gradio app with yolov5 inference with sample images added

app.py

@@ -0,0 +1,26 @@
+import os
+import gradio as gr
+import numpy as np
+import supervision as sv
+from ultralytics import YOLO
+
+
+def detect(image, weights):
+    model = YOLO(weights)
+    result = model(image, verbose=False)[0]
+    detections = sv.Detections.from_ultralytics(result)
+    box_annotator = sv.BoxAnnotator()
+    annotated_image = box_annotator.annotate(image.copy(), detections=detections)
+
+    return annotated_image
+
+
+if __name__ == '__main__':
+    gr.Interface(
+        detect, [gr.Image(type="numpy"), gr.Dropdown(choices=["yolov5s", "yolov5s6"])],
+        gr.Image(type="numpy"),
+        title="Yolov5",
+        examples=[["https://media.roboflow.com/notebooks/examples/dog.jpeg", "yolov5s"]],
+        description=
+        "Gradio based demo for <a href='https://github.com/roboflow/supervision' style='text-decoration: underline' target='_blank'>roboflow/supervision</a>, We write your reusable computer vision tools."
+    ).launch()