Reference for ultralytics/models/nas/model.py
Note
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ultralytics.models.nas.model.NAS
NAS(model: str = 'yolo_nas_s.pt')
Bases: Model
YOLO-NAS model for object detection.
This class provides an interface for the YOLO-NAS models and extends the Model
class from Ultralytics engine.
It is designed to facilitate the task of object detection using pre-trained or custom-trained YOLO-NAS models.
Attributes:
Name | Type | Description |
---|---|---|
model |
Module
|
The loaded YOLO-NAS model. |
task |
str
|
The task type for the model, defaults to 'detect'. |
predictor |
NASPredictor
|
The predictor instance for making predictions. |
validator |
NASValidator
|
The validator instance for model validation. |
Methods:
Name | Description |
---|---|
info |
Log model information and return model details. |
Examples:
>>> from ultralytics import NAS
>>> model = NAS("yolo_nas_s")
>>> results = model.predict("ultralytics/assets/bus.jpg")
Notes
YOLO-NAS models only support pre-trained models. Do not provide YAML configuration files.
Source code in ultralytics/models/nas/model.py
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task_map
property
task_map: Dict[str, Dict[str, Any]]
Return a dictionary mapping tasks to respective predictor and validator classes.
info
info(detailed: bool = False, verbose: bool = True) -> Dict[str, Any]
Log model information.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
detailed
|
bool
|
Show detailed information about model. |
False
|
verbose
|
bool
|
Controls verbosity. |
True
|
Returns:
Type | Description |
---|---|
Dict[str, Any]
|
Model information dictionary. |
Source code in ultralytics/models/nas/model.py
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