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🦉 Introduction


Excerpt

In this section we discribe posibilities possibilities to build your own younique smart vison system by using the provided infastructur of iam camera.

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Example

Repositorys

Repositories

There are different example Git repository for the iam camera system.

smart

Smart app example with third party

libary

library

smart

Smart app with hardware accelerations and third party

libarys
  • smart app with hardware accelerations and third party libarys

libraries

ccode_synview

  • dice_synview

  • remap_synview

  • https://bitbucket.org/net-gmbh/iam_apps/

    ccode_synview

    The example code_synview uses HLS hw acceleration written in c-code.

    Main processing method can be selected among following choices:

    • no processing

    • simple c-code sw processing

    • a optimized c-code version with ARM NEON instructions

    • processing with opencv functions

    • hw accelerated processing based on a c-code source

    After processing the image is sent out via gige - server.

    https://bitbucket.org/net-gmbh/iam_apps/

    remap_synview

    The example remap_synview uses the hw acceleration function xf::cv::remap from the Vitis vision library.

    After processing the image is sent out via gige - server.

    https://bitbucket.org/net-gmbh/iam_apps/

    dice_synview

    The example dice_synview demonstrates dice cube detection and dots counting for each cube. It uses multiple xfOpenCV functions.

    https://bitbucket.org/net-gmbh/iam_apps/

    rtl_threshold_synview

    This example uses RTL hw acceleration written in verilog.

    After processing the image is sent out via gige - server.

    https://bitbucket.org/net-gmbh/iam_apps/

    strm_rtl_threshold_synview

    This example uses RTL hw acceleration in the streaming path.
    The module is located between the sensor interface and the dma.
    It consists of a 32-Bit master and 32-Bit slave axi-stream interface for sensor pixel data and a 32-Bit axi-lite control interface for register access.

    After processing the image is sent out via gige - server.

    https://bitbucket.org/net-gmbh/iam_apps/

    sw_scaler_synview

    This example uses no hw acceleration.
    But it uses the same infrastructure like other hw accelerated examples.
    The main processing consists of a simple c-code scaler for horizontal and vertical rescaling.

    After processing the image is sent out via gige - server.

    https://bitbucket.org/net-gmbh/iam_apps/

    smart

    Smart app example with machine learning

    dpuClassify

    • Reference application for image classifier training and execution.

    • Different convolutional models are available (VGG, DenseNet, ResNet, Inception)

    • Training code for transfere transfer learning with Keras and Tensorflow

    • Vitis Ai model conversion code

    • iam application for image classification

    https://bitbucket.org/net-gmbh/iam_ml/

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