Update app.py

app.py

@@ -1,7 +1,5 @@
 import gradio as gr
-import math
 import cv2
-import numpy as np
 import mediapipe as mp
 
 # Initialize mediapipe pose class
@@ -9,23 +7,15 @@ 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(image):
-    # Your detectPose function implementation
-    pass
-
-def classifyPose(landmarks, image):
-    # Your classifyPose function implementation
-    pass
-
-def detect_yoga_poses(frame):
+def detectPose(frame):
     frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-    frame, landmarks = detectPose(frame)
-    if landmarks:
-        frame, _ = classifyPose(landmarks, frame)
+    results = pose.process(frame)
+    if results.pose_landmarks:
+        mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
     return frame
 
 iface = gr.Interface(
-    fn=detect_yoga_poses,
+    fn=detectPose,
     inputs="webcam",
     outputs="image",
     title="Live Yoga Pose Detection",