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

Creates or loads a YOLOv5 model Arguments: name (str): model name 'yolov5s' or path 'path/to/best.pt' pretrained (bool): load pre

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

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

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

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

Loop through the registered actions and fire all callbacks on main thread Args: hook: The name of the hook to check, def

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

Non-Maximum Suppression (NMS) on inference results to reject overlapping detections Returns: list of detections, on (n,6) tensor per ima

Loop through the registered actions and fire all callbacks Args: hook The name of the hook to check, defaults to all