opencv 4.x, numpy 2 compatibility

SiamMask/tools/test.py

@@ -273,7 +273,7 @@ def siamese_track(state, im, mask_enable=False, refine_enable=False, device='cpu
             c = -a * bbox[0]
             d = -b * bbox[1]
             mapping = np.array([[a, 0, c],
-                                [0, b, d]]).astype(np.float)
+                                [0, b, d]]).astype(float)
             crop = cv2.warpAffine(image, mapping, (out_sz[0], out_sz[1]),
                                   flags=cv2.INTER_LINEAR,
                                   borderMode=cv2.BORDER_CONSTANT,
@@ -289,10 +289,13 @@ def siamese_track(state, im, mask_enable=False, refine_enable=False, device='cpu
         mask_in_img = crop_back(mask, back_box, (state['im_w'], state['im_h']))
 
         target_mask = (mask_in_img > p.seg_thr).astype(np.uint8)
-        if cv2.__version__[-5] == '4':
-            contours, _ = cv2.findContours(target_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+        contours_result = cv2.findContours(target_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+        if len(contours_result) == 3:
+            # OpenCV ≤3.x
+            _, contours, _ = contours_result
         else:
-            _, contours, _ = cv2.findContours(target_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+            # OpenCV ≥4.x
+            contours, _ = contours_result
         cnt_area = [cv2.contourArea(cnt) for cnt in contours]
         if len(contours) != 0 and np.max(cnt_area) > 100:
             contour = contours[np.argmax(cnt_area)]  # use max area polygon