From 515c63e477c4d1532d87cf78ecb58b2dfc25d284 Mon Sep 17 00:00:00 2001
From: Ifeanyi Idiaye <72707830+Ifeanyi55@users.noreply.github.com>
Date: Thu, 9 Oct 2025 19:26:06 +0100
Subject: [PATCH 1/2] Created image_annotate.py

---
 computer_vision/image_annotate.py | 39 +++++++++++++++++++++++++++++++
 1 file changed, 39 insertions(+)
 create mode 100644 computer_vision/image_annotate.py

diff --git a/computer_vision/image_annotate.py b/computer_vision/image_annotate.py
new file mode 100644
index 000000000000..68df69fa43a0
--- /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()

From d4a50412a114aa37d98d43fefe35fa36fa5e7a1a Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 9 Oct 2025 18:27:51 +0000
Subject: [PATCH 2/2] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 computer_vision/image_annotate.py | 48 +++++++++++++++----------------
 1 file changed, 24 insertions(+), 24 deletions(-)

diff --git a/computer_vision/image_annotate.py b/computer_vision/image_annotate.py
index 68df69fa43a0..459aedf082c5 100644
--- a/computer_vision/image_annotate.py
+++ b/computer_vision/image_annotate.py
@@ -4,36 +4,36 @@
 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")
+def image_annotate(image: str) -> Image.Image:
+    # load the input image
+    image = cv2.imread(image)
 
-  # run object detection on the image
-  result = model(image)[0]
+    # load pre-trained vision model
+    model = YOLO("yolo12s.pt")
 
-  # convert YOLO output to a Supervision-compatible detections format
-  detections = sv.Detections.from_ultralytics(result)
+    # run object detection on the image
+    result = model(image)[0]
 
-  # initialize a box annotator for drawing detection bounding boxes
-  box_annotator = sv.BoxAnnotator()
+    # convert YOLO output to a Supervision-compatible detections format
+    detections = sv.Detections.from_ultralytics(result)
 
-  # 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)
+    # initialize a box annotator for drawing detection bounding boxes
+    box_annotator = sv.BoxAnnotator()
 
-  # convert the annotated NumPy array (RGB) to a PIL Image object
-  annotated_pil_image = Image.fromarray(annotated_image_rgb)
+    # 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
 
-  # return annotated image
-  return annotated_pil_image
 
 if __name__ == "__main__":
-  annotate_img = image_annotate("/content/sample_data/Furry.png")
-  annotate_img.show()
+    annotate_img = image_annotate("/content/sample_data/Furry.png")
+    annotate_img.show()