Create app.py

app.py

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+import gradio as gr
+import torch
+import cv2
+import numpy as np
+from PIL import Image
+from ultralytics import YOLO
+
+# Load YOLOv11 Model
+model_path = "best.pt" 
+model = YOLO(model_path)
+
+def predict(image):
+    image = np.array(image)
+    results = model(image)
+
+    # Draw bounding boxes
+    for result in results:
+        for box in result.boxes:
+            x1, y1, x2, y2 = map(int, box.xyxy[0])
+            conf = box.conf[0]
+            cls = int(box.cls[0])
+            label = f"{model.names[cls]} {conf:.2f}"
+            cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 2)
+            cv2.putText(image, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
+
+    return Image.fromarray(image)
+
+# Gradio Interface
+iface = gr.Interface(fn=predict, inputs="image", outputs="image", title="YOLOv11 Object Detection")
+iface.launch()