PYNQ FPGA Development with Python Programming & VIVADO
Learn how to implement face recognition, image and video processing, and machine learning algorithms on the PYNQ FPGA platform. This course covers the PYNQ development flow, GPIO interfacing, installing TensorFlow, and creating custom overlays. Suitable for electrical engineers, computer scientists, and hardware design enthusiasts.
What you’ll learn
- PYNQ Development Flow
- Implementing Face Recognition with PYNQ FPGA
- Image and Video Processing with PYNQ FPGA and Python Library
- Creating Custom Overlay for PYNQ on VIVADO
- Machine Learning Algorithm Implementation on PYNQ
- Installing Tensorflow on PYNQ and Implementing Neural Network on PYNQ
- Python Programming with Jupyter Interface on Internet Browser
PYNQ (Python+Zynq), An FPGA development platform from Xilinx is an Open Source FPGA development platform. This Course covers from the Architecture of PYNQ (Zynq 7000), PYNQ Development Flow, Basic GPIO interfacing with PYNQ FPGA, Image Processing with PYNQ, using PYNQ libraries as sci_pi, OpenCV, Installing Tensorflow on PYNQ,Machine Learning with Pynq, Neural Network Implementation on PYNQ, Creating Custom PYNQ Overlay on Xilinx VIVADO .
After completing this course you will also know about the Acceleration methodology on the PYNQ Development Platform. Another important section of this course is Implementation of Machine Learning Algorithms on Python for Image Processing and other projects. We will implement Artificial Neural Networks (ANN) algorithms as CNN, BNN and other Neural Networks for real time projects as Number Plate Recognition, Face Recognition etc.
At the another section we will have sessions on “How to design Overlay system with VIVADO for PYNQ FPGA”. This session is based on the VIVADO HLS & IP integrator for creating custom Overlay.
Who this course is for:
- Electrical Engineering
- Computer Science
- Hardware Design Enthusiast
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