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Fix gitignore to format Docs datasets (#16071)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-09-06 17:17:33 +02:00 • committed by GitHub
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38
docs/en/datasets/segment/index.md
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@ -44,20 +44,20 @@ The Ultralytics framework uses a YAML file format to define the dataset and mode
```yaml
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/coco8-seg # dataset root dir
train: images/train # train images (relative to 'path') 4 images
val: images/val # val images (relative to 'path') 4 images
test: # test images (optional)
path: ../datasets/coco8-seg # dataset root dir
train: images/train # train images (relative to 'path') 4 images
val: images/val # val images (relative to 'path') 4 images
test: # test images (optional)
# Classes (80 COCO classes)
names:
0: person
1: bicycle
2: car
# ...
77: teddy bear
78: hair drier
79: toothbrush
0: person
1: bicycle
2: car
# ...
77: teddy bear
78: hair drier
79: toothbrush
```
The `train` and `val` fields specify the paths to the directories containing the training and validation images, respectively.
@ -141,7 +141,7 @@ To auto-annotate your dataset using the Ultralytics framework, you can use the `
```
| Argument | Type | Description | Default |
|--------------|-------------------------|-------------------------------------------------------------------------------------------------------------|----------------|
| ------------ | ----------------------- | ----------------------------------------------------------------------------------------------------------- | -------------- |
| `data` | `str` | Path to a folder containing images to be annotated. | `None` |
| `det_model` | `str, optional` | Pre-trained YOLO detection model. Defaults to `'yolov8x.pt'`. | `'yolov8x.pt'` |
| `sam_model` | `str, optional` | Pre-trained SAM segmentation model. Defaults to `'sam_b.pt'`. | `'sam_b.pt'` |
@ -175,15 +175,15 @@ This script converts your COCO dataset annotations to the required YOLO format,
To prepare a YAML file for training YOLO models with Ultralytics, you need to define the dataset paths and class names. Here's an example YAML configuration:
```yaml
path: ../datasets/coco8-seg # dataset root dir
train: images/train # train images (relative to 'path')
val: images/val # val images (relative to 'path')
path: ../datasets/coco8-seg # dataset root dir
train: images/train # train images (relative to 'path')
val: images/val # val images (relative to 'path')
names:
0: person
1: bicycle
2: car
# ...
0: person
1: bicycle
2: car
# ...
```
Ensure you update the paths and class names according to your dataset. For more information, check the [Dataset YAML Format](#dataset-yaml-format) section.