Appends a new transform to the existing list of transforms.

Appends a new transform to the existing list of transforms.

Concatenate a new MaskData object to the current one.

Concatenate a new MaskData object to the current one.

Sends the model to the given device. Args: device (str): device

Sends the model to the given device. Args: device (str): device

Return the value of the specified key if it exists; otherwise, return the default value.

Return the value of the specified key if it exists; otherwise, return the default value.

Return an ItemsView of the MaskData object.

Return a copy of the Results object with all tensors on CPU memory.

Return a copy of the Results object with all tensors as numpy arrays.

Return a copy of the Results object with all tensors on CPU memory.

Return a copy of the Results object with all tensors as numpy arrays.

Logs model info. Args: detailed (bool): Show detailed information about model. verbose (bool): Controls verb

Logs model info. Args: detailed (bool): Show detailed information about model. verbose (bool): Controls verb

Return an ItemsView of the MaskData object.

Concatenate a list of Bboxes objects into a single Bboxes object. Args: boxes_list (List[Bboxes]): A list of Bboxes obje

Return a list of non-empty attribute names.

Concatenate a list of Bboxes objects into a single Bboxes object. Args: boxes_list (List[Bboxes]): A list of Bboxes obje

Return a list of Detections objects, i.e. 'for result in results.tolist():'.

Logs model info. Args: detailed (bool): Show detailed information about model. verbose (bool): Controls verb

Logs model info. Args: detailed (bool): Show detailed information about model. verbose (bool): Controls verb

Args: results (tuple): A tuple of (p, r, ap, f1, ap_class)

Logs model info. Args: detailed (bool): Show detailed information about model. verbose (bool): Controls verb

Logs model info. Args: detailed (bool): Show detailed information about model. verbose (bool): Controls verb

Colors a string https://en.wikipedia.org/wiki/ANSI_escape_code, i.e. colorstr('blue', 'hello world').

Colors a string https://en.wikipedia.org/wiki/ANSI_escape_code, i.e. colorstr('blue', 'hello world').

Return a list of non-empty attribute names.

Return a list of Detections objects, i.e. 'for result in results.tolist():'.

Convert a numpy array to a tensor. Args: x (np.ndarray): The array to be converted. Returns: (

Logs model info. Args: detailed (bool): Show detailed information about model. verbose (bool): Controls verb

r"""This control method is called from ``Env`` on each ``step``.

r"""Main method of trainer evaluation. Calls _eval_checkpoint() that is specified in Trainer class that inherits from BaseRLTrainer or

Get current time.

r"""Main method of trainer evaluation. Calls _eval_checkpoint() that is specified in Trainer class that inherits from BaseRLTrainer or

Converts list of transforms to a standard Python list.

Converts list of transforms to a standard Python list.

Prints model information Args: verbose (bool): if True, prints out the model information. Defaults to False

Prints model information Args: verbose (bool): if True, prints out the model information. Defaults to False

Get current time.

Check if installed dependencies meet YOLOv8 requirements and attempt to auto-update if needed. Args: requirements (Union[Path, str,

Convert a numpy array to a tensor. Args: x (np.ndarray): The array to be converted. Returns: (

Args: results (tuple): A tuple of (p, r, ap, f1, ap_class)

Check if installed dependencies meet YOLOv8 requirements and attempt to auto-update if needed. Args: requirements (Union[Path, str,

Returns device if PyTorch model.

Save detection results with optional labels to specified directory.

Apply object detection on a raw frame using specified method.

Load the weights into the model. Args: weights (dict | torch.nn.Module): The pre-trained weights to be loaded. verbos

r"""This control method is called from ``Env`` on each ``step``.

Return a copy of the Results object with all tensors on GPU memory.

Save detection results with optional labels to specified directory.

Clips bounding boxes, segments, and keypoints values to stay within image boundaries.

Clips bounding boxes, segments, and keypoints values to stay within image boundaries.

r"""Main method of trainer evaluation. Calls _eval_checkpoint() that is specified in Trainer class that inherits from BaseRLTrainer or

Load and merge configuration data from a file or dictionary. Args: cfg (str | Path | Dict | SimpleNamespace): Configuration data.

Returns device if PyTorch model.

Load and merge configuration data from a file or dictionary. Args: cfg (str | Path | Dict | SimpleNamespace): Configuration data.

Transfers parameters with matching names and shapes from 'weights' to model.

Transfers parameters with matching names and shapes from 'weights' to model.

Check current version against the required minimum version. Args: current (str): Current version. minimum (str): Required mi

Check current version against the required minimum version. Args: current (str): Current version. minimum (str): Required mi

Return platform-dependent emoji-safe version of string.

Return platform-dependent emoji-safe version of string.

Update self.im from a numpy array.

Apply object detection on a raw frame using specified method.

Run all existing callbacks associated with a particular event.

Run all existing callbacks associated with a particular event.

Initialize Conv layer with given arguments including activation.

Initialize Conv layer with given arguments including activation.

Args: offset (tuple | list | int): the offset for four coords.

Logs model info. Args: detailed (bool): Show detailed information about model. verbose (bool): Controls verb

Load YAML data from a file. Args: file (str, optional): File name. Default is 'data.yaml'. append_filename (bool): Add the Y

Load YAML data from a file. Args: file (str, optional): File name. Default is 'data.yaml'. append_filename (bool): Add the Y

Update self.im from a numpy array.