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Update simple-utilities.md (#16417)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Muhammad Rizwan Munawar 2024-09-22 18:35:18 +05:00 • committed by GitHub
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docs/en/usage/simple-utilities.md
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@ -460,15 +460,16 @@ for obb in obb_boxes:
image_with_obb = ann.result()
```
#### Bounding Boxes Circle Annotation ([Circle Label](https://docs.ultralytics.com/reference/utils/plotting/#ultralytics.utils.plotting.Annotator.circle_label))
#### Bounding Boxes Circle Annotation [Circle Label](https://docs.ultralytics.com/reference/utils/plotting/#ultralytics.utils.plotting.Annotator.circle_label)
```python
import cv2
from ultralytics import YOLO
from ultralytics.utils.plotting import Annotator, colors
from ultralytics.utils.plotting import Annotator
model = YOLO("yolov8s.pt")
names = model.names
cap = cv2.VideoCapture("path/to/video/file.mp4")
w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
@ -479,15 +480,13 @@ while True:
if not ret:
break
annotator = Annotator(im0, line_width=2)
annotator = Annotator(im0)
results = model.predict(im0)
boxes = results[0].boxes.xyxy.cpu()
clss = results[0].boxes.cls.cpu().tolist()
for box, cls in zip(boxes, clss):
x1, y1 = int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2)
annotator.circle_label(box, label=model.names[int(cls)], color=colors(int(cls), True))
annotator.circle_label(box, label=names[int(cls)])
writer.write(im0)
cv2.imshow("Ultralytics circle annotation", im0)
@ -500,15 +499,16 @@ cap.release()
cv2.destroyAllWindows()
```
#### Bounding Boxes Text Annotation ([Text Label](https://docs.ultralytics.com/reference/utils/plotting/#ultralytics.utils.plotting.Annotator.text_label))
#### Bounding Boxes Text Annotation [Text Label](https://docs.ultralytics.com/reference/utils/plotting/#ultralytics.utils.plotting.Annotator.text_label)
```python
import cv2
from ultralytics import YOLO
from ultralytics.utils.plotting import Annotator, colors
from ultralytics.utils.plotting import Annotator
model = YOLO("yolov8s.pt")
names = model.names
cap = cv2.VideoCapture("path/to/video/file.mp4")
w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
@ -519,15 +519,13 @@ while True:
if not ret:
break
annotator = Annotator(im0, line_width=2)
annotator = Annotator(im0)
results = model.predict(im0)
boxes = results[0].boxes.xyxy.cpu()
clss = results[0].boxes.cls.cpu().tolist()
for box, cls in zip(boxes, clss):
x1, y1 = int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2)
annotator.text_label(box, label=model.names[int(cls)], color=colors(int(cls), True))
annotator.text_label(box, label=names[int(cls)])
writer.write(im0)
cv2.imshow("Ultralytics text annotation", im0)