def zoom(x, zoom_range=(0.9, 1.1), is_random=False, row_index=0, col_index=1, channel_index=2,
fill_mode='nearest', cval=0.):
"""Zoom in and out of a single image, randomly or non-randomly.
Parameters
-----------
x : numpy array
An image with dimension of [row, col, channel] (default).
zoom_range : list or tuple
- If is_random=False, (h, w) are the fixed zoom factor for row and column axies, factor small than one is zoom in.
- If is_random=True, (min zoom out, max zoom out) for x and y with different random zoom in/out factor.
e.g (0.5, 1) zoom in 1~2 times.
is_random : boolean, default False
If True, randomly zoom.
row_index, col_index, channel_index : int
Index of row, col and channel, default (0, 1, 2), for theano (1, 2, 0).
fill_mode : string
Method to fill missing pixel, default ‘nearest’, more options ‘constant’, ‘reflect’ or ‘wrap’.
- `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`_
cval : scalar, optional
Value used for points outside the boundaries of the input if mode='constant'. Default is 0.0.
- `scipy ndimage affine_transform <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.ndimage.interpolation.affine_transform.html>`_
"""
if len(zoom_range) != 2:
raise Exception('zoom_range should be a tuple or list of two floats. '
'Received arg: ', zoom_range)
if is_random:
if zoom_range[0] == 1 and zoom_range[1] == 1:
zx, zy = 1, 1
print(" random_zoom : not zoom in/out")
else:
zx, zy = np.random.uniform(zoom_range[0], zoom_range[1], 2)
else:
zx, zy = zoom_range
# print(zx, zy)
zoom_matrix = np.array([[zx, 0, 0],
[0, zy, 0],
[0, 0, 1]])
h, w = x.shape[row_index], x.shape[col_index]
transform_matrix = transform_matrix_offset_center(zoom_matrix, h, w)
x = apply_transform(x, transform_matrix, channel_index, fill_mode, cval)
return x
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