Appends a new transform to the existing list of transforms.

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

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

Concatenate a new MaskData object to the current one.

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

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

Return an ItemsView of the MaskData object.

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

Get current time.

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

Converts list of transforms to a standard Python list.

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

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

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

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

Saves the current settings to the YAML file.

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

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

Display an image in a window using OpenCV imshow().

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

Return platform-dependent emoji-safe version of string.

Return a list of non-empty attribute names.

Plot image grid with labels.

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

Run all existing callbacks associated with a particular event.

Initialize Conv layer with given arguments including activation.

Update self.im from a numpy array.

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

Add rectangle to image (PIL-only).

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

Returns a loss dict with labelled training loss items tensor

Update confusion matrix for object detection task. Args: detections (Array[N, 6]): Detected bounding boxes and their ass

Raises TypeError is model is not a PyTorch model

Convert bounding box format.

Increments a file or directory path, i.e. runs/exp --> runs/exp{sep}2, runs/exp{sep}3, ... etc. If the path exists and exist_ok is not set t

Adds text to an image using PIL or cv2.

Update the boxes, masks, and probs attributes of the Results object.

Convert bounding box coordinates from (x1, y1, x2, y2) format to (x, y, width, height) format. Args: x (np.ndarray | torch.Tensor):

De-parallelize a model: returns single-GPU model if model is of type DP or DDP.

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

Check if the current script is running inside a Google Colab notebook. Returns: (bool): True if running inside a Colab notebook, Fal

Return a new Results object with the same image, path, and names.

Plot the confusion matrix using seaborn and save it to a file. Args: normalize (bool): Whether to normalize the confusio

Selects PyTorch Device. Options are device = None or 'cpu' or 0 or '0' or '0,1,2,3'.

Perform object tracking on the input source using the registered trackers. Args: source (str, optional): The input sourc

Convert bounding box coordinates from (x, y, width, height) format to (x1, y1, x2, y2) format where (x1, y1) is the top-left corner and (x2,

Save YAML data to a file. Args: file (str, optional): File name. Default is 'data.yaml'. data (dict): Data to save in YAML f

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

Apply object detection on a raw frame using specified method.

Strip auth from URL, i.e. https://url.com/file.txt?auth -> https://url.com/file.txt.

Returns device if PyTorch model.

Mean of results, return mp, mr, map50, map.

Calculate intersection-over-union (IoU) of boxes. Both sets of boxes are expected to be in (x1, y1, x2, y2) format. Based on https://gith

class-aware result, return p[i], r[i], ap50[i], ap[i].

Determines whether the current file is part of a git repository. If the current file is not part of a git repository, returns None. Retu

Return model info dict with useful model information. Example for YOLOv8n: {'model/parameters': 3151904, 'model/GFLOPs': 8.

Downloads files from a URL, with options for retrying, unzipping, and deleting the downloaded file. Args: url (str): The URL of the

load/create/download model for any task.

Makes an HTTP request using the 'requests' library, with exponential backoff retries up to a specified timeout. Args: method (str):

Initialize the BboxLoss module with regularization maximum and DFL settings.

Initialize an ensemble of models.

Args: dim (int): Number of input channels. num_heads (int): Number of attention heads in each ViT block.

Computes the average precision per class for object detection evaluation. Args: tp (np.ndarray): Binary array indicating whether the

Loads a single model weights.

Calculate Intersection over Union (IoU) of box1(1, 4) to box2(n, 4). Args: box1 (torch.Tensor): A tensor representing a single bound

This function checks for any mismatched keys between a custom configuration list and a base configuration list. If any mismatched keys are fo

Search/download file (if necessary) and return path.

Verify image size is a multiple of the given stride in each dimension. If the image size is not a multiple of the stride, update it to the ne

Check if environment supports image displays.

Search/download YAML file (if necessary) and return path, checking suffix.

Denormalizes boxes, segments, and keypoints from normalized coordinates.

Issue a deprecation warning when a deprecated argument is used, suggesting an updated argument.

Export model. Args: **kwargs : Any other args accepted by the predictors. To see all args check 'configuration' section

YOLOv8 export formats.

Model fitness as a weighted combination of metrics.

Determines if the file at the given filepath is part of a pip package. Args: filepath (str): The filepath to check. Returns:

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

Method used for CLI prediction. It uses always generator as outputs as not required by CLI mode.

Runs all registered callbacks for a specific event.

PyTorch-accurate time.

Validate a model on a given dataset. Args: data (str): The dataset to validate on. Accepts all formats accepted by yolo