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How to use _cv_match method in Airtest

Best Python code snippet using Airtest

action_tracking.py

Source:action_tracking.py

...54            x, y = pos55            tid = id(v)56            if self._doing_actions:57                self.action_recorder.click(tid, [1.0 * x / w, 1.0 * y / h], v.filepath)58    def post_cv_match(self, cv_ret, *args, **kwargs):59        if not cv_ret:60            return61        # å¦æå½åå½æ°æ¯ç±loop_findè°ç¨çï¼é£å°±å¯ä»¥æ¾å°ä¸ä¸ªrectï¼è¿ä¸ªrectç±airtest.core.cv._cv_matchéç»åº62        # ä»¥ä¸å°±æ¯ä»frame stackä¸ä¸ç´æ¾å°loop_findè¿ä¸å¸§ï¼ç¶åæ¾åºloop_findçç¬¬ä¸ä¸ªargumentï¼éè¿argumentæ±åºtid63        frame = sys._getframe(0)64        while frame and frame.f_code.co_name != 'loop_find':65            frame = frame.f_back66        if frame:67            # more details about inspect parameter name in runtime,68            # see https://docs.python.org/2/library/inspect.html#inspect.getargvalues69            args, varargs, keywords, locals = inspect.getargvalues(frame)70            if len(args) > 0:71                v_name = args[0]72            elif varargs is not None and len(locals[varargs]) > 0:...

cv.py

Source:cv.py

...83            offset_w, offset_h = int(offset_w - w / 2), int(offset_h - h / 2)84        return (offset_h, offset_h + h, offset_w, offset_w + w)85    def match_in(self, screen, perdict_area=None):86        if not perdict_area:87            match_result = self._cv_match(screen)88        else:89            h1, h2, w1, w2 = perdict_area90            screen = screen[h1 : h2, w1 : w2]91            match_result = self._cv_match(screen)92            if match_result:93                match_result["result"] = (match_result["result"][0] + w1, match_result["result"][1] + h1)94                match_result['rectangle'] = (95                                             (match_result['rectangle'][0][0] + w1, match_result['rectangle'][0][1] + h1),96                                             (match_result['rectangle'][1][0] + w1, match_result['rectangle'][1][1] + h1),97                                             (match_result['rectangle'][2][0] + w1, match_result['rectangle'][2][1] + h1),98                                             (match_result['rectangle'][3][0] + w1, match_result['rectangle'][3][1] + h1),99                                             )100        101        G.LOGGING.debug("match result: %s", match_result)102        log_in_func({"cv": match_result})103        if not match_result:104            return None105        focus_pos = TargetPos().getXY(match_result, self.target_pos)106        return focus_pos107    108    def _cv_match(self, screen):109        try:110            match_result = super(Template, self)._cv_match(screen)111            return match_result112        except cv2.error as e:...

sift_extractor.py

Source:sift_extractor.py

...14        '''15        sift = cv2.xfeatures2d.SIFT_create()16        kp,des = sift.detectAndCompute(gray,None)17        return kp,des18    def _cv_match(self,img_1,kp_1,des_1,img_2,kp_2,des_2):19        bf = cv2.BFMatcher()20        self.count += 1        21        if des_1 is None or des_2 is None:22            return None23        matches = bf.knnMatch(des_1,des_2,k=2)  24        #print (self.count, len(matches))    25        if len(matches) >= 2:26            good_match = []27            for each in matches:28                if len(each) == 2:29                    m,n = each 30                    if m.distance < self.score * n.distance:31                        good_match.append([m])32                else:33                    good_match = None34                    break35            #good_match = [[m] for m, n in matches if m.distance < self.score * n.distance]36        else:37            good_match = None 38             39        return good_match40    def get_matched_landmark(self, img_1, img_2):41          42        gray_1 = cv2.cvtColor(img_1,cv2.COLOR_BGR2GRAY)43        gray_2 = cv2.cvtColor(img_2,cv2.COLOR_BGR2GRAY)44        45        pickle.dump(gray_1,open('img1','wb'))46        pickle.dump(gray_2,open('img2','wb'))47        kp_1,des_1 = self._get_sift(gray_1)48        kp_2,des_2 = self._get_sift(gray_2)49        good_match = self._cv_match(img_1,kp_1,des_1,img_2,kp_2,des_2)50        if good_match is None: 51            return None,None52        53        num_landmark = len(good_match)54        landmark_1 = np.zeros((num_landmark,2), dtype=np.int)55        landmark_2 = np.zeros((num_landmark,2), dtype=np.int)56        for i,each in enumerate(good_match):57            pt_1 = kp_1[each[0].queryIdx].pt58            pt_2 = kp_2[each[0].trainIdx].pt59            landmark_1[i,0] = round(pt_1[0])60            landmark_1[i,1] = round(pt_1[1])61            landmark_2[i,0] = round(pt_2[0])62            landmark_2[i,1] = round(pt_2[1])63        return landmark_1, landmark_2

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