img_as_ubyte skimage.util.img_as_ubyte(image, force_copy=False) [source] Convert an image to 8-bit unsigned integer format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of ubyte (uint8) Output image. Notes Negative input values will be clipped. Positive values are scaled between 0 and 255.

img_as_ubyte skimage.img_as_ubyte(image, force_copy=False) [source] Convert an image to 8-bit unsigned integer format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of ubyte (uint8) Output image. Notes Negative input values will be clipped. Positive values are scaled between 0 and 255.

img_as_int skimage.util.img_as_int(image, force_copy=False) [source] Convert an image to 16-bit signed integer format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of uint16 Output image. Notes The values are scaled between -32768 and 32767. If the input data-type is positive-only (e.g., uint8), then the output image will still only have positive values.

img_as_int skimage.img_as_int(image, force_copy=False) [source] Convert an image to 16-bit signed integer format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of uint16 Output image. Notes The values are scaled between -32768 and 32767. If the input data-type is positive-only (e.g., uint8), then the output image will still only have positive values.

img_as_float skimage.util.img_as_float(image, force_copy=False) [source] Convert an image to double-precision floating point format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of float64 Output image. Notes The range of a floating point image is [0.0, 1.0] or [-1.0, 1.0] when converting from unsigned or signed datatypes, respectively.

img_as_float skimage.img_as_float(image, force_copy=False) [source] Convert an image to double-precision floating point format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of float64 Output image. Notes The range of a floating point image is [0.0, 1.0] or [-1.0, 1.0] when converting from unsigned or signed datatypes, respectively.

img_as_bool skimage.util.img_as_bool(image, force_copy=False) [source] Convert an image to boolean format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of bool (bool_) Output image. Notes The upper half of the input dtype’s positive range is True, and the lower half is False. All negative values (if present) are False.

img_as_bool skimage.img_as_bool(image, force_copy=False) [source] Convert an image to boolean format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of bool (bool_) Output image. Notes The upper half of the input dtype’s positive range is True, and the lower half is False. All negative values (if present) are False.

ImageViewer class skimage.viewer.viewers.ImageViewer(image, useblit=True) [source] Bases: PyQt4.QtGui.QMainWindow Viewer for displaying images. This viewer is a simple container object that holds a Matplotlib axes for showing images. ImageViewer doesn’t subclass the Matplotlib axes (or figure) because of the high probability of name collisions. Subclasses and plugins will likely extend the update_image method to add custom overlays or filter the displayed image. Parameters: image : array I

ImageViewer class skimage.viewer.ImageViewer(image, useblit=True) [source] Bases: PyQt4.QtGui.QMainWindow Viewer for displaying images. This viewer is a simple container object that holds a Matplotlib axes for showing images. ImageViewer doesn’t subclass the Matplotlib axes (or figure) because of the high probability of name collisions. Subclasses and plugins will likely extend the update_image method to add custom overlays or filter the displayed image. Parameters: image : array Image bei