gradio component for image detection added

detect_utils.py

@@ -0,0 +1,41 @@
+import gradio as gr
+from ultralytics import YOLO
+import os
+import supervision as sv
+
+os.system("wget https://media.roboflow.com/notebooks/examples/dog.jpeg")
+os.system("wget https://media.roboflow.com/notebooks/examples/dog-2.jpeg")
+
+
+def detect(image, weights, slider_val):
+    model = YOLO(weights + '.pt')
+    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
+
+
+inputs_thresh = [
+    gr.inputs.Image(type="numpy", label="Input Image"),
+    gr.inputs.Radio(label="Detection Methods",
+                    choices=[
+                        "yolov5s", "yolov8s"
+                    ]),
+    gr.components.Slider(label="Class Probability Value",
+                         value=10, minimum=1, maximum=100, step=1),
+]
+
+outputs_thresh = [
+    gr.outputs.Image(type="numpy", label="Output Image")
+]
+
+detect_tab = gr.Interface(
+    detect,
+    inputs=inputs_thresh,
+    outputs=outputs_thresh,
+    title="supervision",
+    examples=[["dog.jpeg", "yolov5s"], ["dog-2.jpeg", "yolov8s"]],
+    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."
+)