a d3 @sddlmZmZmZddlZddlmZddlmZmZm Z ddl m Z m Z ddl mZddlmZdd lmZd d Zdeeeeeeeeeeeeeeefd d dZGdddZdS))DictOptionalTupleN)Tensor)get_laf_centerget_laf_orientation get_laf_scale)KORNIA_CHECK_LAFKORNIA_CHECK_SHAPEget_cuda_device_if_available) adalam_core) dist_matrixc Cs"ddddddddd d td }|S) Ndg?T) Z area_ratioZsearch_expansionZ ransac_itersZ min_inliersZmin_confidence orientation_difference_thresholdscale_rate_thresholdZdetected_scale_rate_thresholdZrefitforce_seed_mnndevicer )DEFAULT_CONFIGre/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/kornia/feature/adalam/adalam.pyget_adalam_default_configsr) desc1desc2lafs1lafs2confighw1hw2dmreturnc Cst|ddgt|ddgt|t||durFt}|j|d<n|}t|} | t|ddt|dd||||t|dt|dt |dt |d } t j t | d|j |jd} | | fS) aWFunction, which performs descriptor matching, followed by AdaLAM filtering (see :cite:`AdaLAM2020` for more details) If the distance matrix dm is not provided, :py:func:`torch.cdist` is used. Args: desc1: Batch of descriptors of a shape :math:`(B1, D)`. desc2: Batch of descriptors of a shape :math:`(B2, D)`. lafs1: LAFs of a shape :math:`(1, B1, 2, 3)`. lafs2: LAFs of a shape :math:`(1, B1, 2, 3)`. config: dict with AdaLAM config dm: Tensor containing the distances from each descriptor in desc1 to each descriptor in desc2, shape of :math:`(B1, B2)`. Return: - Descriptor distance of matching descriptors, shape of :math:`(B3, 1)`. - Long tensor indexes of matching descriptors in desc1 and desc2. Shape: :math:`(B3, 2)`, where 0 <= B3 <= B1. BDIMNrr )dtyper)r r rr AdalamFiltermatch_and_filterrZreshaperrtorchZoneslenr,) rr r!r"r#r$r%r&Zconfig_Z adalam_objectZidxsZqualityrrr match_adalam$s.      r1c @sjeZdZeZd edddZd ejejejejeje e ejejejejd ddZ ddd Z d d Z dS)r-N) custom_configcCsLtj|_|durH|D]*\}}||jvrr?r@rArBrCrDrErrrfilter_matchesqs. zAdalamFilter.filter_matchesc  Cs2| dus| dur&|jddur&td|dus6|durL|jddurLtd|||||||| | \}}}}}}} } t||dd} tj| dd dd \} } | ddd f}| ddd f| ddd fd }|jd rtj| d d\}}||tj|j d |jddk}nd}| |||||||||| | S)aStandard matching and filtering with AdaLAM. This function: - performs some elementary sanity check on the inputs; - wraps input arrays into torch tensors and loads to GPU if necessary; - extracts nearest neighbors; - finds mutual nearest neighbors if required; - finally calls AdaLAM filtering. Inputs: k1: keypoint locations in the source image, in pixel coordinates. Expected an array with shape (num_keypoints_in_source_image, 2). k2: keypoint locations in the destination image, in pixel coordinates. Expected an array with shape (num_keypoints_in_destination_image, 2). d1: descriptors in the source image. Expected an array with shape (num_keypoints_in_source_image, descriptor_size). d2: descriptors in the destination image. Expected an array with shape (num_keypoints_in_destination_image, descriptor_size). im1shape: Shape of the source image. If None, it is inferred from keypoints max and min, at the cost of wasted runtime. So please provide it. Expected a tuple with (width, height) or (height, width) of source image im2shape: Shape of the destination image. If None, it is inferred from keypoints max and min, at the cost of wasted runtime. So please provide it. Expected a tuple with (width, height) or (height, width) of destination image o1/o2: keypoint orientations in degrees. They can be None if 'orientation_difference_threshold' in config is set to None. See documentation on 'orientation_difference_threshold' in the DEFAULT_CONFIG. Expected an array with shape (num_keypoints_in_source/destination_image,) s1/s2: keypoint scales. They can be None if 'scale_rate_threshold' in config is set to None. See documentation on 'scale_rate_threshold' in the DEFAULT_CONFIG. Expected an array with shape (num_keypoints_in_source/destination_image,) Returns: Filtered putative matches. A long tensor with shape (num_filtered_matches, 2) with indices of corresponding keypoints in k1 and k2. NrzCurrent configuration considers keypoint scales for filtering, but scales have not been provided. Please either provide scales or set 'scale_rate_threshold' to None to disable scale filteringrzCurrent configuration considers keypoint orientations for filtering, but orientations have not been provided. Please either provide orientations or set 'orientation_difference_threshold' to None to disable orientations filteringF) is_normalizedr+r )kdimZlargestrgMbP?r)rIr)r) r#AttributeError_AdalamFilter__to_torchrr/ZtopkZ clamp_min_minZarangeshaperF)r7r;r<d1Zd2r@rArBrCrDrEZdistmatZdd12Znn12r=r>Zdd21Znn21r?rrrr.s(!(& $zAdalamFilter.match_and_filtercsfdd|DS)Nc3s<|]4}|dust|r|ntj|jdtjdVqdS)Nr)rr,)r/Z is_tensorZtensorr#float32).0ar7rr sz*AdalamFilter.__to_torch..r)r7argsrrRrZ __to_torchs zAdalamFilter.__to_torch)N)NNNNNNN)NNNNNN) __name__ __module__ __qualname__rrdictr:r/rtuplerFr.rKrrrrr-[s0 > ;r-)NNNN)typingrrrr/rZkornia.feature.lafrrrZkornia.testingr r Zkornia.utils.helpersr corerutilsrrr1r-rrrrs0     7