pypuclib

pypuclib is python package for INFINICAM SDK PUCLIB. This package allows user to control INFINICAM UC-1 on python.

infinicam_demo_python_tracking_en.mp4

*This is tracking_sample demo movie.

How to Use

1. Install INFINICAM SDK PUCLIB, driver, and Visual C++ Redistributable 2019.
2. See Install section to install pypuclib package.
3. See Quick Start section to start programming.

Install

You can install it in any of the following ways:

• Open command prompt and install using pip from pypi.

  pip install pypuclib
  

  If you don't register environment variable for python path, use this command instead.

  py -m pip install pypuclib
  

• Install from source code.

  git clone repositryURL
  

  Move current directory to pypuclib/pypuclib/ and install using this command.

  pip install ./
  

Quick Start for Image Processing

To connect the first detected camera:

cam = CameraFactory().create()

And grab the image:

xferdata = cam.grab()

To decode image, get decoder object from camera and use it like:

decoder = cam.decoder()
img = decoder.decode(xferdata)

Decoded array is numpy array, so now you can use to imageprocessing package like opencv directory.

If you want to use only the resion of interest:

x = 0, y = 0, w = 128, h = 128
img = decoder.decode(xferdata, x, y, w, h)

This can reduce the decoding time.

For High Speed Processing

Use beginXfer and endXfer to get callback from C++.

  # xfercallback from c++
  def callback(data) :
    seq = data.sequenceNo()
    if oldSeq != seq:
      # avoid same sequence number.


  # beginn xfer and start callback background
  cam.beginXfer(callback)

  ~~ # some processing here

  cam.endXfer()

How to Run Samples

1. Install pypuclib using pip.

2. Download following sample source code.

3. Run on python.

  python hello_world.py

• hello_world

  Sample of streaming a live image and saving a bitmap. If a GPU device is available, decoding is done on the GPU. Otherwise, decoding is done on the CPU.

• create_movie

  Sample of saving videos with high speed streaming.

• tracking_sample

  Sample of real-time tracking at 1,000 fps.

• gui_sample

  GUI sample for controlling camera parameters and recording.

• find_1000

  This sample code implements the a deep learning network to detect objects such as people, cellphones etc.

Source Code Structure

This repository consists of three projects.

• pypuclib

  Source code of python wrapper of PUCLIB

• pupuclib_sample

  Python sample code using pypuclib

• pypuclib_test

  Unit test of pypuclib

Prerequisites

To build pypuclib, the following environment is required.

• Installed Visual Studio 2019

　 ⚠️ The MSVC compiler is required to build the package.

　 ⚠️ This package is available for Windows only.

Issues

Don't hesitate to ask any questions or issues on GitHub.

developped by: