INSTRUCTION stringlengths 1 8.43k | RESPONSE stringlengths 75 104k |
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T. set_default ( k [ d ] ) - > T. get ( k d ) also set T [ k ] = d if k not in T | def set_default(self, key, default=None):
"""T.set_default(k[,d]) -> T.get(k,d), also set T[k]=d if k not in T"""
try:
return self.get_value(key)
except KeyError:
self.insert(key, default)
return default |
T. pop ( k [ d ] ) - > v remove specified key and return the corresponding value. If key is not found d is returned if given otherwise KeyError is raised | def pop(self, key, *args):
"""T.pop(k[,d]) -> v, remove specified key and return the corresponding value.
If key is not found, d is returned if given, otherwise KeyError is raised
"""
if len(args) > 1:
raise TypeError("pop expected at most 2 arguments, got %d" % (1 + len(args... |
Get predecessor to key raises KeyError if key is min key or key does not exist. | def prev_key(self, key, default=_sentinel):
"""Get predecessor to key, raises KeyError if key is min key
or key does not exist.
"""
item = self.prev_item(key, default)
return default if item is default else item[0] |
Get successor to key raises KeyError if key is max key or key does not exist. | def succ_key(self, key, default=_sentinel):
"""Get successor to key, raises KeyError if key is max key
or key does not exist.
"""
item = self.succ_item(key, default)
return default if item is default else item[0] |
T. key_slice ( start_key end_key ) - > key iterator: start_key < = key < end_key. | def key_slice(self, start_key, end_key, reverse=False):
"""T.key_slice(start_key, end_key) -> key iterator:
start_key <= key < end_key.
Yields keys in ascending order if reverse is False else in descending order.
"""
return (k for k, v in self.iter_items(start_key, end_key, reve... |
Iterates over the ( key value ) items of the associated tree in ascending order if reverse is True iterate in descending order reverse defaults to False | def iter_items(self, start_key=None, end_key=None, reverse=False):
"""Iterates over the (key, value) items of the associated tree,
in ascending order if reverse is True, iterate in descending order,
reverse defaults to False"""
# optimized iterator (reduced method calls) - faster on CPy... |
T. insert ( key value ) < == > T [ key ] = value insert key value into tree. | def insert(self, key, value):
"""T.insert(key, value) <==> T[key] = value, insert key, value into tree."""
if self._root is None: # Empty tree case
self._root = self._new_node(key, value)
self._root.red = False # make root black
return
head = Node() # Fals... |
T. remove ( key ) < == > del T [ key ] remove item <key > from tree. | def remove(self, key):
"""T.remove(key) <==> del T[key], remove item <key> from tree."""
if self._root is None:
raise KeyError(str(key))
head = Node() # False tree root
node = head
node.right = self._root
parent = None
grand_parent = None
foun... |
Generate 2D OpenSimplex noise from X Y coordinates. | def noise2d(self, x, y):
"""
Generate 2D OpenSimplex noise from X,Y coordinates.
"""
# Place input coordinates onto grid.
stretch_offset = (x + y) * STRETCH_CONSTANT_2D
xs = x + stretch_offset
ys = y + stretch_offset
# Floor to get grid coordinates of rho... |
Generate 3D OpenSimplex noise from X Y Z coordinates. | def noise3d(self, x, y, z):
"""
Generate 3D OpenSimplex noise from X,Y,Z coordinates.
"""
# Place input coordinates on simplectic honeycomb.
stretch_offset = (x + y + z) * STRETCH_CONSTANT_3D
xs = x + stretch_offset
ys = y + stretch_offset
zs = z + stretch... |
Generate 4D OpenSimplex noise from X Y Z W coordinates. | def noise4d(self, x, y, z, w):
"""
Generate 4D OpenSimplex noise from X,Y,Z,W coordinates.
"""
# Place input coordinates on simplectic honeycomb.
stretch_offset = (x + y + z + w) * STRETCH_CONSTANT_4D
xs = x + stretch_offset
ys = y + stretch_offset
zs = z ... |
Adjust contrast by scaling each pixel value to 255 * (( I_ij/ 255 ) ** gamma ). | def adjust_contrast_gamma(arr, gamma):
"""
Adjust contrast by scaling each pixel value to ``255 * ((I_ij/255)**gamma)``.
dtype support::
* ``uint8``: yes; fully tested (1) (2) (3)
* ``uint16``: yes; tested (2) (3)
* ``uint32``: yes; tested (2) (3)
* ``uint64``: yes; tested ... |
Adjust contrast by scaling each pixel value to 255 * 1/ ( 1 + exp ( gain * ( cutoff - I_ij/ 255 ))). | def adjust_contrast_sigmoid(arr, gain, cutoff):
"""
Adjust contrast by scaling each pixel value to ``255 * 1/(1 + exp(gain*(cutoff - I_ij/255)))``.
dtype support::
* ``uint8``: yes; fully tested (1) (2) (3)
* ``uint16``: yes; tested (2) (3)
* ``uint32``: yes; tested (2) (3)
... |
Adjust contrast by scaling each pixel value to 255 * gain * log_2 ( 1 + I_ij/ 255 ). | def adjust_contrast_log(arr, gain):
"""
Adjust contrast by scaling each pixel value to ``255 * gain * log_2(1 + I_ij/255)``.
dtype support::
* ``uint8``: yes; fully tested (1) (2) (3)
* ``uint16``: yes; tested (2) (3)
* ``uint32``: yes; tested (2) (3)
* ``uint64``: yes; tes... |
Adjust contrast by scaling each pixel value to 127 + alpha * ( I_ij - 127 ). | def adjust_contrast_linear(arr, alpha):
"""Adjust contrast by scaling each pixel value to ``127 + alpha*(I_ij-127)``.
dtype support::
* ``uint8``: yes; fully tested (1) (2)
* ``uint16``: yes; tested (2)
* ``uint32``: yes; tested (2)
* ``uint64``: no (3)
* ``int8``: yes;... |
Adjust contrast by scaling each pixel value to 255 * (( I_ij/ 255 ) ** gamma ). | def GammaContrast(gamma=1, per_channel=False, name=None, deterministic=False, random_state=None):
"""
Adjust contrast by scaling each pixel value to ``255 * ((I_ij/255)**gamma)``.
Values in the range ``gamma=(0.5, 2.0)`` seem to be sensible.
dtype support::
See :func:`imgaug.augmenters.contra... |
Adjust contrast by scaling each pixel value to 255 * 1/ ( 1 + exp ( gain * ( cutoff - I_ij/ 255 ))). | def SigmoidContrast(gain=10, cutoff=0.5, per_channel=False, name=None, deterministic=False, random_state=None):
"""
Adjust contrast by scaling each pixel value to ``255 * 1/(1 + exp(gain*(cutoff - I_ij/255)))``.
Values in the range ``gain=(5, 20)`` and ``cutoff=(0.25, 0.75)`` seem to be sensible.
dtyp... |
Adjust contrast by scaling each pixel value to 255 * gain * log_2 ( 1 + I_ij/ 255 ). | def LogContrast(gain=1, per_channel=False, name=None, deterministic=False, random_state=None):
"""
Adjust contrast by scaling each pixel value to ``255 * gain * log_2(1 + I_ij/255)``.
dtype support::
See :func:`imgaug.augmenters.contrast.adjust_contrast_log`.
Parameters
----------
gai... |
Adjust contrast by scaling each pixel value to 127 + alpha * ( I_ij - 127 ). | def LinearContrast(alpha=1, per_channel=False, name=None, deterministic=False, random_state=None):
"""Adjust contrast by scaling each pixel value to ``127 + alpha*(I_ij-127)``.
dtype support::
See :func:`imgaug.augmenters.contrast.adjust_contrast_linear`.
Parameters
----------
alpha : num... |
Convert images to another colorspace. | def InColorspace(to_colorspace, from_colorspace="RGB", children=None, name=None, deterministic=False,
random_state=None):
"""Convert images to another colorspace."""
return WithColorspace(to_colorspace, from_colorspace, children, name, deterministic, random_state) |
Augmenter to convert images to their grayscale versions. | def Grayscale(alpha=0, from_colorspace="RGB", name=None, deterministic=False, random_state=None):
"""
Augmenter to convert images to their grayscale versions.
NOTE: Number of output channels is still 3, i.e. this augmenter just "removes" color.
TODO check dtype support
dtype support::
* ... |
Get the height of a bounding box encapsulating the line. | def height(self):
"""Get the height of a bounding box encapsulating the line."""
if len(self.coords) <= 1:
return 0
return np.max(self.yy) - np.min(self.yy) |
Get the width of a bounding box encapsulating the line. | def width(self):
"""Get the width of a bounding box encapsulating the line."""
if len(self.coords) <= 1:
return 0
return np.max(self.xx) - np.min(self.xx) |
Get for each point whether it is inside of the given image plane. | def get_pointwise_inside_image_mask(self, image):
"""
Get for each point whether it is inside of the given image plane.
Parameters
----------
image : ndarray or tuple of int
Either an image with shape ``(H,W,[C])`` or a tuple denoting
such an image shape.... |
Get the euclidean distance between each two consecutive points. | def compute_neighbour_distances(self):
"""
Get the euclidean distance between each two consecutive points.
Returns
-------
ndarray
Euclidean distances between point pairs.
Same order as in `coords`. For ``N`` points, ``N-1`` distances
are retu... |
Compute the minimal distance between each point on self and other. | def compute_pointwise_distances(self, other, default=None):
"""
Compute the minimal distance between each point on self and other.
Parameters
----------
other : tuple of number \
or imgaug.augmentables.kps.Keypoint \
or imgaug.augmentables.LineStr... |
Compute the minimal distance between the line string and other. | def compute_distance(self, other, default=None):
"""
Compute the minimal distance between the line string and `other`.
Parameters
----------
other : tuple of number \
or imgaug.augmentables.kps.Keypoint \
or imgaug.augmentables.LineString
... |
Estimate whether the bounding box contains a point. | def contains(self, other, max_distance=1e-4):
"""
Estimate whether the bounding box contains a point.
Parameters
----------
other : tuple of number or imgaug.augmentables.kps.Keypoint
Point to check for.
max_distance : float
Maximum allowed eucli... |
Project the line string onto a differently shaped image. | def project(self, from_shape, to_shape):
"""
Project the line string onto a differently shaped image.
E.g. if a point of the line string is on its original image at
``x=(10 of 100 pixels)`` and ``y=(20 of 100 pixels)`` and is projected
onto a new image with size ``(width=200, he... |
Estimate whether the line string is fully inside the image area. | def is_fully_within_image(self, image, default=False):
"""
Estimate whether the line string is fully inside the image area.
Parameters
----------
image : ndarray or tuple of int
Either an image with shape ``(H,W,[C])`` or a tuple denoting
such an image sh... |
Estimate whether the line string is at least partially inside the image. | def is_partly_within_image(self, image, default=False):
"""
Estimate whether the line string is at least partially inside the image.
Parameters
----------
image : ndarray or tuple of int
Either an image with shape ``(H,W,[C])`` or a tuple denoting
such an... |
Estimate whether the line is partially/ fully outside of the image area. | def is_out_of_image(self, image, fully=True, partly=False, default=True):
"""
Estimate whether the line is partially/fully outside of the image area.
Parameters
----------
image : ndarray or tuple of int
Either an image with shape ``(H,W,[C])`` or a tuple denoting
... |
Clip off all parts of the line_string that are outside of the image. | def clip_out_of_image(self, image):
"""
Clip off all parts of the line_string that are outside of the image.
Parameters
----------
image : ndarray or tuple of int
Either an image with shape ``(H,W,[C])`` or a tuple denoting
such an image shape.
R... |
Find all intersection points between the line string and other. | def find_intersections_with(self, other):
"""
Find all intersection points between the line string and `other`.
Parameters
----------
other : tuple of number or list of tuple of number or \
list of LineString or LineString
The other geometry to use du... |
Shift/ move the line string from one or more image sides. | def shift(self, top=None, right=None, bottom=None, left=None):
"""
Shift/move the line string from one or more image sides.
Parameters
----------
top : None or int, optional
Amount of pixels by which to shift the bounding box from the
top.
right ... |
Draw this line segment as a binary image mask. | def draw_mask(self, image_shape, size_lines=1, size_points=0,
raise_if_out_of_image=False):
"""
Draw this line segment as a binary image mask.
Parameters
----------
image_shape : tuple of int
The shape of the image onto which to draw the line mask.
... |
Draw the line segments of the line string as a heatmap array. | def draw_lines_heatmap_array(self, image_shape, alpha=1.0,
size=1, antialiased=True,
raise_if_out_of_image=False):
"""
Draw the line segments of the line string as a heatmap array.
Parameters
----------
image_shap... |
Draw the points of the line string as a heatmap array. | def draw_points_heatmap_array(self, image_shape, alpha=1.0,
size=1, raise_if_out_of_image=False):
"""
Draw the points of the line string as a heatmap array.
Parameters
----------
image_shape : tuple of int
The shape of the image onto... |
Draw the line segments and points of the line string as a heatmap array. | def draw_heatmap_array(self, image_shape, alpha_lines=1.0, alpha_points=1.0,
size_lines=1, size_points=0, antialiased=True,
raise_if_out_of_image=False):
"""
Draw the line segments and points of the line string as a heatmap array.
Parameters... |
Draw the line segments of the line string on a given image. | def draw_lines_on_image(self, image, color=(0, 255, 0),
alpha=1.0, size=3,
antialiased=True,
raise_if_out_of_image=False):
"""
Draw the line segments of the line string on a given image.
Parameters
-----... |
Draw the points of the line string on a given image. | def draw_points_on_image(self, image, color=(0, 128, 0),
alpha=1.0, size=3,
copy=True, raise_if_out_of_image=False):
"""
Draw the points of the line string on a given image.
Parameters
----------
image : ndarray or tuple ... |
Draw the line string on an image. | def draw_on_image(self, image,
color=(0, 255, 0), color_lines=None, color_points=None,
alpha=1.0, alpha_lines=None, alpha_points=None,
size=1, size_lines=None, size_points=None,
antialiased=True,
raise_if_out_o... |
Extract the image pixels covered by the line string. | def extract_from_image(self, image, size=1, pad=True, pad_max=None,
antialiased=True, prevent_zero_size=True):
"""
Extract the image pixels covered by the line string.
It will only extract pixels overlapped by the line string.
This function will by default ze... |
Concatenate this line string with another one. | def concatenate(self, other):
"""
Concatenate this line string with another one.
This will add a line segment between the end point of this line string
and the start point of `other`.
Parameters
----------
other : imgaug.augmentables.lines.LineString or ndarray ... |
Adds N interpolated points with uniform spacing to each edge. | def subdivide(self, points_per_edge):
"""
Adds ``N`` interpolated points with uniform spacing to each edge.
For each edge between points ``A`` and ``B`` this adds points
at ``A + (i/(1+N)) * (B - A)``, where ``i`` is the index of the added
point and ``N`` is the number of points... |
Convert the line string points to keypoints. | def to_keypoints(self):
"""
Convert the line string points to keypoints.
Returns
-------
list of imgaug.augmentables.kps.Keypoint
Points of the line string as keypoints.
"""
# TODO get rid of this deferred import
from imgaug.augmentables.kps ... |
Generate a bounding box encapsulating the line string. | def to_bounding_box(self):
"""
Generate a bounding box encapsulating the line string.
Returns
-------
None or imgaug.augmentables.bbs.BoundingBox
Bounding box encapsulating the line string.
``None`` if the line string contained no points.
"""
... |
Generate a polygon from the line string points. | def to_polygon(self):
"""
Generate a polygon from the line string points.
Returns
-------
imgaug.augmentables.polys.Polygon
Polygon with the same corner points as the line string.
Note that the polygon might be invalid, e.g. contain less than 3
... |
Generate a heatmap object from the line string. | def to_heatmap(self, image_shape, size_lines=1, size_points=0,
antialiased=True, raise_if_out_of_image=False):
"""
Generate a heatmap object from the line string.
This is similar to
:func:`imgaug.augmentables.lines.LineString.draw_lines_heatmap_array`
executed... |
Generate a segmentation map object from the line string. | def to_segmentation_map(self, image_shape, size_lines=1, size_points=0,
raise_if_out_of_image=False):
"""
Generate a segmentation map object from the line string.
This is similar to
:func:`imgaug.augmentables.lines.LineString.draw_mask`.
The result is... |
Compare this and another LineString s coordinates. | def coords_almost_equals(self, other, max_distance=1e-6, points_per_edge=8):
"""
Compare this and another LineString's coordinates.
This is an approximate method based on pointwise distances and can
in rare corner cases produce wrong outputs.
Parameters
----------
... |
Compare this and another LineString. | def almost_equals(self, other, max_distance=1e-4, points_per_edge=8):
"""
Compare this and another LineString.
Parameters
----------
other: imgaug.augmentables.lines.LineString
The other line string. Must be a LineString instance, not just
its coordinates... |
Create a shallow copy of the LineString object. | def copy(self, coords=None, label=None):
"""
Create a shallow copy of the LineString object.
Parameters
----------
coords : None or iterable of tuple of number or ndarray
If not ``None``, then the coords of the copied object will be set
to this value.
... |
Create a deep copy of the BoundingBox object. | def deepcopy(self, coords=None, label=None):
"""
Create a deep copy of the BoundingBox object.
Parameters
----------
coords : None or iterable of tuple of number or ndarray
If not ``None``, then the coords of the copied object will be set
to this value.
... |
Project bounding boxes from one image to a new one. | def on(self, image):
"""
Project bounding boxes from one image to a new one.
Parameters
----------
image : ndarray or tuple of int
The new image onto which to project.
Either an image with shape ``(H,W,[C])`` or a tuple denoting
such an image ... |
Convert an ( N M 2 ) ndarray to a LineStringsOnImage object. | def from_xy_arrays(cls, xy, shape):
"""
Convert an `(N,M,2)` ndarray to a LineStringsOnImage object.
This is the inverse of
:func:`imgaug.augmentables.lines.LineStringsOnImage.to_xy_array`.
Parameters
----------
xy : (N,M,2) ndarray or iterable of (M,2) ndarray
... |
Convert this object to an iterable of ( M 2 ) arrays of points. | def to_xy_arrays(self, dtype=np.float32):
"""
Convert this object to an iterable of ``(M,2)`` arrays of points.
This is the inverse of
:func:`imgaug.augmentables.lines.LineStringsOnImage.from_xy_array`.
Parameters
----------
dtype : numpy.dtype, optional
... |
Draw all line strings onto a given image. | def draw_on_image(self, image,
color=(0, 255, 0), color_lines=None, color_points=None,
alpha=1.0, alpha_lines=None, alpha_points=None,
size=1, size_lines=None, size_points=None,
antialiased=True,
raise_if_out_o... |
Remove all line strings that are fully/ partially outside of the image. | def remove_out_of_image(self, fully=True, partly=False):
"""
Remove all line strings that are fully/partially outside of the image.
Parameters
----------
fully : bool, optional
Whether to remove line strings that are fully outside of the image.
partly : bool... |
Clip off all parts of the line strings that are outside of the image. | def clip_out_of_image(self):
"""
Clip off all parts of the line strings that are outside of the image.
Returns
-------
imgaug.augmentables.lines.LineStringsOnImage
Line strings, clipped to fall within the image dimensions.
"""
lss_cut = [ls_clipped
... |
Shift/ move the line strings from one or more image sides. | def shift(self, top=None, right=None, bottom=None, left=None):
"""
Shift/move the line strings from one or more image sides.
Parameters
----------
top : None or int, optional
Amount of pixels by which to shift all bounding boxes from the
top.
rig... |
Create a shallow copy of the LineStringsOnImage object. | def copy(self, line_strings=None, shape=None):
"""
Create a shallow copy of the LineStringsOnImage object.
Parameters
----------
line_strings : None \
or list of imgaug.augmentables.lines.LineString, optional
List of line strings on the image.
... |
Create a deep copy of the LineStringsOnImage object. | def deepcopy(self, line_strings=None, shape=None):
"""
Create a deep copy of the LineStringsOnImage object.
Parameters
----------
line_strings : None \
or list of imgaug.augmentables.lines.LineString, optional
List of line strings on the image.... |
Blend two images using an alpha blending. | def blend_alpha(image_fg, image_bg, alpha, eps=1e-2):
"""
Blend two images using an alpha blending.
In an alpha blending, the two images are naively mixed. Let ``A`` be the foreground image
and ``B`` the background image and ``a`` is the alpha value. Each pixel intensity is then
computed as ``a * A... |
Augmenter to alpha - blend two image sources using simplex noise alpha masks. | def SimplexNoiseAlpha(first=None, second=None, per_channel=False, size_px_max=(2, 16), upscale_method=None,
iterations=(1, 3), aggregation_method="max", sigmoid=True, sigmoid_thresh=None,
name=None, deterministic=False, random_state=None):
"""
Augmenter to alpha-blend... |
Augmenter that always executes exactly one of its children. | def OneOf(children, name=None, deterministic=False, random_state=None):
"""
Augmenter that always executes exactly one of its children.
dtype support::
See ``imgaug.augmenters.meta.SomeOf``.
Parameters
----------
children : list of imgaug.augmenters.meta.Augmenter
The choices ... |
Augmenter that runs an assert on each batch of input images using a lambda function as condition. | def AssertLambda(func_images=None, func_heatmaps=None, func_keypoints=None,
func_polygons=None, name=None, deterministic=False,
random_state=None):
"""
Augmenter that runs an assert on each batch of input images
using a lambda function as condition.
This is useful to m... |
Augmenter to make assumptions about the shape of input image ( s ) heatmaps and keypoints. | def AssertShape(shape, check_images=True, check_heatmaps=True,
check_keypoints=True, check_polygons=True,
name=None, deterministic=False, random_state=None):
"""
Augmenter to make assumptions about the shape of input image(s), heatmaps and keypoints.
dtype support::
... |
Randomize the order of ( color ) channels in an image. | def shuffle_channels(image, random_state, channels=None):
"""
Randomize the order of (color) channels in an image.
dtype support::
* ``uint8``: yes; fully tested
* ``uint16``: yes; indirectly tested (1)
* ``uint32``: yes; indirectly tested (1)
* ``uint64``: yes; indirectly ... |
Blur an image using gaussian blurring. | def blur_gaussian_(image, sigma, ksize=None, backend="auto", eps=1e-3):
"""
Blur an image using gaussian blurring.
This operation might change the input image in-place.
dtype support::
if (backend="auto")::
* ``uint8``: yes; fully tested (1)
* ``uint16``: yes; tested ... |
Augmenter that sharpens images and overlays the result with the original image. | def MotionBlur(k=5, angle=(0, 360), direction=(-1.0, 1.0), order=1, name=None, deterministic=False, random_state=None):
"""
Augmenter that sharpens images and overlays the result with the original image.
dtype support::
See ``imgaug.augmenters.convolutional.Convolve``.
Parameters
--------... |
Augmenter to draw clouds in images. | def Clouds(name=None, deterministic=False, random_state=None):
"""
Augmenter to draw clouds in images.
This is a wrapper around ``CloudLayer``. It executes 1 to 2 layers per image, leading to varying densities
and frequency patterns of clouds.
This augmenter seems to be fairly robust w.r.t. the im... |
Augmenter to draw fog in images. | def Fog(name=None, deterministic=False, random_state=None):
"""
Augmenter to draw fog in images.
This is a wrapper around ``CloudLayer``. It executes a single layer per image with a configuration leading
to fairly dense clouds with low-frequency patterns.
This augmenter seems to be fairly robust w... |
Augmenter to add falling snowflakes to images. | def Snowflakes(density=(0.005, 0.075), density_uniformity=(0.3, 0.9), flake_size=(0.2, 0.7),
flake_size_uniformity=(0.4, 0.8), angle=(-30, 30), speed=(0.007, 0.03),
name=None, deterministic=False, random_state=None):
"""
Augmenter to add falling snowflakes to images.
This is a... |
Get the segmentation map array as an integer array of shape ( H W ). | def get_arr_int(self, background_threshold=0.01, background_class_id=None):
"""
Get the segmentation map array as an integer array of shape (H, W).
Each pixel in that array contains an integer value representing the pixel's class.
If multiple classes overlap, the one with the highest lo... |
Render the segmentation map as an RGB image. | def draw(self, size=None, background_threshold=0.01, background_class_id=None, colors=None,
return_foreground_mask=False):
"""
Render the segmentation map as an RGB image.
Parameters
----------
size : None or float or iterable of int or iterable of float, optional
... |
Draw the segmentation map as an overlay over an image. | def draw_on_image(self, image, alpha=0.75, resize="segmentation_map", background_threshold=0.01,
background_class_id=None, colors=None, draw_background=False):
"""
Draw the segmentation map as an overlay over an image.
Parameters
----------
image : (H,W,3) ... |
Pad the segmentation map on its top/ right/ bottom/ left side. | def pad(self, top=0, right=0, bottom=0, left=0, mode="constant", cval=0.0):
"""
Pad the segmentation map on its top/right/bottom/left side.
Parameters
----------
top : int, optional
Amount of pixels to add at the top side of the segmentation map. Must be 0 or greater... |
Pad the segmentation map on its sides so that its matches a target aspect ratio. | def pad_to_aspect_ratio(self, aspect_ratio, mode="constant", cval=0.0, return_pad_amounts=False):
"""
Pad the segmentation map on its sides so that its matches a target aspect ratio.
Depending on which dimension is smaller (height or width), only the corresponding
sides (left/right or t... |
Resize the segmentation map array to the provided size given the provided interpolation. | def resize(self, sizes, interpolation="cubic"):
"""
Resize the segmentation map array to the provided size given the provided interpolation.
Parameters
----------
sizes : float or iterable of int or iterable of float
New size of the array in ``(height, width)``.
... |
Convert segmentation map to heatmaps object. | def to_heatmaps(self, only_nonempty=False, not_none_if_no_nonempty=False):
"""
Convert segmentation map to heatmaps object.
Each segmentation map class will be represented as a single heatmap channel.
Parameters
----------
only_nonempty : bool, optional
If T... |
Convert heatmaps to segmentation map. | def from_heatmaps(heatmaps, class_indices=None, nb_classes=None):
"""
Convert heatmaps to segmentation map.
Assumes that each class is represented as a single heatmap channel.
Parameters
----------
heatmaps : imgaug.HeatmapsOnImage
Heatmaps to convert.
... |
Create a deep copy of the segmentation map object. | def deepcopy(self):
"""
Create a deep copy of the segmentation map object.
Returns
-------
imgaug.SegmentationMapOnImage
Deep copy.
"""
segmap = SegmentationMapOnImage(self.arr, shape=self.shape, nb_classes=self.nb_classes)
segmap.input_was =... |
Offer a new event s at point p in this queue. | def offer(self, p, e: Event):
"""
Offer a new event ``s`` at point ``p`` in this queue.
"""
existing = self.events_scan.setdefault(
p, ([], [], [], []) if USE_VERTICAL else
([], [], []))
# Can use double linked-list for easy insertion at beginni... |
Get the heatmap s array within the value range originally provided in __init__ (). | def get_arr(self):
"""
Get the heatmap's array within the value range originally provided in ``__init__()``.
The HeatmapsOnImage object saves heatmaps internally in the value range ``(min=0.0, max=1.0)``.
This function converts the internal representation to ``(min=min_value, max=max_va... |
Render the heatmaps as RGB images. | def draw(self, size=None, cmap="jet"):
"""
Render the heatmaps as RGB images.
Parameters
----------
size : None or float or iterable of int or iterable of float, optional
Size of the rendered RGB image as ``(height, width)``.
See :func:`imgaug.imgaug.imre... |
Draw the heatmaps as overlays over an image. | def draw_on_image(self, image, alpha=0.75, cmap="jet", resize="heatmaps"):
"""
Draw the heatmaps as overlays over an image.
Parameters
----------
image : (H,W,3) ndarray
Image onto which to draw the heatmaps. Expected to be of dtype uint8.
alpha : float, opt... |
Inverts each value in the heatmap shifting low towards high values and vice versa. | def invert(self):
"""
Inverts each value in the heatmap, shifting low towards high values and vice versa.
