─░├žeri─če ge├ž

Referans i├žin ultralytics/models/yolo/pose/train.py

Not

Bu dosya https://github.com/ultralytics/ultralytics/blob/main/ ultralytics/models/ yolo/pose/train .py adresinde mevcuttur. Bir sorun tespit ederseniz l├╝tfen bir ├çekme ─░ste─či ­čŤá´ŞĆ ile katk─▒da bulunarak d├╝zeltilmesine yard─▒mc─▒ olun. Te┼čekk├╝rler ­čÖĆ!



ultralytics.models.yolo.pose.train.PoseTrainer

├ťsler: DetectionTrainer

Bir poz modeline dayal─▒ e─čitim i├žin DetectionTrainer s─▒n─▒f─▒n─▒ geni┼čleten bir s─▒n─▒f.

├ľrnek
from ultralytics.models.yolo.pose import PoseTrainer

args = dict(model='yolov8n-pose.pt', data='coco8-pose.yaml', epochs=3)
trainer = PoseTrainer(overrides=args)
trainer.train()
Kaynak kodu ultralytics/models/yolo/pose/train.py
class PoseTrainer(yolo.detect.DetectionTrainer):
    """
    A class extending the DetectionTrainer class for training based on a pose model.

    Example:
        ```python
        from ultralytics.models.yolo.pose import PoseTrainer

        args = dict(model='yolov8n-pose.pt', data='coco8-pose.yaml', epochs=3)
        trainer = PoseTrainer(overrides=args)
        trainer.train()
        ```
    """

    def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
        """Initialize a PoseTrainer object with specified configurations and overrides."""
        if overrides is None:
            overrides = {}
        overrides["task"] = "pose"
        super().__init__(cfg, overrides, _callbacks)

        if isinstance(self.args.device, str) and self.args.device.lower() == "mps":
            LOGGER.warning(
                "WARNING ÔÜá´ŞĆ Apple MPS known Pose bug. Recommend 'device=cpu' for Pose models. "
                "See https://github.com/ultralytics/ultralytics/issues/4031."
            )

    def get_model(self, cfg=None, weights=None, verbose=True):
        """Get pose estimation model with specified configuration and weights."""
        model = PoseModel(cfg, ch=3, nc=self.data["nc"], data_kpt_shape=self.data["kpt_shape"], verbose=verbose)
        if weights:
            model.load(weights)

        return model

    def set_model_attributes(self):
        """Sets keypoints shape attribute of PoseModel."""
        super().set_model_attributes()
        self.model.kpt_shape = self.data["kpt_shape"]

    def get_validator(self):
        """Returns an instance of the PoseValidator class for validation."""
        self.loss_names = "box_loss", "pose_loss", "kobj_loss", "cls_loss", "dfl_loss"
        return yolo.pose.PoseValidator(
            self.test_loader, save_dir=self.save_dir, args=copy(self.args), _callbacks=self.callbacks
        )

    def plot_training_samples(self, batch, ni):
        """Plot a batch of training samples with annotated class labels, bounding boxes, and keypoints."""
        images = batch["img"]
        kpts = batch["keypoints"]
        cls = batch["cls"].squeeze(-1)
        bboxes = batch["bboxes"]
        paths = batch["im_file"]
        batch_idx = batch["batch_idx"]
        plot_images(
            images,
            batch_idx,
            cls,
            bboxes,
            kpts=kpts,
            paths=paths,
            fname=self.save_dir / f"train_batch{ni}.jpg",
            on_plot=self.on_plot,
        )

    def plot_metrics(self):
        """Plots training/val metrics."""
        plot_results(file=self.csv, pose=True, on_plot=self.on_plot)  # save results.png

__init__(cfg=DEFAULT_CFG, overrides=None, _callbacks=None)

Bir PoseTrainer nesnesini belirtilen yap─▒land─▒rmalar ve ge├žersiz k─▒lmalarla ba┼člat─▒n.

Kaynak kodu ultralytics/models/yolo/pose/train.py
def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
    """Initialize a PoseTrainer object with specified configurations and overrides."""
    if overrides is None:
        overrides = {}
    overrides["task"] = "pose"
    super().__init__(cfg, overrides, _callbacks)

    if isinstance(self.args.device, str) and self.args.device.lower() == "mps":
        LOGGER.warning(
            "WARNING ÔÜá´ŞĆ Apple MPS known Pose bug. Recommend 'device=cpu' for Pose models. "
            "See https://github.com/ultralytics/ultralytics/issues/4031."
        )

get_model(cfg=None, weights=None, verbose=True)

Belirtilen yap─▒land─▒rma ve a─č─▒rl─▒klarla poz tahmin modelini al─▒n.

Kaynak kodu ultralytics/models/yolo/pose/train.py
def get_model(self, cfg=None, weights=None, verbose=True):
    """Get pose estimation model with specified configuration and weights."""
    model = PoseModel(cfg, ch=3, nc=self.data["nc"], data_kpt_shape=self.data["kpt_shape"], verbose=verbose)
    if weights:
        model.load(weights)

    return model

get_validator()

Do─črulama i├žin PoseValidator s─▒n─▒f─▒n─▒n bir ├Ârne─čini d├Ând├╝r├╝r.

Kaynak kodu ultralytics/models/yolo/pose/train.py
def get_validator(self):
    """Returns an instance of the PoseValidator class for validation."""
    self.loss_names = "box_loss", "pose_loss", "kobj_loss", "cls_loss", "dfl_loss"
    return yolo.pose.PoseValidator(
        self.test_loader, save_dir=self.save_dir, args=copy(self.args), _callbacks=self.callbacks
    )

plot_metrics()

E─čitim/val metriklerini ├žizer.

Kaynak kodu ultralytics/models/yolo/pose/train.py
def plot_metrics(self):
    """Plots training/val metrics."""
    plot_results(file=self.csv, pose=True, on_plot=self.on_plot)  # save results.png

plot_training_samples(batch, ni)

A├ž─▒klamal─▒ s─▒n─▒f etiketleri, s─▒n─▒rlay─▒c─▒ kutular ve anahtar noktalar i├žeren bir grup e─čitim ├Ârne─čini ├žizin.

Kaynak kodu ultralytics/models/yolo/pose/train.py
def plot_training_samples(self, batch, ni):
    """Plot a batch of training samples with annotated class labels, bounding boxes, and keypoints."""
    images = batch["img"]
    kpts = batch["keypoints"]
    cls = batch["cls"].squeeze(-1)
    bboxes = batch["bboxes"]
    paths = batch["im_file"]
    batch_idx = batch["batch_idx"]
    plot_images(
        images,
        batch_idx,
        cls,
        bboxes,
        kpts=kpts,
        paths=paths,
        fname=self.save_dir / f"train_batch{ni}.jpg",
        on_plot=self.on_plot,
    )

set_model_attributes()

PoseModel'in anahtar noktalar─▒ ┼čekil niteli─čini ayarlar.

Kaynak kodu ultralytics/models/yolo/pose/train.py
def set_model_attributes(self):
    """Sets keypoints shape attribute of PoseModel."""
    super().set_model_attributes()
    self.model.kpt_shape = self.data["kpt_shape"]





Created 2023-11-12, Updated 2024-06-02
Authors: glenn-jocher (5), Burhan-Q (1)