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How to use mask_kaze method in Airtest

Best Python code snippet using Airtest

keypoint_base.py

Source:keypoint_base.py

...22        self.im_source = im_source23        self.im_search = im_search24        self.threshold = threshold25        self.rgb = rgb26    def mask_kaze(self):27        """åºäºkazeæ¥æ¾å¤ä¸ªç®æ åºåçæ¹æ³."""28        # æ±åºç¹å¾ç¹åï¼self.im_sourceä¸è·å¾matchçé£äºç¹è¿è¡èç±»29        raise NotImplementedError30    def find_all_results(self):31        """åºäºkazeæ¥æ¾å¤ä¸ªç®æ åºåçæ¹æ³."""32        # æ±åºç¹å¾ç¹åï¼self.im_sourceä¸è·å¾matchçé£äºç¹è¿è¡èç±»33        raise NotImplementedError34    @print_run_time35    def find_best_result(self):36        """åºäºkazeè¿è¡å¾åè¯å«ï¼åªçéåºæä¼åºå."""37        # ç¬¬ä¸æ¥ï¼æ£éªå¾åæ¯å¦æ£å¸¸ï¼38        if not check_image_valid(self.im_source, self.im_search):39            return None40        # ç¬¬äºæ¥ï¼è·åç¹å¾ç¹éå¹¶å¹éåºç¹å¾ç¹å¯¹: è¿åå¼ good, pypts, kp_sch, kp_src...

