Code Snippet: Sift Features, Distances

Sift_Distance.py

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+sift = cv.xfeatures2d.SIFT_create()
+original_kp, original_des = sift.detectAndCompute(left,None)
+new_kp, new_des = sift.detectAndCompute(right,None)
+
+bf = cv2.BFMatcher()
+matches = bf.knnMatch(original_des, new_des, k=2)
+
+# Apply ratio test
+good = []
+for m, n in matches:
+    if m.distance < 0.3 * n.distance:
+        good.append([m])
+
+# Featured matched keypoints from images 1 and 2
+pts1 = np.float32([original_kp[m.queryIdx].pt for m in good])
+pts2 = np.float32([new_kp[m.trainIdx].pt for m in good])
+
+#convert to complex number
+z1 = np.array([[complex(c[0],c[1]) for c in pts1]])
+z2 = np.array([[complex(c[0],c[1]) for c in pts2]])
+
+# Distance between featured matched keypoints
+FM_dist = abs(z2 - z1)
+