Pre-Trained Object Class Recognizers
OpenText 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.
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ObjectClassRecognizer_Gen4_CommonObjects80.datRecognizes 80 different types of common object (the same classes as the corresponding
Gen2recognizer). This is ageneration4recognizer and is expected to provide better accuracy than other types of recognizer, even more specialized recognizers such asObjectClassRecognizer_Gen3_PersonCar.dat. -
ObjectClassRecognizer_Gen3_CommonObjects20.datRecognizes common objects. The classes are the same as for the recognizer
ObjectClassRecognizer_CommonObjects.dat, but this is ageneration3recognizer that provides faster recognition than other types of recognizer. -
ObjectClassRecognizer_Gen3_PersonCar.datRecognizes people and cars. This is a
generation3recognizer that provides faster recognition than other types of recognizer. -
ObjectClassRecognizer_Gen2_CommonObjects80.datRecognizes 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.
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ObjectClassRecognizer_CommonObjects.datRecognizes 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
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ObjectClassRecognizer_HeadAndShoulder.datRecognizes 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.
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ObjectClassRecognizer_Person.datRecognizes people.
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ObjectClassRecognizer_RoadScene.datRecognizes 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.
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ObjectClassRecognizer_Gen4_Surveillance.datIntended for tracking objects as part of a surveillance configuration. The object classes are: person, car, bicycle, truck, motorcycle, bus. This is a
generation4recognizer, and is expected to provide better accuracy. -
ObjectClassRecognizer_Gen2_Surveillance.datIntended for tracking objects as part of a surveillance configuration. The object classes are: person, car, bicycle, truck, motorcycle, bus.