VisualOdometry.py

Source:VisualOdometry.py

1import os2import glob3import numpy as np4import math5import cv2 as cv6from matplotlib import pyplot as plt78##################plot graph#######################9position_figure = plt.figure()10position_axes = position_figure.add_subplot(1, 1, 1)11# error_figure = plt.figure()12# rotation_error_axes = error_figure.add_subplot(1, 1, 1)13# rotation_error_list = []14# frame_index_list = []1516position_axes.set_aspect('equal', adjustable='box')17####################################################18###############ground truth###################################19gt_file = glob.glob('./poses/01.txt')20ground_truth_exist = True21ground_truth = []22with open(*gt_file) as f:23    gt_lines = f.readlines()2425    for gt_line in gt_lines:26        pose = np.array(gt_line.split()).reshape((3, 4)).astype(np.float32)27        ground_truth.append(pose)2829#######################################################################30#######################################################################31# parameters for lucas kanade optical flow32lk_params = dict(winSize=(21, 21),criteria=(cv.TERM_CRITERIA_EPS |cv.TERM_CRITERIA_COUNT, 30, 0.03))33#######################################################################34#####################camera setting information ###############################35camera_matrix = np.array([[718.8560, 0.0, 607.1928],36                          [0.0, 718.8560, 185.2157],37                          [0.0, 0.0, 1.0]])38f_l = camera_matrix[0][0]39f_r = camera_matrix[0][0]40c_x_l = camera_matrix[0][2]41c_y_l = camera_matrix[1][2]42c_x_r = camera_matrix[0][2]43c_y_r = camera_matrix[1][2]44baseline = -3.861448000000e+0245##################################################################################4647prev_img = None4849current_pos_akaze = np.zeros((3, 1))50current_rot_akaze = np.eye(3)51current_pos_orb = np.zeros((3, 1))52current_rot_orb = np.eye(3)53current_pos_kaze = np.zeros((3, 1))54current_rot_kaze = np.eye(3)55current_pos_sift = np.zeros((3, 1))56current_rot_sift = np.eye(3)5758camera_matrix = np.array([[718.8560, 0.0, 607.1928],59                          [0.0, 718.8560, 185.2157],60                          [0.0, 0.0, 1.0]])6162output = len(glob.glob('./image_0/*.png'))  # ì¬ì§ ê°ì6364for index in range(output):65    img_file = os.path.join('./image_0/', '{:06d}.png').format(index)66    img = cv.imread('./image_0/{}'.format(img_file))67    # print("check: {} , img : {} ".format(index, img))68    # cvtColorë ìí¨  ì´ë¯¸ ë³íëì´ ìì¼ëê¹6970    # keypoint detection and feature description71    # 1. AKAZE72    akaze = cv.AKAZE_create()73    kp_akaze = akaze.detect(img, None)  # find keypoints74    kp_akaze, des_akaze = akaze.compute(img, kp_akaze)  # compute descriptors with AKAZE75    # kp_akaze, des_akaze =akaze.detectAndCompute(img, None)76    # print("Keypoints AKAZE : {}".format(len(kp_akaze)))7778    # 2, ORB79    orb = cv.ORB_create()80    kp_orb = orb.detect(img, None)  # find keypoints81    kp_orb, des_orb = orb.compute(img, kp_orb)  # compute descriptors with ORB82    # kp_orb, des_orb =orb.detectAndCompute(img, None)83    # print("Keypoints ORB : {}".format(len(kp_orb)))8485    # 3. KAZE86    kaze = cv.KAZE_create()87    kp_kaze = kaze.detect(img, None)88    kp_kaze, des_kaze = kaze.compute(img, kp_kaze)89    # kp_kaze, des_kaze =kaze.detectAndCompute(img, None)90    # print("Keypoints KAZE : {}".format(len(kp_kaze)))9192    # 4. SIFT93    sift = cv.SIFT_create()94    kp_sift = sift.detect(img, None)95    kp_sift, des_sift = sift.compute(img, kp_sift)96    # print("Keypoints SIFT : {}".format(len(kp_sift)))97    # kp_sift, des_sift =sift.detectAndCompute(img, None)9899    if prev_img is None:100        prev_img = img101        prev_keypoint_akaze = kp_akaze102        prev_keypoint_orb = kp_orb103        prev_keypoint_kaze = kp_kaze104        prev_keypoint_sift = kp_sift105        #106        prev_des_akaze = des_akaze107        prev_des_orb = des_orb108        prev_des_kaze = des_kaze109        prev_des_sift = des_sift110        continue111112    points_akaze = np.array(list(map(lambda x: [x.pt], prev_keypoint_akaze)), dtype=np.float32).squeeze()113    points_orb = np.array(list(map(lambda x: [x.pt], prev_keypoint_orb)), dtype=np.float32).squeeze()114    points_kaze = np.array(list(map(lambda x: [x.pt], prev_keypoint_kaze)), dtype=np.float32).squeeze()115    points_sift = np.array(list(map(lambda x: [x.pt], prev_keypoint_sift)), dtype=np.float32).squeeze()116117    #############################points matching ##################################118    # # BFMatcher with default params119    # # brute-force matcher120    # # ì¬ì´ì¦ê° ì»¤ì§ë©´ ìë ì í121    # bf = cv.BFMatcher()122    # matches_akaze = bf.knnMatch(prev_des_akaze, des_akaze, k=2)123    # matches_orb = bf.knnMatch(prev_des_orb, des_orb, k=2)124    # matches_kaze = bf.knnMatch(prev_des_kaze, des_kaze, k=2)125    # matches_sift = bf.knnMatch(prev_des_sift, des_sift, k=2)126    #127    # # Apply ratio test128    # good_matches_akaze = []129    # good_matches_orb = []130    # good_matches_kaze = []131    # good_matches_sift = []132    #133    # pt1_akaze, pt2_akaze = [], []134    # pt1_orb, pt2_orb = [],[]135    # pt1_kaze, pt2_kaze = [],[]136    # pt1_sift, pt2_sift = [],[]137    #138    # for m, n in matches_akaze:139    #     if m.distance < 0.75 * n.distance:140    #         good_matches_akaze.append([m])141    #         pt1_akaze.append(prev_keypoint_akaze[m.queryIdx].pt)142    #         pt2_akaze.append(kp_akaze[m.trainIdx].pt)143    # for m,n in matches_orb:144    #     if m.distance < 0.75*n.distance:145    #         good_matches_orb.append([m])146    #         pt1_orb.append(prev_keypoint_orb[m.queryIdx].pt)147    #         pt2_orb.append(kp_orb[m.trainIdx].pt)148    # for m,n in matches_kaze:149    #     if m.distance < 0.75*n.distance:150    #         good_matches_kaze.append([m])151    #         pt1_kaze.append(prev_keypoint_kaze[m.queryIdx].pt)152    #         pt2_kaze.append(kp_kaze[m.trainIdx].pt)153    # for m,n in matches_sift:154    #     if m.distance < 0.75*n.distance:155    #         good_matches_sift.append([m])156    #         pt1_sift.append(prev_keypoint_sift[m.queryIdx].pt)157    #         pt2_sift.append(kp_sift[m.trainIdx].pt)158    #159    # pt1_akaze, pt2_akaze = np.float32(pt1_akaze), np.float32(pt2_akaze)160    # pt1_orb, pt2_orb = np.float32(pt1_orb), np.float32(pt2_orb)161    # pt1_kaze, pt2_kaze = np.float32(pt1_kaze), np.float32(pt2_kaze)162    # pt1_sift, pt2_sift = np.float32(pt1_sift), np.float32(pt2_sift)163    #################################################################################164165    pt1_akaze, st, err = cv.calcOpticalFlowPyrLK(prev_img, img, points_akaze, None, **lk_params)166    pt2_akaze = points_akaze167    pt1_orb, st, err = cv.calcOpticalFlowPyrLK(prev_img, img, points_orb, None, **lk_params)168    pt2_orb = points_orb169    pt1_kaze, st, err = cv.calcOpticalFlowPyrLK(prev_img, img, points_kaze, None, **lk_params)170    pt2_kaze = points_kaze171    pt1_sift, st, err = cv.calcOpticalFlowPyrLK(prev_img, img, points_sift, None, **lk_params)172    pt2_sift = points_sift173174    # Essenstial Matrix175    E_akaze, mask_akaze = cv.findEssentialMat(pt1_akaze, pt2_akaze, camera_matrix, cv.RANSAC, 0.999, 1.0, None)176    E_orb, mask_orb = cv.findEssentialMat(pt1_orb, pt2_orb, camera_matrix, cv.RANSAC, 0.999, 1.0, None)177    E_kaze, mask_kaze = cv.findEssentialMat(pt1_kaze, pt2_kaze, camera_matrix, cv.RANSAC, 0.999, 1.0, None)178    E_sift, mask_sift = cv.findEssentialMat(pt1_sift, pt2_sift, camera_matrix, cv.RANSAC, 0.999, 1.0, None)179180    pt1_akaze, R_akaze, t_akaze, mask_akaze = cv.recoverPose(E_akaze, pt2_akaze, pt1_akaze, camera_matrix)181    pt1_orb, R_orb, t_orb, mask_orb = cv.recoverPose(E_orb, pt2_orb, pt1_orb, camera_matrix)182    pt1_kaze, R_kaze, t_kaze, mask_kaze = cv.recoverPose(E_kaze, pt2_kaze, pt1_kaze, camera_matrix)183    pt1_sift, R_sift, t_sift, mask_sift = cv.recoverPose(E_sift, pt2_sift, pt1_sift, camera_matrix)184185    scale = 1.0186187    # ground truthë¥¼ ê¸°ë°ì¼ë¡ scale ê³ì°188    if ground_truth_exist:189        gt_pose = [ground_truth[index][0, 3], ground_truth[index][2, 3]]190        pre_gt_pose = [ground_truth[index - 1][0, 3], ground_truth[index - 1][2, 3]]191        scale = math.sqrt(math.pow((gt_pose[0] - pre_gt_pose[0]), 2.0) + math.pow((gt_pose[1] - pre_gt_pose[1]), 2.0))192193    # ì°ì  ground truthê° ìë¤ë©´ scale ê³ì°ì íì§ ìê³ 194    current_pos_akaze += current_rot_akaze.dot(t_akaze) * scale195    current_rot_akaze = R_akaze.dot(current_rot_akaze)196197    current_pos_orb += current_rot_orb.dot(t_orb) * scale198    current_rot_orb = R_orb.dot(current_rot_orb)199200    current_pos_kaze += current_rot_kaze.dot(t_kaze) * scale201    current_rot_kaze = R_kaze.dot(current_rot_kaze)202203    current_pos_sift += current_rot_sift.dot(t_sift) * scale204    current_rot_sift = R_sift.dot(current_rot_sift)205206    # ground truth plot207    position_axes.scatter(ground_truth[index][0, 3], ground_truth[index][2, 3],s=2 , c='red')208209    # odometry plot210    position_axes.scatter(-current_pos_akaze[0][0], -current_pos_akaze[2][0], s=2, c='gray')211    position_axes.scatter(-current_pos_orb[0][0], -current_pos_orb[2][0], s=2, c='purple')212    position_axes.scatter(-current_pos_kaze[0][0], -current_pos_kaze[2][0], s=2, c='blue')213    position_axes.scatter(-current_pos_sift[0][0], -current_pos_sift[2][0], s=2, c='black')214    plt.pause(.01)215216    plot_img = cv.drawKeypoints(img, kp_akaze, None)217218    # cv.imshow('feature', plot_img)219    # cv.waitKey(1)220221    prev_img = img222    prev_keypoint_akaze = kp_akaze223    prev_keypoint_orb = kp_orb224    prev_keypoint_kaze = kp_kaze225    prev_keypoint_sift = kp_sift226227    prev_des_akaze = des_akaze228    prev_des_orb = des_orb229    prev_des_kaze = des_kaze230    prev_des_sift = des_sift231
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