add

app.py

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+import streamlit as st
+import cv2
+import numpy as np
+import mediapipe as mp
+
+def convert_and_process(uploaded_file):
+    with open("temp.mp4", "wb") as f:
+        f.write(uploaded_file.getbuffer())
+
+    # Convert to desired format (replace with your preferred format)
+    cap = cv2.VideoCapture("temp.mp4")
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    out = cv2.VideoWriter('output.mp4', fourcc, 20.0, (int(cap.get(3)), int(cap.get(4))))
+
+    # Initialize Mediapipe Pose
+    mp_pose = mp.solutions.pose
+    with mp_pose.Pose() as pose:
+        while True:
+            ret, frame = cap.read()
+            if not ret:
+                break
+
+            # Convert to RGB for Mediapipe
+            image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            results = pose.process(image)
+
+            # Draw skeleton stickfigure (basic implementation)
+            if results.pose_landmarks:
+                for id, lm in enumerate(results.pose_landmarks.landmark):
+                    h, w, c = image.shape
+                    cx, cy = int(lm.x * w), int(lm.y  
+ * h)
+                    cv2.circle(image, (cx, cy), 5, (255, 0, 0), cv2.FILLED)  
+
+
+            # Write the frame with stickfigures to the output video
+            out.write(image)
+
+    cap.release()
+    out.release()
+
+def main():
+    st.title("Video Upload and Processing")
+    uploaded_file = st.file_uploader("Upload a video")
+    if uploaded_file is not None:
+        convert_and_process(uploaded_file)
+        st.video('output.mp4')
+
+if __name__ == '__main__':
+    main()