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Video Processing with FPGA
Rating: 3.7 out of 5(131 ratings)
1,203 students

Video Processing with FPGA

Implementing different Computer Vision Algorithm on Xilinx Zynq FPGA with VIVADO High Level Synthesis & SDK
Last updated 10/2022
English

What you'll learn

  • Implement different Computer Vision algorithm for Video Processing
  • Creating IP from the VIVADO High Level Synthesis
  • IP integration and configuration with Xilinx VIVADO
  • Xilinx SDK Application Development
  • Migrating the OpenCV algorithm on XfOpenCV
  • Simulating & Generating xfOpenCV codes in the VIVADO HLS
  • Integrating TPG, VDMA and Writing application for this blocks
  • Vitis HLS and OpenCV installation Session for 2020.2 or later

Course content

9 sections30 lectures4h 21m total length
  • VIVADO High Level Synthesis [HLS] Overview11:29
  • Overview of Xilinx VIVADO , IP and Zynq FPGA Architecture11:52
  • AXI Protocol Overview17:09

    This session is on detailing different AXI interfaces and getting familiar with AXI Protocols!

Requirements

  • Basics of FPGA Design
  • High Level Synthesis Basics
  • PC with installed VIVADO, HLS and SDK [we will also show the steps for installation]

Description

This Course is on implementing different Video Processing algorithm on FPGA. We implement the algorithm on High Level Synthesis [HLS], simulate it with the image input, generate & export IP from the HLS. The HLS IP is integrated with the necessary video processing pipeline [block design] and implemented on the FPGA Device.

We have "Implemented Sobel Edge Detection, Dilation, Histogram Equalize, Fast Corner like algorithm" on HLS and then FPGA. For the debugging the algorithm on the FPGA, we have initialized the Test Pattern Generator [TPG] IP and Video DMA [VDMA] for processing the image streams on the DDR with the Processing System involvement.

After Completing this course you will be able to:

  1. Utilized the HLS Video Processing Library and Implement as well as Simulate different OpenCV Algorithm on HLS

  2. Integrating the HLS IP with Video Processing Pipeline with TPG and VDMA and Implementing on the FPGA Device.

  3. Implementing the XfOpenCV [SDSoC] Library on HLS for Computer Vision

  4. Migrating the OpenCV algorithm into XfOpenCV

Who this course is for:

  • Electrical Engineering Enthusiast
  • Computer Science Enthusiast
  • FPGA Design Professional
  • Enthusiast of FPGA Design