Mkdocs annotations fixes (#7600)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2024-01-15 23:37:37 +01:00 committed by GitHub
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24 changed files with 137 additions and 63 deletions

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@ -50,6 +50,7 @@ To perform object detection on an image, use the `predict` method as shown below
!!! Example
=== "Python"
```python
from ultralytics import FastSAM
from ultralytics.models.fastsam import FastSAMPrompt
@ -83,6 +84,7 @@ To perform object detection on an image, use the `predict` method as shown below
```
=== "CLI"
```bash
# Load a FastSAM model and segment everything with it
yolo segment predict model=FastSAM-s.pt source=path/to/bus.jpg imgsz=640
@ -97,6 +99,7 @@ Validation of the model on a dataset can be done as follows:
!!! Example
=== "Python"
```python
from ultralytics import FastSAM
@ -108,6 +111,7 @@ Validation of the model on a dataset can be done as follows:
```
=== "CLI"
```bash
# Load a FastSAM model and validate it on the COCO8 example dataset at image size 640
yolo segment val model=FastSAM-s.pt data=coco8.yaml imgsz=640

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@ -72,6 +72,7 @@ You can download the model [here](https://github.com/ChaoningZhang/MobileSAM/blo
!!! Example
=== "Python"
```python
from ultralytics import SAM
@ -87,6 +88,7 @@ You can download the model [here](https://github.com/ChaoningZhang/MobileSAM/blo
!!! Example
=== "Python"
```python
from ultralytics import SAM

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@ -148,6 +148,7 @@ Tests run on a 2023 Apple M2 Macbook with 16GB of RAM. To reproduce this test:
!!! Example
=== "Python"
```python
from ultralytics import FastSAM, SAM, YOLO
@ -183,6 +184,7 @@ To auto-annotate your dataset with the Ultralytics framework, use the `auto_anno
!!! Example
=== "Python"
```python
from ultralytics.data.annotator import auto_annotate

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@ -97,6 +97,7 @@ If you use YOLOv5 or YOLOv5u in your research, please cite the Ultralytics YOLOv
!!! Quote ""
=== "BibTeX"
```bibtex
@software{yolov5,
title = {Ultralytics YOLOv5},