Replacing np.int by np.int32 as np.int is no longer available startin…

…g from numpy 1.24

HandTracker.py

@@ -431,7 +431,7 @@ def lm_postprocess(self, hand, inference):
             mat = cv2.getAffineTransform(src, dst)
             lm_xy = np.expand_dims(hand.norm_landmarks[:,:2], axis=0)
             # lm_z = hand.norm_landmarks[:,2:3] * hand.rect_w_a  / 0.4
-            hand.landmarks = np.squeeze(cv2.transform(lm_xy, mat)).astype(np.int)
+            hand.landmarks = np.squeeze(cv2.transform(lm_xy, mat)).astype(np.int32)
 
             # World landmarks
             if self.use_world_landmarks:

HandTrackerBpf.py

@@ -489,7 +489,7 @@ def lm_postprocess(self, hand, inference):
             mat = cv2.getAffineTransform(src, dst)
             lm_xy = np.expand_dims(hand.norm_landmarks[:,:2], axis=0)
             # lm_z = hand.norm_landmarks[:,2:3] * hand.rect_w_a  / 0.4
-            hand.landmarks = np.squeeze(cv2.transform(lm_xy, mat)).astype(np.int)
+            hand.landmarks = np.squeeze(cv2.transform(lm_xy, mat)).astype(np.int32)
 
             # World landmarks
             if self.use_world_landmarks:

HandTrackerBpfEdge.py

@@ -483,7 +483,7 @@ def extract_hand_data(self, res, hand_idx):
         hand.handedness = res["handedness"][hand_idx]
         hand.label = "right" if hand.handedness > 0.5 else "left"
         hand.norm_landmarks = np.array(res['rrn_lms'][hand_idx]).reshape(-1,3)
-        hand.landmarks = (np.array(res["sqn_lms"][hand_idx]) * self.frame_size).reshape(-1,2).astype(np.int)
+        hand.landmarks = (np.array(res["sqn_lms"][hand_idx]) * self.frame_size).reshape(-1,2).astype(np.int32)
         if self.xyz:
             hand.xyz = np.array(res["xyz"][hand_idx])
             hand.xyz_zone = res["xyz_zone"][hand_idx]

HandTrackerEdge.py

@@ -430,7 +430,7 @@ def extract_hand_data(self, res, hand_idx):
         hand.handedness = res["handedness"][hand_idx]
         hand.label = "right" if hand.handedness > 0.5 else "left"
         hand.norm_landmarks = np.array(res['rrn_lms'][hand_idx]).reshape(-1,3)
-        hand.landmarks = (np.array(res["sqn_lms"][hand_idx]) * self.frame_size).reshape(-1,2).astype(np.int)
+        hand.landmarks = (np.array(res["sqn_lms"][hand_idx]) * self.frame_size).reshape(-1,2).astype(np.int32)
         if self.xyz:
             hand.xyz = np.array(res["xyz"][hand_idx])
             hand.xyz_zone = res["xyz_zone"][hand_idx]

HandTrackerRenderer.py

@@ -65,7 +65,7 @@ def draw_hand(self, hand):
                 if self.show_rot_rect:
                     cv2.polylines(self.frame, [np.array(hand.rect_points)], True, (0,255,255), 2, cv2.LINE_AA)
                 if self.show_landmarks:
-                    lines = [np.array([hand.landmarks[point] for point in line]).astype(np.int) for line in LINES_HAND]
+                    lines = [np.array([hand.landmarks[point] for point in line]).astype(np.int32) for line in LINES_HAND]
                     if self.show_handedness == 3:
                         color = (0,255,0) if hand.handedness > 0.5 else (0,0,255)
                     else:

examples/3d_visualization/demo.py

@@ -73,7 +73,7 @@ def __init__(self, tracker, mode_3d="image", smoothing=True):
     def draw_hand(self, hand, i):
         if self.mode_3d == "image":
             # Denormalize z-component of 'norm_landmarks'
-            lm_z = (hand.norm_landmarks[:,2:3] * hand.rect_w_a  / 0.4).astype(np.int)
+            lm_z = (hand.norm_landmarks[:,2:3] * hand.rect_w_a  / 0.4).astype(np.int32)
             # ... and concatenates with x and y components of 'landmarks'
             points = np.hstack((hand.landmarks, lm_z))
             radius = hand.rect_w_a / 30 # Thickness of segments depends on the hand size

mediapipe_utils.py

@@ -592,8 +592,8 @@ def __init__(self, scores=None, keypoints_norm=None, keypoints=None, score_thres
         self.score_thresh = score_thresh
         self.crop_region = crop_region
         self.next_crop_region = next_crop_region
-        # self.keypoints_square = (self.keypoints_norm * self.crop_region.size).astype(np.int)
-        self.keypoints = (np.array([self.crop_region.xmin, self.crop_region.ymin]) + self.keypoints_norm * self.crop_region.size).astype(np.int)
+        # self.keypoints_square = (self.keypoints_norm * self.crop_region.size).astype(np.int32)
+        self.keypoints = (np.array([self.crop_region.xmin, self.crop_region.ymin]) + self.keypoints_norm * self.crop_region.size).astype(np.int32)
 
     def print(self):
         attrs = vars(self)