xupsh / pynq-computervision

Computer Vision Overlays on Pynq

PYNQ - Computer Vision

All PYNQ releases ship with the popular OpenCV library pre-installed. The PYNQ computer vision overlays enable accelerating OpenCV components in Programmable Logic (PL). These overlays expose a subset Xilinx' xfOpenCV library (a part of Xilinx' reVISION solution) at the Python level, combined with the support for HDMI input/output. Note that webcam, stream or file based input/output remains available through the pre-installed SW OpenCV.

Currently, two overlays are available for the Pynq-Z1 board:

• 2D filter & dilate: accelerated 3x3 2D filter and 3x3 dilate. Open the filter2d_and_dilate_example notebook for demo and more details.
• 2D filter & remap: accelerated 3x3 2D filter and remap. Open the filter2d_and_remap_example notebook for demo and more details.

Quick Start

To install the computer vision overlay example on your Pynq-Z1 board (with the latest PYNQ-Z1 image), open a terminal and run:

$ sudo -H pip3.6 install --upgrade git+https://github.com/Xilinx/PYNQ-ComputerVision.git

After the setup, new Jupyter notebooks will be added under the computer_vision folder, ready to try out, no additional steps are needed.

Building Your Own Overlay

When after profiling, the critical OpenCV modules in an application are identified, the generation of a tailored overlay is easily done by specifying those modules as a list in a CMake project file. After that, building the tailored overlay only requires running cmake to generate the Makefiles followed by make to build the overlay.

For detailed instructions: Building xfOpenCV Overlays for Pynq: CMake based sds++ cross-compilation.

License

The source for this project is licensed under the 3-Clause BSD License