodes=electrodes,
metadata=metadata,
compress=compress)
self.metadata = metadata
def resize(self, shape, electrodes=None):
img = img_resize(self.data.reshape(self.img_shape), shape)
if electrodes is None:
electrodes = np.arange(img.size)
self._stim = {
'data': img.reshape((-1, 1)),
'electrodes': electrodes,
'time': None
}
self.img_shape = img.shape
return self
def __init__(self, fname, format=None, resize=None, as_gray=False,
electrodes=None, metadata=None, compress=False):
img = imread(fname, format=format)
# Build the metadata container:
if metadata is None:
metadata = {}
metadata['source'] = fname
metadata['source_shape'] = img.shape
# Convert to grayscale if necessary:
if as_gray:
if img.shape[-1] == 4:
# Convert the transparent background to black:
img = rgba2rgb(img, background=(0, 0, 0))
img = rgb2gray(img)
# Resize if necessary:
if resize is not None:
img = img_resize(img, resize)
# Store the original image shape for resizing and color conversion:
self.img_shape = img.shape
# Convert to float array in [0, 1] and call the Stimulus constructor:
super(ImageStimulus, self).__init__(img_as_float(img).ravel(),
time=None, electrodes=electrodes,
metadata=metadata,
compress=compress)
