Update app.py

app.py

@@ -12,6 +12,9 @@ pose = mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5)
 # Initialize MediaPipe Drawing
 mp_drawing = mp.solutions.drawing_utils
 
+Load the model
+    model = load_model()
+
 # Load the Hugging Face model and tokenizer
 model_name = "your-huggingface-model-name"
 model = AutoModelForSequenceClassification.from_pretrained(model_name)
@@ -30,7 +33,10 @@ def classify_pose(landmarks):
     # Map predictions to pose names (adjust this mapping according to your model)
     pose_names = ["Mountain Pose", "Tree Pose", "Warrior Pose", "Unknown Pose"]
     return pose_names[predictions.item()]
-
+    
+def load_model():
+    return pipeline("pose-detection", device=0)  # Adjust device as per your requirement
+    
 def main():
     st.title("Live Yoga Pose Detection with Hugging Face")