sift
: 2D image alignment¶
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class
silx.image.sift.
SiftPlan
(shape=None, dtype=None, devicetype='ALL', template=None, profile=False, device=None, PIX_PER_KP=None, max_workgroup_size=None, context=None, init_sigma=None)[source]¶ This class implements a way to calculate SIFT keypoints.
How to calculate a set of SIFT keypoint on an image:
siftp = sift.SiftPlan(img.shape,img.dtype,devicetype="GPU") kp = siftp.keypoints(img)
kp is a nx132 array. the second dimension is composed of x,y, scale and angle as well as 128 floats describing the keypoint
This SIFT algorithm is patented: U.S. Patent 6,711,293: “Method and apparatus for identifying scale invariant features in an image and use of same for locating an object in an image”,
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keypoints
(image)[source]¶ Calculates the keypoints of the image
Parameters: image – ndimage of 2D (or 3D if RGB) Returns: vector of keypoint (1D numpy array)
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class
silx.image.sift.
MatchPlan
(size=16384, devicetype='ALL', profile=False, device=None, max_workgroup_size=None, roi=None, context=None)[source]¶ Plan to compare sets of SIFT keypoint and find common ones.
siftp = sift.MatchPlan(devicetype="ALL") commonkp = siftp.match(kp1,kp2)
where kp1, kp2 is a n x 132 array. the second dimension is composed of x,y, scale and angle as well as 128 floats describing the keypoint. commonkp is mx2 array of matching keypoints
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match
(nkp1, nkp2, raw_results=False)[source]¶ Calculate the matching of 2 keypoint list
Parameters: - nkp1 – numpy 1D recarray of keypoints or equivalent GPU buffer
- nkp2 – numpy 1D recarray of keypoints or equivalent GPU buffer
- raw_results – if true return the 2D array of indexes of matching keypoints (not the actual keypoints)
TODO: implement the ROI ...
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class
silx.image.sift.
LinearAlign
(image, devicetype='CPU', profile=False, device=None, max_workgroup_size=None, ROI=None, extra=0, context=None, init_sigma=None)[source]¶ Align images on a reference image based on an afine transformation (bi-linear + offset)
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align
(img, shift_only=False, return_all=False, double_check=False, relative=False, orsa=False)[source]¶ Align image on reference image
Parameters: - img – numpy array containing the image to align to reference
- return_all – return in addition ot the image, keypoints, matching keypoints, and transformations as a dict
- reltive – update reference keypoints with those from current image to perform relative alignment
Returns: aligned image or all informations
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