Create app.py

app.py

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+import numpy as np
+import gradio as gr
+from ultralytics import YOLO
+
+# Load a pretrained YOLO model
+model = YOLO('yolov8n.pt') # Or any other suitable YOLO model
+
+def predict_image_class(input_img):
+    """Predicts the class of objects in an image using the YOLO model."""
+    results = model.predict(source=input_img, conf=0.25) # Adjust confidence threshold as needed
+    
+    # Process results and extract classes
+    predicted_classes = []
+    for r in results:
+        boxes = r.boxes
+        for box in boxes:
+            cls = model.names[int(box.cls)]
+            predicted_classes.append(cls)
+
+    return ", ".join(predicted_classes) # Return a string of comma-separated classes
+
+demo = gr.Interface(
+    fn=predict_image_class,
+    inputs=gr.Image(type="filepath"), # Accept image filepaths as input
+    outputs="text",
+    title="Image Class Prediction with YOLO",
+    description="Upload an image and get predictions of the object classes present."
+)
+
+demo.launch(debug=True)