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Update TFLite Docs images (#8605)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2024-03-03 01:59:43 +01:00 • committed by GitHub
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6
docs/en/usage/simple-utilities.md
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@ -20,7 +20,7 @@ The `ultralytics` package comes with a myriad of utilities that can support, enh
### Auto Labeling / Annotations
Dataset annotation is an _extremely_ resource heavy and time consuming process. If you have a YOLO object detection model trained on a reasonable amount of data, you can use it and [SAM](../models/sam.md) to auto-annotate additional data (segmentation format).
Dataset annotation is a very resource intensive and time-consuming process. If you have a YOLO object detection model trained on a reasonable amount of data, you can use it and [SAM](../models/sam.md) to auto-annotate additional data (segmentation format).
```{ .py .annotate }
from ultralytics.data.annotator import auto_annotate
@ -211,7 +211,7 @@ boxes.bboxes
See the [`Bboxes` reference section](../reference/utils/instance.md#ultralytics.utils.instance.Bboxes) for more attributes and methods available.
!!! tip
Many of the following functions (and more) can be accessed using the [`Bboxes` class](#bounding-box-horizontal-instances) but if you prefer to work with the functions directly, see the next sub-sections on how to import these independently.
Many of the following functions (and more) can be accessed using the [`Bboxes` class](#bounding-box-horizontal-instances) but if you prefer to work with the functions directly, see the next subsections on how to import these independently.
### Scaling Boxes
@ -385,7 +385,7 @@ for obb in obb_boxes:
image_with_obb = ann.result()
```
See the [`Annotator` Reference Page](../reference/utils/plotting.md#ultralytics.utils.plotting.Annotator) page for additional insight.
See the [`Annotator` Reference Page](../reference/utils/plotting.md#ultralytics.utils.plotting.Annotator) for additional insight.
## Miscellaneous