model.yolo_license_plate

Description

πŸ”² License Plate Detection model.

class Node(config=None, **kwargs)[source]

Initializes and uses YOLO model to infer bboxes from image frame.

This customized YOLO node is capable of detecting objects from a single class (License Plate). It uses YOLOv4 by default and can be changed to use YOLOv4-tiny if FPS is critical over accuracy.

Inputs

img (numpy.ndarray): A NumPy array of shape \((height, width, channels)\) containing the image data in BGR format.

Outputs

bboxes (numpy.ndarray): A NumPy array of shape \((N, 4)\) containing normalized bounding box coordinates of \(N\) detected objects. Each bounding box is represented as \((x_1, y_1, x_2, y_2)\) where \((x_1, y_1)\) is the top-left corner and \((x_2, y_2)\) is the bottom-right corner. The order corresponds to bbox_labels and bbox_scores.

bbox_labels (numpy.ndarray): A NumPy array of shape \((N)\) containing strings representing the labels of detected objects. The order corresponds to bboxes and bbox_scores.

bbox_scores (numpy.ndarray): A NumPy array of shape \((N)\) containing confidence scores \([0, 1]\) of detected objects. The order corresponds to bboxes and bbox_labels.

Configs

  • model_type (str) – {β€œv4”, β€œv4tiny”}, default=”v4”.
    Defines the type of YOLO model to be used.

  • weights_parent_dir (Optional[str]) – default = null.
    Change the parent directory where weights will be stored by replacing null with an absolute path to the desired directory.

  • iou_threshold (float) – [0, 1], default = 0.3.
    Overlapping bounding boxes above the specified IoU (Intersection over Union) threshold are discarded.

  • score_threshold (float) – [0, 1], default = 0.1.
    Bounding box with confidence score less than the specified confidence score threshold is discarded.

References

YOLOv4: Optimal Speed and Accuracy of Object Detection: https://arxiv.org/pdf/2004.10934v1.pdf

Model weights trained using pretrained weights from Darknet: https://github.com/AlexeyAB/darknet

Changed in version 1.2.0:
yolo_iou_threshold is renamed to iou_threshold.
yolo_score_threshold is renamed to score_threshold.