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Referencia para ultralytics/models/nas/predict.py

Nota

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ultralytics.models.nas.predict.NASPredictor

Bases: BasePredictor

Ultralytics YOLO Predictor NAS para la detecci贸n de objetos.

Esta clase ampl铆a la clase BasePredictor del motor Ultralytics y se encarga del postprocesamiento de las predicciones brutas generadas por los modelos NAS de YOLO . Aplica operaciones como la supresi贸n de no m谩ximos y escalar los cuadros delimitadores para ajustarlos a las dimensiones de la imagen original.

Atributos:

Nombre Tipo Descripci贸n
args Namespace

Espacio de nombres que contiene varias configuraciones para el postprocesado.

Ejemplo
from ultralytics import NAS

model = NAS('yolo_nas_s')
predictor = model.predictor
# Assumes that raw_preds, img, orig_imgs are available
results = predictor.postprocess(raw_preds, img, orig_imgs)
Nota

Normalmente, esta clase no se instancia directamente. Se utiliza internamente dentro de NAS clase.

C贸digo fuente en ultralytics/models/nas/predict.py
class NASPredictor(BasePredictor):
    """
    Ultralytics YOLO NAS Predictor for object detection.

    This class extends the `BasePredictor` from Ultralytics engine and is responsible for post-processing the
    raw predictions generated by the YOLO NAS models. It applies operations like non-maximum suppression and
    scaling the bounding boxes to fit the original image dimensions.

    Attributes:
        args (Namespace): Namespace containing various configurations for post-processing.

    Example:
        ```python
        from ultralytics import NAS

        model = NAS('yolo_nas_s')
        predictor = model.predictor
        # Assumes that raw_preds, img, orig_imgs are available
        results = predictor.postprocess(raw_preds, img, orig_imgs)
        ```

    Note:
        Typically, this class is not instantiated directly. It is used internally within the `NAS` class.
    """

    def postprocess(self, preds_in, img, orig_imgs):
        """Postprocess predictions and returns a list of Results objects."""

        # Cat boxes and class scores
        boxes = ops.xyxy2xywh(preds_in[0][0])
        preds = torch.cat((boxes, preds_in[0][1]), -1).permute(0, 2, 1)

        preds = ops.non_max_suppression(
            preds,
            self.args.conf,
            self.args.iou,
            agnostic=self.args.agnostic_nms,
            max_det=self.args.max_det,
            classes=self.args.classes,
        )

        if not isinstance(orig_imgs, list):  # input images are a torch.Tensor, not a list
            orig_imgs = ops.convert_torch2numpy_batch(orig_imgs)

        results = []
        for i, pred in enumerate(preds):
            orig_img = orig_imgs[i]
            pred[:, :4] = ops.scale_boxes(img.shape[2:], pred[:, :4], orig_img.shape)
            img_path = self.batch[0][i]
            results.append(Results(orig_img, path=img_path, names=self.model.names, boxes=pred))
        return results

postprocess(preds_in, img, orig_imgs)

Postprocesa las predicciones y devuelve una lista de objetos Resultados.

C贸digo fuente en ultralytics/models/nas/predict.py
def postprocess(self, preds_in, img, orig_imgs):
    """Postprocess predictions and returns a list of Results objects."""

    # Cat boxes and class scores
    boxes = ops.xyxy2xywh(preds_in[0][0])
    preds = torch.cat((boxes, preds_in[0][1]), -1).permute(0, 2, 1)

    preds = ops.non_max_suppression(
        preds,
        self.args.conf,
        self.args.iou,
        agnostic=self.args.agnostic_nms,
        max_det=self.args.max_det,
        classes=self.args.classes,
    )

    if not isinstance(orig_imgs, list):  # input images are a torch.Tensor, not a list
        orig_imgs = ops.convert_torch2numpy_batch(orig_imgs)

    results = []
    for i, pred in enumerate(preds):
        orig_img = orig_imgs[i]
        pred[:, :4] = ops.scale_boxes(img.shape[2:], pred[:, :4], orig_img.shape)
        img_path = self.batch[0][i]
        results.append(Results(orig_img, path=img_path, names=self.model.names, boxes=pred))
    return results





Creado 2023-11-12, Actualizado 2024-05-18
Autores: glenn-jocher (4), Burhan-Q (1)