ultralytics 8.0.123 Ubuntu security and VideoWriter codec fixes (#3380)

This commit is contained in:
Glenn Jocher
2023-06-25 23:59:28 +02:00
committed by GitHub
parent 8b50b2a897
commit b5a2be8ca8
5 changed files with 41 additions and 76 deletions

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@ -37,44 +37,31 @@ Here is an example of the YOLO dataset format for a single image with two object
Note: The length of each row does not have to be equal.
** Dataset file format **
### Dataset YAML format
The Ultralytics framework uses a YAML file format to define the dataset and model configuration for training Detection Models. Here is an example of the YAML format used for defining a detection dataset:
```yaml
train: <path-to-training-images>
val: <path-to-validation-images>
nc: <number-of-classes>
names: [<class-1>, <class-2>, ..., <class-n>]
# 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)
# Classes (80 COCO classes)
names:
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.
The `nc` field specifies the number of object classes in the dataset.
The `names` field is a list of the names of the object classes. The order of the names should match the order of the object class indices in the YOLO dataset files.
NOTE: Either `nc` or `names` must be defined. Defining both are not mandatory.
Alternatively, you can directly define class names like this:
```yaml
names:
0: person
1: bicycle
```
** Example **
```yaml
train: data/train/
val: data/val/
nc: 2
names: ['person', 'car']
```
`names` is a dictionary of class names. The order of the names should match the order of the object class indices in the YOLO dataset files.
## Usage