depthai-gui 2.0.6

DepthAI Pipeline Visualizer GUI

Gen2 Visual Pipeline Editor

This experiment has two components:

1. A visual graph editor that lets you compose a DepthAI pipeline visually and save it as a JSON file.
2. A parser for those JSON files that will turn it into a usable DepthAI pipeline

Editor

The graph editor is a modified version of NodeGraphQt by Johnny Chan.

Installation

To install this tool, run the following command

$ python3 -m pip install depthai-gui

Usage

To run the visual pipeline editor, run the following command

$ depthai-gui

Navigation

• Press Tab to create new nodes
• Right Click To save/load pipeline graphs
• You can find a full list of controls in the NodeGraphQt Documentation

You can also provide optional arguments, like default context path (-p / --path) or the project file to open (-o / --open)

$ depthai-gui --help
usage: depthai-gui [-h] [-p PATH] [-o OPEN]

optional arguments:
  -h, --help            show this help message and exit
  -p PATH, --path PATH  Path to save/load default directory
  -o OPEN, --open OPEN  Path to project file to open

Also, you can use the demo program that will run the generated pipeline (or default ExampleGraph.json) with the following command

$ depthai-gui-demo  # to run a default ExampleGraph.json
$ depthai-gui-demo -p <path>  # to run a custom pipeline

Local development

If you want to enhance or modify this script or would like to install it without PyPi, please install all the necessary requirements with

$ python3 install_requirements.py

Next, you can check the following files:

• pipeline_editor.py - Runs the visual pipeline editor (eqivalent of depthai-gui)
• demo.py- Runs the demo script (equivalent of depthai-gui-demo)
• DAIPipelineGraph.py is the graph parser.

Using exported pipeline

If you want to use the generated pipeline in your application, you can do so by importing DAIPipelineGraph module.

And example integration is shown below

from DAIPipelineGraph import DAIPipelineGraph

pipeline_graph = DAIPipelineGraph( path=pipeline_path )

with dai.Device( pipeline_graph.pipeline ) as device:
  ...

The most useful fields you can use from DAIPipelineGraph class are:

• DAIPipelineGraph.pipeline: A reference to the DepthAI pipeline
• DAIPipelineGraph.nodes: A table of all the nodes. You can access them via the name you put into the "Node Name" field in the editor. Ex: pipeline_graph.nodes["rgb_cam"].setPreviewSize(300,300)
• DAIPipelineGraph.xout_streams: A list of all the names of the XLinkOut streams

You can also check the demo script as a reference on how to make a working scripts with this class