Update app.py

app.py

@@ -2,75 +2,70 @@ import cv2
 import mediapipe as mp
 import os
 
-# Initialize MediaPipe utilities
 mp_drawing = mp.solutions.drawing_utils
-mp_pose = mp.solutions.pose
+mp_hands = mp.solutions.hands
 
 def process_image(image_path):
-    """Run pose estimation on a static image."""
+    """Run hand detection on a static image."""
     image = cv2.imread(image_path)
     if image is None:
         print(f"❌ Could not read image: {image_path}")
         return
 
-    with mp_pose.Pose(static_image_mode=True) as pose:
-        results = pose.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
-        if results.pose_landmarks:
-            mp_drawing.draw_landmarks(
-                image,
-                results.pose_landmarks,
-                mp_pose.POSE_CONNECTIONS,
-                landmark_drawing_spec=mp_drawing.DrawingSpec(color=(0, 255, 0), thickness=2, circle_radius=2),
-                connection_drawing_spec=mp_drawing.DrawingSpec(color=(255, 255, 255), thickness=2, circle_radius=2)
-            )
+    with mp_hands.Hands(static_image_mode=True, max_num_hands=2, min_detection_confidence=0.5) as hands:
+        results = hands.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
 
-        cv2.imshow("🧍 Pose Estimation (Image)", image)
+        if not results.multi_hand_landmarks:
+            print("🙌 No hands detected in image.")
+        else:
+            for hand_landmarks in results.multi_hand_landmarks:
+                mp_drawing.draw_landmarks(
+                    image,
+                    hand_landmarks,
+                    mp_hands.HAND_CONNECTIONS,
+                    mp_drawing.DrawingSpec(color=(0, 255, 0), thickness=2, circle_radius=3),
+                    mp_drawing.DrawingSpec(color=(255, 255, 255), thickness=2, circle_radius=2)
+                )
+
+        cv2.imshow("🤚 Hand Recognition (Image Mode)", image)
         cv2.waitKey(0)
         cv2.destroyAllWindows()
 
 def process_webcam():
-    """Run pose estimation using webcam if available."""
+    """Run hand detection using webcam if available."""
     cap = cv2.VideoCapture(0)
     if not cap.isOpened():
         print("⚠️ Webcam not detected. Switching to image mode...")
         return False
 
-    with mp_pose.Pose(
+    with mp_hands.Hands(
         static_image_mode=False,
-        model_complexity=1,
-        smooth_landmarks=True,
-        enable_segmentation=True,
+        max_num_hands=2,
         min_detection_confidence=0.5,
         min_tracking_confidence=0.5
-    ) as pose:
-        print("🎥 Webcam started. Press ESC to exit.")
+    ) as hands:
+        print("🎥 Hand Recognition running. Press ESC to exit.")
         while True:
             ret, frame = cap.read()
             if not ret:
                 print("❌ Failed to capture frame.")
                 break
 
-            # Convert to RGB for MediaPipe
-            image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-            image.flags.writeable = False
-            results = pose.process(image)
+            frame = cv2.flip(frame, 1)  # Mirror view
+            results = hands.process(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
 
-            # Convert back to BGR for display
-            image.flags.writeable = True
-            image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+            if results.multi_hand_landmarks:
+                for hand_landmarks in results.multi_hand_landmarks:
+                    mp_drawing.draw_landmarks(
+                        frame,
+                        hand_landmarks,
+                        mp_hands.HAND_CONNECTIONS,
+                        mp_drawing.DrawingSpec(color=(0, 255, 0), thickness=2, circle_radius=3),
+                        mp_drawing.DrawingSpec(color=(255, 255, 255), thickness=2, circle_radius=2)
+                    )
 
-            # Draw pose landmarks
-            if results.pose_landmarks:
-                mp_drawing.draw_landmarks(
-                    image,
-                    results.pose_landmarks,
-                    mp_pose.POSE_CONNECTIONS,
-                    landmark_drawing_spec=mp_drawing.DrawingSpec(color=(0, 255, 0), thickness=2, circle_radius=2),
-                    connection_drawing_spec=mp_drawing.DrawingSpec(color=(255, 255, 255), thickness=2, circle_radius=2)
-                )
-
-            cv2.imshow("🧍 Pose Estimation (ESC to exit)", image)
-            if cv2.waitKey(5) & 0xFF == 27:  # ESC key
+            cv2.imshow("🤚 Hand Recognition (ESC to exit)", frame)
+            if cv2.waitKey(5) & 0xFF == 27:  # ESC
                 break
 
     cap.release()
@@ -78,13 +73,12 @@ def process_webcam():
     return True
 
 if __name__ == "__main__":
-    print("🚀 Starting MediaPipe Pose App...")
+    print("🚀 Starting MediaPipe Hand Recognition App...")
 
-    # Try webcam first
     if not process_webcam():
-        # If no webcam, use fallback image
-        test_image = "pose_test.jpg"
+        test_image = "hand_test.jpg"
         if not os.path.exists(test_image):
-            print(f"⚠️ No '{test_image}' found. Please place a test image in this folder.")
+            print(f"⚠️ No '{test_image}' found. Please place a hand image in this folder.")
         else:
             process_image(test_image)
+