Object Detection using Detectron2

author: filip-halt, fzliu

Description

This operator uses Facebook's Detectron2 library to compute bounding boxes, class labels, and class scores for detected objects in a given image.

Code Example

import towhee

towhee.glob('./towhee.jpg') \
      .image_decode.cv2() \
      .object_detection.detectron2(model_name='retinanet_resnet50') \
      .show()

Factory Constructor

Create the operator via the following factory method

object_detection.detectron2(model_name='retinanet_resnet50', thresh=0.5, num_classes=1000, skip_preprocess=False)

Parameters:

model_name: str

A string indicating which model to use.

thresh: float

The threshold value for which an object is detected (default value: 0.5). Set this value lower to detect more objects at the expense of accuracy, or higher to reduce the total number of detections but increase the quality of detected objects.