SPRADH2 February   2024 AM62A3 , AM62A3-Q1 , AM62A7 , AM62A7-Q1 , AM62P , AM62P-Q1 , DS90UB953A-Q1 , DS90UB960-Q1 , TDES960 , TSER953

 

  1.   1
  2.   Abstract
  3.   Trademarks
  4. 1Introduction
  5. 2Connecting Multiple CSI-2 Cameras to the SoC
    1. 2.1 CSI-2 Aggregator Using SerDes
    2. 2.2 CSI-2 Aggregator without Using SerDes
  6. 3Enabling Multiple Cameras in Software
    1. 3.1 Camera Subsystem Software Architecture
    2. 3.2 Image Pipeline Software Architecture
  7. 4Reference Design
    1. 4.1 Supported Cameras
    2. 4.2 Setting up Four IMX219 Cameras
    3. 4.3 Configuring Cameras and CSI-2 RX Interface
    4. 4.4 Streaming from Four Cameras
      1. 4.4.1 Streaming Camera Data to Display
      2. 4.4.2 Streaming Camera Data through Ethernet
      3. 4.4.3 Storing Camera Data to Files
    5. 4.5 Multicamera Deep Learning Inference
      1. 4.5.1 Model Selection
      2. 4.5.2 Pipeline Setup
  8. 5Performance Analysis
  9. 6Summary
  10. 7References

4.5 Multicamera Deep Learning Inference

AM62A is equipped with a deep learning accelerator (C7x-MMA) with up to two TOPS, which are capable of running various types of deep learning models for classification, object detection, semantic segmentation, and more. This section shows how AM62A can simultaneously run four deep learning models on four different camera feeds.