Detect objects in image using a YOLO network

Works on a single input image only, at the moment.

Usage

ovml_yolo_detect(
  net,
  image_file,
  conf = 0.25,
  nms_conf = 0.45,
  classes,
  as,
  ...
)

net: yolo: as returned by ovml_yolo()
image_file: character: path to one or more image files, or a single video file (mp4, m4v, or mov extension)
conf: scalar: confidence level
nms_conf: scalar: non-max suppression confidence level
classes: character: vector of class names, only detections of these classes will be returned
as: string: for object detection networks, "boxes" (default and only option); for pose detection "segments" (default) or "keypoints"
...: : currently ignored

A data.frame with columns "image_number", "image_file", "class", "score", "xmin", "xmax", "ymin", "ymax", "frame"

if (FALSE) {
  dn <- ovml_yolo()
  img <- ovml_example_image()
  res <- ovml_yolo_detect(dn, img)
  ovml_ggplot(img, res)
}