Initialize YOLO network with default parameters and Convolutional Layers.

Builds the selected SAM model architecture.

Logs images to the experiment with optional annotations.

Perform a forward pass through the network. Args: x (torch.Tensor): The input tensor to the model. profile (

Attempt file download from GitHub release assets if not found locally. release = 'latest', 'v6.2', etc.

Return an InfiniteDataLoader or DataLoader for training or validation set.

Download, check and/or unzip dataset if not found locally.

Converts bounding box format from one type to another.

It takes a mask and a bounding box, and returns a mask that is cropped to the bounding box Args: masks (torch.Tensor): [n, h, w] tenso

Returns a list of HUB-supported export formats.

Return file/dir size (MB).

Guess the task of a PyTorch model from its architecture or configuration. Args: model (nn.Module | dict): PyTorch model or model con

Check if a directory is writeable. Args: dir_path (str | Path): The path to the directory. Returns: (bool): True if the

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

Generate anchors from features.

Convert model output to target format [batch_id, class_id, x, y, w, h, conf] for plotting.

Plot training results.csv. Usage: from utils.plots import *; plot_results('path/to/results.csv').

Perform prediction using the YOLO model. Args: source (str | int | PIL | np.ndarray): The source of the image to make pr

Process predicted results for object detection and update metrics.

Runs all callbacks associated with a specified event.

Load model/trainer/validator/predictor.

Update a matched track :type new_track: STrack :type frame_id: int :return:

Convert URL to filename, i.e. https://url.com/file.txt?auth -> file.txt.

Load a YOLOv8 model from a YAML file.

Initialize the Boxes class.

Returns metadata for YOLO training including epoch and asset saving status.

Log scalars to the NeptuneAI experiment logger.

Return correct prediction matrix Arguments: detections (array[N, 6]), x1, y1, x2, y2, conf, class labels (arr

Separate the input tensor into the specified number of attention heads.

Attempt to authenticate with the server using either id_token or API key. Returns: bool: True if authentication is succe

Decode predicted object bounding box coordinates from anchor points and distribution.

Build a SAM model specified by ckpt.

Check class names. Map imagenet class codes to human-readable names if required. Convert lists to dicts.

Check file(s) for acceptable suffix.

判断img_url路径是否含有中文字符 :param img_url: 图片路径 :return: True or False

It takes a list of bounding boxes and a shape (height, width) and clips the bounding boxes to the shape Args: boxes (torch.Tensor)

Convert a bounding box's top-left-width-height format to its x-y-angle-height equivalent.

YOLOv8 ONNX export.

Reverses the order of the bounding boxes and segments horizontally.

Fuse the `Conv2d()` and `BatchNorm2d()` layers of the model into a single layer, in order to improve the computation efficiency.

Return GitHub repo tag and assets (i.e. ['yolov8n.pt', 'yolov8s.pt', ...]).

Check if a string is composed of only ASCII characters. Args: s (str): String to be checked. Returns: bool: True if the

Check if the current script is running inside a Kaggle kernel. Returns: (bool): True if running inside a Kaggle kernel, False otherw

Check internet connectivity by attempting to connect to a known online host. Returns: (bool): True if connection is successful, Fals

Combine two lists of stracks into a single one.

Returns a list of keys for accessing specific metrics.

Returns the mean Average Precision (mAP) over IoU thresholds of 0.5 - 0.95 in steps of 0.05. Returns: (float): The mAP o

Model information. imgsz may be int or list, i.e. imgsz=640 or imgsz=[640, 320].

Plots a metric-confidence curve.

Pre-transform input image before inference. Args: im (List(np.ndarray)): (N, 3, h, w) for tensor, [(h, w, 3) x N] for list.

Perform a forward pass through the network. Args: x (torch.Tensor): The input tensor to the model. profile (

Preprocesses the target counts and matches with the input batch size to output a tensor.

this might be similar with denormalize func but without normalized sign.

Streams real-time inference on camera feed and saves results to file.

Decorator to make all processes in distributed training wait for each local_master to do something.

Update features vector and smooth it using exponential moving average.

Return a human-readable string representation of the object.

Add metadata to *.tflite models per https://www.tensorflow.org/lite/models/convert/metadata.

Return labels with mosaic border instances clipped.

Get losses

Log the confusion matrix to Comet experiment.

Log files (images) as debug samples in the ClearML task. Args: files (list): A list of file paths in PosixPath format. title

Logs predicted boxes for a single image during training.

Log scalars to the NeptuneAI experiment logger.

Log the best-trained model to Comet.ml.

Logs scalar values to TensorBoard.

Create a new video capture object.

From PyTorch internals.

Positionally encode points that are normalized to [0,1].

Return correct prediction matrix Arguments: detections (array[N, 6]), x1, y1, x2, y2, conf, class labels (arr

Return correct prediction matrix Arguments: detections (array[N, 6]), x1, y1, x2, y2, conf, class labels (arr

Profile the computation time and FLOPs of a single layer of the model on a given input. Appends the results to the provided list.

Update labels.

Add a callback.

Handle rect and mosaic situation.

Loads an ensemble of models weights=[a,b,c] or a single model weights=[a] or weights=a.

Pad to 'same' shape outputs.

Calculates boxes in XYXY format around masks. Return [0,0,0,0] for an empty mask. For input shape C1xC2x...xHxW, the output shape is C1xC2x..

Benchmark a YOLO model across different formats for speed and accuracy. Args: model (str | Path | optional): Path to the model file

Add one xyxy box to image with label.

Build YOLO Dataset

Convert a configuration object to a dictionary, whether it is a file path, a string, or a SimpleNamespace object. Args: cfg (str | P