Update app.py

app.py

@@ -12,9 +12,6 @@ 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)
@@ -33,10 +30,7 @@ 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")