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Commite7fdf7e

Browse files
syurkeviumar456
authored andcommitted
adds missing deconv functions to python wrapper
1 parenta1d5a1f commite7fdf7e

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3 files changed

+94
-0
lines changed

3 files changed

+94
-0
lines changed

‎arrayfire/image.py

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Original file line numberDiff line numberDiff line change
@@ -1324,6 +1324,78 @@ def anisotropic_diffusion(image, time_step, conductance, iterations, flux_functi
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flux_function_type.value,diffusion_kind.value))
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returnout
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defiterativeDeconv(image,psf,iterations,relax_factor,algo=ITERATIVE_DECONV.DEFAULT):
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"""
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Iterative deconvolution algorithm.
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Parameters
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----------
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image: af.Array
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The blurred input image.
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psf: af.Array
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The kernel(point spread function) known to have caused
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the blur in the system.
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iterations:
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Number of times the algorithm will run.
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relax_factor: scalar.
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is the relaxation factor multiplied with distance
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of estimate from observed image.
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algo:
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takes enum value of type af.ITERATIVE_DECONV
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indicating the iterative deconvolution algorithm to be used
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Returns
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-------
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out: af.Array
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sharp image estimate generated from the blurred input
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Note
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-------
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relax_factor argument is ignored when the RICHARDSONLUCY algorithm is used.
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"""
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out=Array()
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safe_call(backend.get().
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af_iterative_deconv(c_pointer(out.arr),image.arr,psf.arr,
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c_uint_t(iterations),c_float_t(relax_factor),algo.value))
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returnout
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definverseDeconv(image,psf,gamma,algo=ITERATIVE_DECONV.DEFAULT):
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"""
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Inverse deconvolution algorithm.
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Parameters
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----------
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image: af.Array
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The blurred input image.
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psf: af.Array
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The kernel(point spread function) known to have caused
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the blur in the system.
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gamma: scalar.
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is a user defined regularization constant
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algo:
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takes enum value of type af.INVERSE_DECONV
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indicating the inverse deconvolution algorithm to be used
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Returns
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-------
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out: af.Array
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sharp image estimate generated from the blurred input
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"""
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out=Array()
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safe_call(backend.get().
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af_inverse_deconv(c_pointer(out.arr),image.arr,psf.arr,
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c_float_t(gamma),algo.value))
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returnout
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defis_image_io_available():
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"""
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Function to check if the arrayfire library was built with Image IO support.

‎arrayfire/library.py

Lines changed: 15 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -459,6 +459,21 @@ class TOPK(_Enum):
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MIN=_Enum_Type(1)
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MAX=_Enum_Type(2)
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classITERATIVE_DECONV(_Enum):
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"""
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Iterative deconvolution algorithm
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"""
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DEFAULT=_Enum_Type(0)
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LANDWEBER=_Enum_Type(1)
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RICHARDSONLUCY=_Enum_Type(2)
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classINVERSE_DECONV(_Enum):
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"""
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Inverse deconvolution algorithm
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"""
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DEFAULT=_Enum_Type(0)
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TIKHONOV=_Enum_Type(1)
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classVARIANCE(_Enum):
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"""
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Variance bias type

‎tests/simple/image.py

Lines changed: 7 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -88,5 +88,12 @@ def simple_image(verbose=False):
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display_func(af.anisotropic_diffusion(a,0.125,1.0,64,af.FLUX.QUADRATIC,af.DIFFUSION.GRAD))
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a=af.randu(10,10)
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psf=af.gaussian_kernel(3,3)
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cimg=af.convolve(a,psf)
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display_func(af.iterativeDeconv(cimg,psf,100,0.5,af.ITERATIVE_DECONV.LANDWEBER))
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display_func(af.iterativeDeconv(cimg,psf,100,0.5,af.ITERATIVE_DECONV.RICHARDSONLUCY))
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display_func(af.inverseDeconv(cimg,psf,1.0,af.INVERSE_DECONV.TIKHONOV))
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_util.tests["image"]=simple_image

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