Pre-Trained Object Class Recognizers
Micro Focus may provide pre-trained recognizers that you can use with Media Server to recognize objects in images and videos.
The following recognizers are currently available, in the package MediaServerPretrainedModels_<VERSION>_COMMON.zip
. When you download this package, ensure that <VERSION>
matches the version of Media Server that you are using.
For information about the different types of recognizers, see Recognizer Types. For information about how to import a recognizer into your training database, see Import a Recognizer.
Visual Analytics
To use the following recognizers, Media Server must be able to request a visual channel from your License Server.
-
ObjectClassRecognizer_Gen4_CommonObjects80.dat
Recognizes 80 different types of common object (the same classes as the corresponding
Gen2
recognizer). This is ageneration4
recognizer and is expected to provide better accuracy than other types of recognizer, even more specialized recognizers such asObjectClassRecognizer_Gen3_PersonCar.dat
. -
ObjectClassRecognizer_Gen3_CommonObjects20.dat
Recognizes common objects. The classes are the same as for the recognizer
ObjectClassRecognizer_CommonObjects.dat
, but this is ageneration3
recognizer that provides faster recognition than other types of recognizer. -
ObjectClassRecognizer_Gen3_PersonCar.dat
Recognizes people and cars. This is a
generation3
recognizer that provides faster recognition than other types of recognizer. -
ObjectClassRecognizer_Gen2_CommonObjects80.dat
Recognizes 80 different types of common object.
The object classes are: aeroplane, apple, backpack, banana, baseball bat, baseball glove, bear, bed, bench, bicycle, bird, boat, book, bottle, bowl, broccoli, bus, cake, car, carrot, cat, cell phone, chair, clock, cow, cup, diningtable, dog, donut, elephant, fire hydrant, fork, frisbee, giraffe, hair drier, handbag, horse, hot dog, keyboard, kite, knife, laptop, microwave, motorbike, mouse, orange, oven, parking meter, person, pizza, pottedplant, refrigerator, remote, sandwich, scissors, sheep, sink, skateboard, skis, snowboard, sofa, spoon, sports ball, stop sign, suitcase, surfboard, teddy bear, tennis racket, tie, toaster, toilet, toothbrush, traffic light, train, truck, tvmonitor, umbrella, vase, wine glass, zebra.
-
ObjectClassRecognizer_CommonObjects.dat
Recognizes common objects. This recognizer contains twenty classes across four categories:
- (Person) person
- (Animal) bird, cat, cow, dog, horse, sheep
- (Vehicle) aeroplane, bicycle, boat, bus, car, motorbike, train
- (Indoor) bottle, chair, dining table, potted plant, sofa, tv/monitor
-
ObjectClassRecognizer_HeadAndShoulder.dat
Recognizes people, in order to count them. This recognizer has been trained to detect only the head and shoulder region, which is useful when you want to count people in a crowded area.
-
ObjectClassRecognizer_Person.dat
Recognizes people.
-
ObjectClassRecognizer_RoadScene.dat
Recognizes cars, vans and people.
Surveillance Analytics
To use the following recognizers, Media Server must be able to request a visual or surveillance channel from your License Server.
-
ObjectClassRecognizer_Gen4_Surveillance.dat
Intended for tracking objects as part of a surveillance configuration. The object classes are: person, car, bicycle, truck, motorcycle, bus. This is a
generation4
recognizer, and is expected to provide better accuracy. -
ObjectClassRecognizer_Gen2_Surveillance.dat
Intended for tracking objects as part of a surveillance configuration. The object classes are: person, car, bicycle, truck, motorcycle, bus.