Create app.py

app.py

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+import gradio as gr
+from ultralytics import YOLO
+import cv2
+import numpy as np
+
+# Load the YOLOv8 model
+model = YOLO("yolov8n.pt")  # Replace with your trained brain tumor model
+
+def predict(image_path):
+    # Run YOLOv8 inference
+    results = model(image_path)
+    
+    # Get annotated image
+    annotated_frame = results[0].plot()
+    
+    # Convert BGR to RGB
+    annotated_frame_rgb = cv2.cvtColor(annotated_frame, cv2.COLOR_BGR2RGB)
+    
+    # Check if a tumor is detected
+    tumor_detected = len(results[0].boxes) > 0
+    detection_message = "Tumor Detected!" if tumor_detected else "No Tumor Detected."
+    
+    return annotated_frame_rgb, detection_message
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="filepath", label="Upload MRI Image"),
+    outputs=[
+        gr.Image(label="Detection Result"),
+        gr.Textbox(label="Diagnosis")
+    ],
+    title="Brain Tumor Detection with YOLOv8",
+    description="Upload an MRI scan to detect brain tumors using AI.",
+    allow_flagging="never"
+)
+
+interface.launch()