Media Server 23.3

# 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.

- `ObjectClassRecognizer_Gen4_CommonObjects80.dat`

  Recognizes 80 different types of common object (the same classes as the corresponding `Gen2` recognizer). This is a `generation4` recognizer and is expected to provide better accuracy than other types of recognizer, even more specialized recognizers such as `ObjectClassRecognizer_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 a `generation3` 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.

Copyright 2023 Open Text
Version 23.3 | Last updated June 2023

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Product: IDOL Media Server 23.3

Topic Title: Pre-Trained Object Class Recognizers