# Pre-Trained Object Class Recognizers

Micro Focus may provide pre-trained recognizers that you can use with Media Server to recognize objects belonging to generic categories 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.

- `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 differs from `ObjectDetector_Person.dat` because it 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.

- `ObjectClassRecognizer_Gen2_CommonObjects80.dat`

  Recognizes 80 different types of common object. This is a `generation2` 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.

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.

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