31 lines
900 B
Python
31 lines
900 B
Python
# import the necessary packages
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from __future__ import absolute_import
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import numpy as np
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import cv2
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from ..convenience import is_cv2
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class RootSIFT:
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def __init__(self):
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# initialize the SIFT feature extractor for OpenCV 2.4
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if is_cv2():
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self.extractor = cv2.DescriptorExtractor_create("SIFT")
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# otherwise initialize the SIFT feature extractor for OpenCV 3+
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else:
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self.extractor = cv2.xfeatures2d.SIFT_create()
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def compute(self, image, kps, eps=1e-7):
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# compute SIFT descriptors
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(kps, descs) = self.extractor.compute(image, kps)
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# if there are no keypoints or descriptors, return an empty tuple
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if len(kps) == 0:
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return ([], None)
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# apply the Hellinger kernel by first L1-normalizing and taking the
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# square-root
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descs /= (descs.sum(axis=1, keepdims=True) + eps)
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descs = np.sqrt(descs)
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# return a tuple of the keypoints and descriptors
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return (kps, descs) |