Create app.py

app.py

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+import torch
+import gradio as gr
+from PIL import Image
+
+# Load pre-trained YOLOv5 model from ultralytics
+model = torch.hub.load('ultralytics/yolov5', 'yolov5s')
+
+def detect_objects(image):
+    # Perform inference
+    results = model(image)
+    results.render()  # updates results.imgs with boxes and labels
+    detected_image = Image.fromarray(results.imgs[0])
+    return detected_image
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=detect_objects,
+    inputs=gr.inputs.Image(type="pil"),
+    outputs=gr.outputs.Image(type="pil"),
+    title="Object Detection with YOLOv5",
+    description="Upload an image and get the detected objects with their names."
+)
+
+# Launch the interface
+iface.launch()