app.py

import gradio as gr
from ultralytics import YOLO
import cv2
import tempfile
import os

# Model load
model = YOLO('yolov8n.pt')

def count_people(video):
    if video is None:
        return "Please upload a video!"
    
    try:
        # Video process karo
        cap = cv2.VideoCapture(video)
        total_detections = 0
        frame_count = 0
        
        while cap.isOpened():
            ret, frame = cap.read()
            if not ret:
                break
            
            frame_count += 1
            
            # Har 5th frame process karo (speed ke liye)
            if frame_count % 5 == 0:
                # Person detect karo
                results = model(frame, classes=[0], verbose=False)
                
                # Count detections
                if len(results[0].boxes) > 0:
                    total_detections += len(results[0].boxes)
        
        cap.release()
        
        avg_people = total_detections / (frame_count / 5) if frame_count > 0 else 0
        
        return f"""
        📊 Detection Results:
        - Total Frames Processed: {frame_count}
        - Total Detections: {total_detections}
        - Average People per Frame: {avg_people:.2f}
        """
    
    except Exception as e:
        return f"Error processing video: {str(e)}"

# Gradio interface
demo = gr.Interface(
    fn=count_people,
    inputs=gr.Video(label="Upload Video"),
    outputs=gr.Textbox(label="Results"),
    title="🚪 Guest Entry/Exit Management System",
    description="Upload a video to detect and count people using YOLOv8",
    examples=[],
    theme=gr.themes.Soft()
)

if __name__ == "__main__":
    demo.launch()