save the metrics to the logging dictionary arguments: log_dict (Dict) -- metrics/media to be logged in current step

Creates a specified YOLOv5 model Arguments: name (str): name of model, i.e. 'yolov5s' pretrained (bool): load pretrained weights

Runs Non-Maximum Suppression (NMS) on inference results Returns: list of detections, on (n,6) tensor per image [xyxy, conf, cls]

Return intersection-over-union (Jaccard index) of boxes. Both sets of boxes are expected to be in (x1, y1, x2, y2) format. Arguments:

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

source - https://gist.github.com/simon-weber/7853144 A context manager that will prevent any logging messages triggered during the body from bein

Returns the intersection over box2 area given box1, box2. Boxes are x1y1x2y2 box1: np.array of shape(4) box2: np.array of shape(n

Check if the dataset format is compatible and upload it as W&B artifact arguments: opt (namespace)-- Commandline arguments f