lab5 zad 2

lab5/zad2.py

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+import cv2 as cv
+import numpy as np
+
+if __name__ == '__main__':
+    boat_1 = cv.imread("../img/boat_1.jpg", cv.IMREAD_COLOR)
+    boat_2 = cv.imread("../img/boat_2.jpg", cv.IMREAD_COLOR)
+
+    boat_1_g = cv.cvtColor(boat_1, cv.COLOR_BGR2GRAY)
+    boat_2_g = cv.cvtColor(boat_2, cv.COLOR_BGR2GRAY)
+
+    orb_alg = cv.ORB_create(nfeatures=1000)
+
+    key_points_1, descriptors_1 = orb_alg.detectAndCompute(boat_1_g, None)
+    key_points_2, descriptors_2 = orb_alg.detectAndCompute(boat_2_g, None)
+
+    matcher = cv.DescriptorMatcher_create(cv.DESCRIPTOR_MATCHER_BRUTEFORCE_HAMMING)
+    matches = matcher.match(descriptors_1, descriptors_2, None)
+
+    matches = list(matches)
+
+    matches.sort(key=lambda x: x.distance, reverse=False)  # sort by distance
+
+    num_good_matches = int(len(matches) * 0.05)  # save 5%
+    matches = matches[:num_good_matches]
+
+    qIdx = matches[0].queryIdx
+    tIdx = matches[0].trainIdx
+
+    point_1 = key_points_1[qIdx].pt
+    point_2 = key_points_2[tIdx].pt
+
+    print(point_1)
+    print(point_2)
+
+    cv.circle(boat_1, np.int32(point_1), 10, [0, 255, 255], -1)
+    cv.circle(boat_2, np.int32(point_2), 10, [0, 255, 255], -1)
+
+    print(boat_1.shape)
+    print(boat_2.shape)
+
+    common_area_width = boat_1.shape[1] - int(point_1[0])
+
+    to_remove = common_area_width + int(point_2[0])
+
+    cropped_boat_2 = boat_2[:, to_remove:boat_2.shape[1], :]
+
+    panorama = np.concatenate((boat_1, cropped_boat_2), axis=1)
+    cv.imshow('panorama', panorama)
+
+    cv.waitKey(0)
+    cv.destroyAllWindows()