Add labels.txt to gesture classification and a new hand recognition project for 張君雅

projects/得能2026專題班/張君雅/手勢特徵分類/labels.txt

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+0 背景
+1 喝水中
+2 其他動作

projects/得能2026專題班/張君雅/手部辨識/hand_landmarker.task

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+version https://git-lfs.github.com/spec/v1
+oid sha256:fbc2a30080c3c557093b5ddfc334698132eb341044ccee322ccf8bcf3607cde1
+size 7819105

projects/得能2026專題班/張君雅/手部辨識/main.py

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+import cv2
+import mediapipe as mp
+from mediapipe.tasks import python
+from mediapipe.tasks.python import vision
+import os
+
+# ============================================
+# Week 9 - Step 2: MediaPipe 手部追蹤 (Tasks API)
+# ============================================
+
+# 初始化 MediaPipe Hand Landmarker
+model_path = os.path.join(os.path.dirname(__file__), 'hand_landmarker.task')
+base_options = python.BaseOptions(model_asset_path=model_path)
+options = vision.HandLandmarkerOptions(base_options=base_options, num_hands=1)
+detector = vision.HandLandmarker.create_from_options(options)
+
+cap = cv2.VideoCapture(0)
+
+while True:
+    success, img = cap.read()
+    if not success:
+        break
+
+    img = cv2.flip(img, 1)
+
+    # 1. OpenCV 的 BGR 轉為 RGB
+    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    
+    # 2. 將 Numpy 陣列轉為 MediaPipe Image 物件
+    mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=img_rgb)
+    
+    # 3. 進行偵測
+    results = detector.detect(mp_image)
+
+    # 4. 如果有偵測到手，把 21 個關鍵點都畫出來
+    if results.hand_landmarks:
+        for hand_lms in results.hand_landmarks:
+            h, w, c = img.shape
+            
+            # 迴圈畫出 21 個節點
+            for i, lm in enumerate(hand_lms):
+                cx, cy = int(lm.x * w), int(lm.y * h)
+                
+                # 畫出小綠點標示每個關節
+                cv2.circle(img, (cx, cy), 5, (0, 255, 0), -1)
+                
+                # 特別把食指尖 (Landmark 8) 標示為大紅點，並印出座標
+                if i == 8:
+                    cv2.circle(img, (cx, cy), 12, (0, 0, 255), -1)
+                    print(f"食指(8) 座標：({cx}, {cy})")
+
+    cv2.imshow("Hand Tracking", img)
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()