Added from Yolov9

app.py

@@ -0,0 +1,22 @@
+import gradio as gr
+from ultralytics import YOLO
+from PIL import Image
+import numpy as np
+
+# Load the YOLOv9 model
+model = YOLO('best.pt')  # Make sure best.pt is in the same folder
+
+def detect(image):
+    results = model(image)
+    annotated_frame = results[0].plot()  # Draw predictions on the image
+    return Image.fromarray(annotated_frame)
+
+# Launch the Gradio interface
+gr.Interface(
+    fn=detect,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="YOLOv9 (Ultralytics) Object Detection",
+    description="Upload an image to run object detection using your custom YOLOv9 model.",
+).launch()
+

best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bac45e3f015ac183637df63558f4f6d1c0908e87cbc7a91eaa09a6e3e1af276e
+size 40842779

requirements.txt

@@ -0,0 +1,3 @@
+ultralytics>=8.1.5
+gradio
+Pillow