diff --git a/computer_vision/image_annotate.py b/computer_vision/image_annotate.py
new file mode 100644
index 000000000000..459aedf082c5
--- /dev/null
+++ b/computer_vision/image_annotate.py
@@ -0,0 +1,39 @@
+import supervision as sv
+from ultralytics import YOLO
+from PIL import Image
+import numpy as np
+import cv2
+
+
+def image_annotate(image: str) -> Image.Image:
+    # load the input image
+    image = cv2.imread(image)
+
+    # load pre-trained vision model
+    model = YOLO("yolo12s.pt")
+
+    # run object detection on the image
+    result = model(image)[0]
+
+    # convert YOLO output to a Supervision-compatible detections format
+    detections = sv.Detections.from_ultralytics(result)
+
+    # initialize a box annotator for drawing detection bounding boxes
+    box_annotator = sv.BoxAnnotator()
+
+    # annotate the image with detected objects
+    annotated_image = box_annotator.annotate(scene=image.copy(), detections=detections)
+
+    # convert BGR to RGB for correct display
+    annotated_image_rgb = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
+
+    # convert the annotated NumPy array (RGB) to a PIL Image object
+    annotated_pil_image = Image.fromarray(annotated_image_rgb)
+
+    # return annotated image
+    return annotated_pil_image
+
+
+if __name__ == "__main__":
+    annotate_img = image_annotate("/content/sample_data/Furry.png")
+    annotate_img.show()