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Configure the CIDR IntelliVision module as follows:

  1. Go to the settings panle of the CIDR IntelliVision module object created under on the basis of the LPR channel object.

  2. Set the Use GPU checkbox(1) checkbox if if it is necessary to use the NVIDIA GPU resources to increase the license plate recognition performance. By default, only the CPU resources are used.

    Note
    titleAttention!

    The startup (initialization) of the license plate recognition algorithm on NVIDIA GPU can take about one minute. No LP recognition events will be received until the initialization is complete.


  3. Select the numbers recognition accuracy in the Accuracy drop-down list(2) drop-down list. The following options are available:
    1. Maximum - enables Maximum—enables maximum recognition accuracy, but it causes great CPU and/or GPU load.  
    2. High - enables High—enables high recognition accuracy, it requires less computing less computing resources than for maximum accuracy.
    3. Fast - enables Fast—enables high recognition speed, but while reducing the recognition accuracy becomes worse.
  4. Select the computing resources use mode in the Strategy drop-down list(3) drop-down list. The following options are available:
    1. Process  - mild Process—mild mode: no more than 1 one core for 1 one license plate.
    2. System - default System—default mode: all available computing cores are in useused;
    3. Core  - strict Core—strict mode: 1 one core per one stream.
  5. Specify In the Interval field (4), specify the minimum time interval lasting in milliseconds that lasts between the frames processing for the Interval (4) parameter (i.e. all frames within this interval won't will not be processed). The range of values is 0-999, the default value is 0.
  6. The Profile drop-down list (5) displays the license plate recognition quality profile. At the moment, only profile 6 is used, which provides high performance (high processing speed and low CPU usage).
  7. Click the Apply button (6).

Configuration of the CIDR IntelliVision module is completed.