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Here you can get any help you might need with installation, configuration, troubleshooting and others. Also you can report bugs or suggest improvements, we'll be glad to hear from you.

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RECOMMENDED HARDWARE

Runtime

  • For typical requirements - fast processing and convenient usage we recommend to use NVIDIA GPU with enough memory. A rough estimation is 6GB per deep-learning module. For basic projects we recommend using Nvidia GeForce RTX 3060 12GB and for more complex cases Nvidia GeForce RTX 3090 24GB or RTX A4000. For other PC components we advise to have at least: 512GB SSD, Intel Core i5 or AMD Ryzen 5 CPU not older than 3 years, 16 GB RAM.
  • For price sensitive use-cases it is possible to use cheaper NVIDIA GPU.
  • For embedded use-cases we support embedded hardware too - e.g. ARM based devices like NVIDIA Xavier. Contact us for more information.

Development

  • For typical requirements - fast processing and convenient usage we recommend to use NVIDIA GPU with enough memory. A rough estimation is 6GB per deep-learning module. For basic projects we recommend using Nvidia GeForce RTX 3060 12GB and for more complex cases Nvidia GeForce RTX 3090 24GB or RTX A4000. For other PC components we advise to have at least: 512GB SSD, Intel Core i5 or AMD Ryzen 5 CPU not older than 3 years, 16 GB RAM.

HOW TO INTEGRATE PEKAT VISION

Camera is directly connected to PEKAT VISION (GenICam camera)

This option is the easiest. PEKAT VISION processes input from the camera in a loop. You have to enable the camera and set what should happen after evaluation (output).

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PEKAT VISION is middleware

You use additional software for capturing images or processing. This method has 3 steps and requires programming knowledge.

  1. Send images to PEKAT
  2. For price sensitive use-cases it is possible to use cheaper NVIDIA GPU.
  3. For embedded use-cases we support embedded hardware too - e.g. ARM based devices like NVIDIA Xavier. Contact us for more information.

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