Update app.py

app.py

@@ -8,19 +8,30 @@ mp_pose = mp.solutions.pose
 pose = mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5, model_complexity=1)
 mp_drawing = mp.solutions.drawing_utils
 
-def detectPose(input_image):
+# Define a function to classify yoga poses
+def classify_pose(landmarks):
+    # Example logic for classifying poses
+    if landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].visibility > 0.5 and \
+       landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value].visibility > 0.5:
+        return "T-Pose"
+    # Add more classification rules here
+    return "Unknown Pose"
+
+def detect_and_classify_pose(input_image):
     frame = cv2.cvtColor(input_image, cv2.COLOR_BGR2RGB)
     results = pose.process(frame)
     if results.pose_landmarks:
         mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
+        pose_classification = classify_pose(results.pose_landmarks.landmark)
+        cv2.putText(frame, pose_classification, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2, cv2.LINE_AA)
     return frame
 
 iface = gr.Interface(
-    fn=detectPose,
+    fn=detect_and_classify_pose,
     inputs="image",
     outputs="image",
-    title="Live Yoga Pose Detection",
-    description="This app detects yoga poses from the live camera feed using MediaPipe.",
+    title="Live Yoga Pose Detection and Classification",
+    description="This app detects and classifies yoga poses from the live camera feed using MediaPipe.",
 )
 
 iface.launch()