Import Annotator class from ultralytics package (#11930)

* Import Annotator class from `ultralytics` package

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Import Annotator class from `ultralytics` package

* Update requirements.txt

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

---------

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

classify/predict.py

@@ -43,12 +43,13 @@ if str(ROOT) not in sys.path:
     sys.path.append(str(ROOT))  # add ROOT to PATH
 ROOT = Path(os.path.relpath(ROOT, Path.cwd()))  # relative
 
+from ultralytics.utils.plotting import Annotator
+
 from models.common import DetectMultiBackend
 from utils.augmentations import classify_transforms
 from utils.dataloaders import IMG_FORMATS, VID_FORMATS, LoadImages, LoadScreenshots, LoadStreams
 from utils.general import (LOGGER, Profile, check_file, check_img_size, check_imshow, check_requirements, colorstr, cv2,
                            increment_path, print_args, strip_optimizer)
-from utils.plots import Annotator
 from utils.torch_utils import select_device, smart_inference_mode
 
 
@@ -144,7 +145,7 @@ def run(
             # Write results
             text = '\n'.join(f'{prob[j]:.2f} {names[j]}' for j in top5i)
             if save_img or view_img:  # Add bbox to image
-                annotator.text((32, 32), text, txt_color=(255, 255, 255))
+                annotator.text([32, 32], text, txt_color=(255, 255, 255))
             if save_txt:  # Write to file
                 with open(f'{txt_path}.txt', 'a') as f:
                     f.write(text + '\n')