Class GenericImage
source code
object --+
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base.parameterizedobject.ParameterizedObject --+
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base.patterngenerator.PatternGenerator --+
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GenericImage
- Known Subclasses:
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misc.robotics.CameraImage,
FileImage
Generic 2D image generator.
Generates a pattern from a Python Imaging Library image object.
Subclasses should override the _get_image method to produce the
image object.
The background value is calculated as an edge average: see edge_average().
Black-bordered images therefore have a black background, and
white-bordered images have a white background. Images with no
border have a background that is less of a contrast than a white
or black one.
At present, rotation, scaling, etc. just resample; it would be nice
to support some interpolation options as well.
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function(self,
params)
Function to draw a pattern that will then be scaled and rotated. |
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__getstate__(self)
Return the object's state (as in the superclass), but replace
the '_image' attribute's Image with a string representation. |
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__setstate__(self,
state)
Load the object's state (as in the superclass), but replace
the '_image' string with an actual Image object. |
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Inherited from base.patterngenerator.PatternGenerator:
__call__
Inherited from base.parameterizedobject.ParameterizedObject:
__init__,
__repr__,
__str__,
as_uninitialized,
debug,
defaults,
force_new_dynamic_value,
get_param_values,
get_value_generator,
inspect_value,
message,
print_param_values,
script_repr,
verbose,
warning
Inherited from object:
__delattr__,
__getattribute__,
__hash__,
__new__,
__reduce__,
__reduce_ex__,
__setattr__
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__abstract = True
bool(x) -> bool
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output_fn = <topo.base.parameterclasses.ClassSelectorParameter...
Optional function to apply to the pattern array after it has been created.
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aspect_ratio = <topo.base.parameterclasses.Number object at 0x...
Ratio of width to height; size*aspect_ratio gives the width.
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size = Number(default= 1.0, bounds= (0.0, None), softbounds= (...
Height of the image.
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size_normalization = <topo.base.parameterclasses.Enumeration o...
How to scale the initial image size relative to the default area of 1.0.
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whole_image_output_fn = <topo.base.parameterclasses.ClassSelec...
Function applied to the whole, original image array (before any cropping).
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pattern_sampler_type = <topo.base.parameterizedobject.Paramete...
The type of PatternSampler to use to resample/resize the image.
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Inherited from base.patterngenerator.PatternGenerator:
bounds,
mask,
offset,
orientation,
position,
scale,
x,
xdensity,
y,
ydensity
Inherited from base.parameterizedobject.ParameterizedObject:
name,
print_level
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Inherited from object:
__class__
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If a new filename or whole_image_output_fn is supplied, create a
PatternSampler based on the image found at filename.
The PatternSampler is given the whole image array after it has
been converted to grayscale.
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Function to draw a pattern that will then be scaled and rotated.
Instead of implementing __call__ directly, PatternGenerator
subclasses will typically implement this helper function used
by __call__, because that way they can let __call__ handle the
scaling and rotation for them. Alternatively, __call__ itself
can be reimplemented entirely by a subclass (e.g. if it does
not need to do any scaling or rotation), in which case this
function will be ignored.
- Overrides:
base.patterngenerator.PatternGenerator.function
- (inherited documentation)
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Get a new image, if necessary.
If necessary as indicated by the parameters, get a new image,
assign it to self._image and return True. If no new image is
needed, return False.
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__abstract
bool(x) -> bool
Returns True when the argument x is true, False otherwise.
The builtins True and False are the only two instances of the class bool.
The class bool is a subclass of the class int, and cannot be subclassed.
- Value:
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output_fn
Optional function to apply to the pattern array after it has been created.
This function can be used for normalization, thresholding, etc.
- Value:
ClassSelectorParameter(OutputFn, default= IdentityOF())
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aspect_ratio
Ratio of width to height; size*aspect_ratio gives the width.
- Value:
Number(default= 1.0, bounds= (0.0, None), softbounds= (0.0, 2.0), precedence= 0.31
, doc= """
Ratio of width to height; size*aspect_ratio gives the width.""")
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size
Height of the image.
- Value:
Number(default= 1.0, bounds= (0.0, None), softbounds= (0.0, 2.0), precedence= 0.30
, doc= "Height of the image.")
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size_normalization
How to scale the initial image size relative to the default area of 1.0.
- Value:
Enumeration(default= 'fit_shortest', available= ['fit_shortest', 'fit_longest', 's
tretch_to_fit', 'original'], precedence= 0.95, doc= """
How to scale the initial image size relative to the default area of 1.0.""
")
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whole_image_output_fn
Function applied to the whole, original image array (before any cropping).
- Value:
ClassSelectorParameter(OutputFn, default= DivisiveNormalizeLinf(), precedence= 0.9
6, doc= """
Function applied to the whole, original image array (before any cropping).
""")
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pattern_sampler_type
The type of PatternSampler to use to resample/resize the image.
- Value:
Parameter(default= PatternSampler, doc= """
The type of PatternSampler to use to resample/resize the image.""")
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