回传数据解析，兼容v5和v10

hands/hand_inference_origin.py

@@ -0,0 +1,44 @@
+import cv2
+import os
+import mediapipe as mp
+
+class hand_pose:
+    def __init__(self, min_dc=0.45, min_tc=0.45, max_nh=1):
+        self.mp_drawing = mp.solutions.drawing_utils
+        self.mp_hands = mp.solutions.hands
+        self.hands = self.mp_hands.Hands(
+            static_image_mode=False,
+            max_num_hands=max_nh,
+            min_detection_confidence=min_dc,
+            min_tracking_confidence=min_tc
+        )
+
+    @staticmethod
+    def img_show(img):
+        cv2.imshow('MediaPipe Hands', img)
+        cv2.waitKey(1)
+
+    def draw(self, img):
+        hand_local = []
+        h_re = self.hands.process(img)
+        if h_re.multi_hand_landmarks:
+            for hand_landmarks in h_re.multi_hand_landmarks:
+                self.mp_drawing.draw_landmarks(img,
+                                               hand_landmarks,
+                                               self.mp_hands.HAND_CONNECTIONS)
+                self.img_show(img)
+
+            '''获取手部关键点坐标'''
+            for i in range(21):
+                x = hand_landmarks.landmark[i].x * img.shape[1]
+                y = hand_landmarks.landmark[i].y * img.shape[0]
+                hand_local.append((x, y))
+        return hand_local
+
+if __name__ == "__main__":
+    handpose = hand_pose()
+    cap = cv2.VideoCapture(0)
+    while True:
+        ret, frame = cap.read()
+        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        handpose.draw(frame)