Create app.py

app.py

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+import gradio as gr
+import cv2
+from detector import detect_cheating
+from utils import plot_cheating_graph, update_score
+
+def process_frame(frame):
+    frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
+    frame, cheating, persons = detect_cheating(frame)
+    update_score(cheating)
+    status = "Cheating Detected" if cheating else "Clean"
+    frame = cv2.putText(frame, f"Status: {status}", (10, 30),
+                        cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255) if cheating else (0,255,0), 2)
+    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+    graph = plot_cheating_graph()
+    return frame, graph
+
+iface = gr.Interface(
+    fn=process_frame,
+    inputs=gr.Image(source="webcam", streaming=True),
+    outputs=[gr.Image(label="Live Feed"), gr.Image(label="Cheating Score Graph")],
+    live=True,
+    title="AI Proctoring System",
+    description="Detects cheating based on number of persons and head orientation using YOLOv8."
+)
+
+iface.launch()