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1004 B
detectron2
Object Detection using Detectron2
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.
1004 B
detectron2
Object Detection using Detectron2
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.