Update app.py

I am trying to reduce the lag by keeping the pose outside of the function if it will not work return back to original function

app.py

@@ -3,13 +3,11 @@ import queue
 from pathlib import Path
 from typing import List, NamedTuple
 import mediapipe as mp
-
 import av
 import cv2
 import numpy as np
 import streamlit as st
 from streamlit_webrtc import WebRtcMode, webrtc_streamer
-
 from sample_utils.download import download_file
 from sample_utils.turn import get_ice_servers
 
@@ -67,10 +65,12 @@ def calculate_angle(a, b, c):
         angle = 360 - angle
     return angle
 
-
 # Detection Queue
 result_queue: "queue.Queue[List[Detection]]" = queue.Queue()
 
+# Initialize MediaPipe Pose once
+pose = mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5)
+
 def video_frame_callback(frame: av.VideoFrame) -> av.VideoFrame:
     global counterL, correct, incorrect, stage
     if 'stage' not in globals():
@@ -82,87 +82,55 @@ def video_frame_callback(frame: av.VideoFrame) -> av.VideoFrame:
     h, w = image.shape[:2]
     image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 
-    with mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5) as pose:
-        results = pose.process(image_rgb)
-        landmarks = results.pose_landmarks.landmark if results.pose_landmarks else []
-
-        # Corrected detection logic
-        detections = [
-            Detection(
-                class_id=0,  # Assuming a generic class_id for pose detections
-                label="Pose",
-                score=0.5,  # Full confidence as pose landmarks were detected
-                box=np.array([0, 0, image.shape[1], image.shape[0]])  # Full image as bounding box
-            ) ] if landmarks else []
-
-        
-        if landmarks:
-            hipL = [landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].x, 
-                   landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].y]
-            kneeL = [landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value].x, 
-                    landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value].y]
-            ankleL = [landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].x, 
-                     landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].y]
-            shoulderL = [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x, 
-                        landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y]
-
-            # Calculate angles
-            angleKneeL = calculate_angle(hipL, kneeL, ankleL)
-            angleHipL = calculate_angle(shoulderL, hipL, [hipL[0], 0])
-
-                #Visualize of left leg
-            # cv2.putText(image, str(angleHipL), tuple(np.multiply(angleHipL, [w, h]).astype(int)),cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2, cv2.LINE_AA)
-            
-            # cv2.putText(image, str(int(angleHipL)),(0, 200), cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
-            # # cv2.putText(image, str(angleKneeL), tuple(np.multiply(angleKneeL, [w, h]).astype(int)),cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2, cv2.LINE_AA)
-            # cv2.putText(image, str(int(angleKneeL)),(170, 200), cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
-
-            # Relative points in terms of w and h
-            rel_point1 = (int(w * 0), int(h - h * 0.55))  # (0, h - 0.2*h)
-            rel_point2 = (int(w * 0.265625), int(h - h * 0.55))  # 170 / 640 = 0.265625
-
-            cv2.rectangle(image, (0,110), (280, 225), (127, 248, 236), -1)
-            cv2.rectangle(image, (0, 113), (277, 222), (12, 85, 61), -1)
-
-            cv2.putText(image, str(int(angleHipL)),(rel_point1), cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
-
-            cv2.putText(image, str(int(angleKneeL)),(rel_point2), cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
-
-            cv2.putText(image, 'HipL', (10, 140), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2, cv2.LINE_AA)
-
-            cv2.putText(image, 'KneeL', (180, 140),cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2, cv2.LINE_AA)
-            
-            if angleKneeL > 110 and stage == 'down':
-                stage = 'up'
-                if 18 < angleHipL < 40:
-                    correct += 1
-
-            if 80 < angleKneeL < 110 and stage == 'up':
-                stage = 'down'
-        
-         # REP data
-# Setup Status box
-        cv2.rectangle(image, (0,0), (280, 103), (127, 248, 236), -1)
-        cv2.rectangle(image, (0, 3), (277, 100), (12, 85, 61), -1)
-
-        cv2.putText(image, 'Left', (10, 22),
-            cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2, cv2.LINE_AA)
-
-        cv2.putText(image, str(correct),
-            (10, 70), cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
-
-# Stage data for left leg
-
-        cv2.putText(image, 'STAGE', (180, 22),
-            cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2, cv2.LINE_AA)
-
-        cv2.putText(image, stage,
-            (147, 70), cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
-        
-        mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS,mp_drawing.DrawingSpec(color=(255, 175, 0), thickness=2, circle_radius=2),mp_drawing.DrawingSpec(color=(0, 255, 200), thickness=2, circle_radius=2))
+    results = pose.process(image_rgb)
+    landmarks = results.pose_landmarks.landmark if results.pose_landmarks else []
+
+    detections = [
+        Detection(
+            class_id=0, label="Pose", score=0.5, box=np.array([0, 0, w, h])
+        )
+    ] if landmarks else []
+
+    if landmarks:
+        hipL = [landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].x, landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].y]
+        kneeL = [landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value].x, landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value].y]
+        ankleL = [landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].x, landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].y]
+        shoulderL = [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x, landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y]
+
+        angleKneeL = calculate_angle(hipL, kneeL, ankleL)
+        angleHipL = calculate_angle(shoulderL, hipL, [hipL[0], 0])
+
+        rel_point1 = (int(w * 0), int(h - h * 0.55))
+        rel_point2 = (int(w * 0.265625), int(h - h * 0.55))
+
+        cv2.rectangle(image, (0, 110), (280, 225), (127, 248, 236), -1)
+        cv2.rectangle(image, (0, 113), (277, 222), (12, 85, 61), -1)
+        cv2.putText(image, str(int(angleHipL)), rel_point1, cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
+        cv2.putText(image, str(int(angleKneeL)), rel_point2, cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
+
+        if angleKneeL > 110 and stage == 'down':
+            stage = 'up'
+            if 18 < angleHipL < 40:
+                correct += 1
+
+        if 80 < angleKneeL < 110 and stage == 'up':
+            stage = 'down'
+
+    cv2.rectangle(image, (0, 0), (280, 103), (127, 248, 236), -1)
+    cv2.rectangle(image, (0, 3), (277, 100), (12, 85, 61), -1)
+
+    cv2.putText(image, 'Left', (10, 22), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2, cv2.LINE_AA)
+    cv2.putText(image, str(correct), (10, 70), cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
+    cv2.putText(image, 'STAGE', (180, 22), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2, cv2.LINE_AA)
+    cv2.putText(image, stage, (147, 70), cv2.FONT_HERSHEY_SIMPLEX, 1.7, (255, 255, 255), 2, cv2.LINE_AA)
+
+    mp_drawing.draw_landmarks(
+        image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS,
+        mp_drawing.DrawingSpec(color=(255, 175, 0), thickness=2, circle_radius=2),
+        mp_drawing.DrawingSpec(color=(0, 255, 200), thickness=2, circle_radius=2)
+    )
 
     result_queue.put(detections)
-    
     return av.VideoFrame.from_ndarray(image, format="bgr24")
 
 webrtc_streamer(
@@ -172,4 +140,4 @@ webrtc_streamer(
     media_stream_constraints={"video": True, "audio": False},
     video_frame_callback=video_frame_callback,
     async_processing=True,
-)  
+)