initial commit

app.py

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+import gradio as gr
+import cv2
+import numpy as np
+from ultralytics import YOLO
+import time
+
+# Load YOLO model
+model = YOLO("yolov8n.pt")  # Updated to correct model name
+
+# Define trapezoidal restricted area (top-left, top-right, bottom-right, bottom-left)
+trapezoid_pts = np.array([[250, 150], [400, 150], [450, 300], [200, 300]], np.int32)
+
+def is_inside_trapezoid(box, trapezoid_pts):
+    """Check if the center of a detected object is inside the trapezoidal area."""
+    x1, y1, x2, y2 = box
+    cx, cy = int((x1 + x2) / 2), int((y1 + y2) / 2)
+    return cv2.pointPolygonTest(trapezoid_pts, (cx, cy), False) >= 0
+
+def detect_objects(frame):
+    if frame is None:
+        return np.zeros((480, 640, 3), dtype=np.uint8), "No input frame"
+    
+    results = model.predict(frame, conf=0.5)
+    annotated_frame = results[0].plot()
+    
+    # Draw the trapezoid area
+    cv2.polylines(annotated_frame, [trapezoid_pts.reshape((-1, 1, 2))], isClosed=True, color=(0, 0, 255), thickness=2)
+    
+    isAlert = {"alert": [False, ""], "personCount": 0}
+    classInIntrusion = ["person", "bicycle", "car", "motorcycle"]
+    
+    for r in results:
+        for box, cls in zip(r.boxes.xyxy, r.boxes.cls):
+            class_id = int(cls.item())
+            if class_id == 0:  # Person
+                isAlert["personCount"] += 1
+            if class_id in [0, 1, 2, 3]:  # Person, bicycle, car, motorcycle
+                if is_inside_trapezoid(box.tolist(), trapezoid_pts):
+                    isAlert["alert"] = [True, classInIntrusion[class_id]]
+                    # Mark the intrusion with a red box
+                    x1, y1, x2, y2 = map(int, box.tolist())
+                    cv2.rectangle(annotated_frame, (x1, y1), (x2, y2), (0, 0, 255), 3)
+    
+    # Add alert text on the frame
+    alert_text = f"Intrusion Alert: {isAlert['alert'][0]}, Object: {isAlert['alert'][1]}, Persons: {isAlert['personCount']}"
+    cv2.putText(annotated_frame, alert_text, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+    
+    return annotated_frame, alert_text
+
+def webcam_feed():
+    cap = cv2.VideoCapture(0)
+    
+    # Check if the webcam opened successfully
+    if not cap.isOpened():
+        return np.zeros((480, 640, 3), dtype=np.uint8), "Failed to open webcam"
+    
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+        
+        # Process frame
+        result_frame, alert_message = detect_objects(frame)
+        
+        # Return the processed frame and alert message
+        yield result_frame, alert_message
+
+# Create the Gradio interface with webcam
+demo = gr.Interface(
+    fn=webcam_feed,
+    inputs=[],
+    outputs=[
+        gr.Image(label="Detection Output"),
+        gr.Textbox(label="Alert Status")
+    ],
+    live=True,
+    title="YOLO Intrusion Detection",
+    description="Real-time detection of persons and vehicles inside a restricted trapezoidal area.",
+    allow_flagging="never"
+)
+
+if __name__ == "__main__":
+    demo.queue(max_size=1).launch()