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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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2
docs/en/usage/cfg.md
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@ -194,7 +194,7 @@ The val (validation) settings for YOLO models involve various hyperparameters an
| `max_det` | `int` | `300` | Limits the maximum number of detections per image. Useful in dense scenes to prevent excessive detections. |
| `half` | `bool` | `True` | Enables half-precision (FP16) computation, reducing memory usage and potentially increasing speed with minimal impact on accuracy. |
| `device` | `str` | `None` | Specifies the device for validation (`cpu`, `cuda:0`, etc.). Allows flexibility in utilizing CPU or GPU resources. |
| `dnn` | `bool` | `False` | If `True`, uses OpenCV's DNN module for ONNX model inference, offering an alternative to PyTorch inference methods. |
| `dnn` | `bool` | `False` | If `True`, uses the OpenCV DNN module for ONNX model inference, offering an alternative to PyTorch inference methods. |
| `plots` | `bool` | `False` | When set to `True`, generates and saves plots of predictions versus ground truth for visual evaluation of the model's performance. |
| `rect` | `bool` | `False` | If `True`, uses rectangular inference for batching, reducing padding and potentially increasing speed and efficiency. |
| `split` | `str` | `val` | Determines the dataset split to use for validation (`val`, `test`, or `train`). Allows flexibility in choosing the data segment for performance evaluation. |

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docs/en/usage/python.md
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@ -249,7 +249,7 @@ Benchmark mode is used to profile the speed and accuracy of various export forma
## Explorer
Explorer API can be used to explore datasets with advanced semantic, vector-similarity and SQL search among other features. It also searching for images based on their content using natural language by utilizing the power of LLMs. The Explorer API allows you to write your own dataset exploration notebooks or scripts to get insights into your datasets.
Explorer API can be used to explore datasets with advanced semantic, vector-similarity and SQL search among other features. It also enabled searching for images based on their content using natural language by utilizing the power of LLMs. The Explorer API allows you to write your own dataset exploration notebooks or scripts to get insights into your datasets.
!!! Example "Semantic Search Using Explorer"

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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