This changes each value to::
v' = max - (v - min)
where ``v`` is the value at some spatial location, ``min`` is the minimum value in the heatmap
and ``max`` is... |
Pad the heatmaps on their top/ right/ bottom/ left side. | def pad(self, top=0, right=0, bottom=0, left=0, mode="constant", cval=0.0):
"""
Pad the heatmaps on their top/right/bottom/left side.
Parameters
----------
top : int, optional
Amount of pixels to add at the top side of the heatmaps. Must be 0 or greater.
rig... |
Pad the heatmaps on their sides so that they match a target aspect ratio. | def pad_to_aspect_ratio(self, aspect_ratio, mode="constant", cval=0.0, return_pad_amounts=False):
"""
Pad the heatmaps on their sides so that they match a target aspect ratio.
Depending on which dimension is smaller (height or width), only the corresponding
sides (left/right or top/bott... |
Resize the heatmap ( s ) array using average pooling of a given block/ kernel size. | def avg_pool(self, block_size):
"""
Resize the heatmap(s) array using average pooling of a given block/kernel size.
Parameters
----------
block_size : int or tuple of int
Size of each block of values to pool, aka kernel size. See :func:`imgaug.pool` for details.
... |
Resize the heatmap ( s ) array using max - pooling of a given block/ kernel size. | def max_pool(self, block_size):
"""
Resize the heatmap(s) array using max-pooling of a given block/kernel size.
Parameters
----------
block_size : int or tuple of int
Size of each block of values to pool, aka kernel size. See :func:`imgaug.pool` for details.
... |
Resize the heatmap ( s ) array to the provided size given the provided interpolation. | def resize(self, sizes, interpolation="cubic"):
"""
Resize the heatmap(s) array to the provided size given the provided interpolation.
Parameters
----------
sizes : float or iterable of int or iterable of float
New size of the array in ``(height, width)``.
... |
Convert this heatmaps object to a 0 - to - 255 array. | def to_uint8(self):
"""
Convert this heatmaps object to a 0-to-255 array.
Returns
-------
arr_uint8 : (H,W,C) ndarray
Heatmap as a 0-to-255 array (dtype is uint8).
"""
# TODO this always returns (H,W,C), even if input ndarray was originall (H,W)
... |
Create a heatmaps object from an heatmap array containing values ranging from 0 to 255. | def from_uint8(arr_uint8, shape, min_value=0.0, max_value=1.0):
"""
Create a heatmaps object from an heatmap array containing values ranging from 0 to 255.
Parameters
----------
arr_uint8 : (H,W) ndarray or (H,W,C) ndarray
Heatmap(s) array, where ``H`` is height, ``W... |
Create a heatmaps object from an heatmap array containing values ranging from 0. 0 to 1. 0. | def from_0to1(arr_0to1, shape, min_value=0.0, max_value=1.0):
"""
Create a heatmaps object from an heatmap array containing values ranging from 0.0 to 1.0.
Parameters
----------
arr_0to1 : (H,W) or (H,W,C) ndarray
Heatmap(s) array, where ``H`` is height, ``W`` is wid... |
Change the value range of a heatmap from one min - max to another min - max. | def change_normalization(cls, arr, source, target):
"""
Change the value range of a heatmap from one min-max to another min-max.
E.g. the value range may be changed from min=0.0, max=1.0 to min=-1.0, max=1.0.
Parameters
----------
arr : ndarray
Heatmap array... |
Create a deep copy of the Heatmaps object. | def deepcopy(self):
"""
Create a deep copy of the Heatmaps object.
Returns
-------
imgaug.HeatmapsOnImage
Deep copy.
"""
return HeatmapsOnImage(self.get_arr(), shape=self.shape, min_value=self.min_value, max_value=self.max_value) |
If the header key does not exist then set it to value. Returns the header value. | def setdefault(self, key: str, value: str) -> str:
"""
If the header `key` does not exist, then set it to `value`.
Returns the header value.
"""
set_key = key.lower().encode("latin-1")
set_value = value.encode("latin-1")
for idx, (item_key, item_value) in enumera... |
Append a header preserving any duplicate entries. | def append(self, key: str, value: str) -> None:
"""
Append a header, preserving any duplicate entries.
"""
append_key = key.lower().encode("latin-1")
append_value = value.encode("latin-1")
self._list.append((append_key, append_value)) |
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