SIFT difinition no SIFT.get_distance_fn

[scutzhe]

def get_feature_and_dist_fns(feature_type):
if feature_type == 'hog':
return (HOG.compute_feature, HOG.get_distance_fn, HOG.DIST_METRICS)
elif feature_type == 'sift':
return (SIFT.compute_feature, SIFT.get_distance_fn, SIFT.DIST_METRICS)
elif feature_type == 'ch':
return (ColorHistogram.compute_feature, ColorHistogram.get_distance_fn, ColorHistogram.DIST_METRICS)
elif feature_type == 'raw':
return (RawImage.compute_feature, RawImage.get_distance_fn, RawImage.DIST_METRICS)

import cv2
import numpy as np
from scipy.spatial.distance import euclidean, cityblock, chebyshev, cosine

DIST_METRICS = [
('euclidean', euclidean),
('manhattan', cityblock),
('chebyshev', chebyshev),
('cosine', lambda x, y: -1*cosine(x, y)),
#('chisqr', lambda x, y: cv2.compareHist(x, y, cv2.HISTCMP_CHISQR)),
#('bhatta', lambda x, y: cv2.compareHist(x, y, cv2.HISTCMP_BHATTACHARYYA))
]

def compute_feature(frame):
sift = cv2.xfeatures2d.SIFT_create()
image = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
_, des = sift.detectAndCompute(image, None)
if des is not None:
return np.mean(des, axis=0).astype('float32')
else:
return np.zeros(128)

SIFT difinition no SIFT.get_distance_fn