AVETO.app DataForwarding Measurement Object

A sample implementation to be able to forward individual data streams from AVETO to external software and vice versa
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Communication
5. Message format
6. Contributing
7. License

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About The Project

The project consists of three components:

• Data Forwarding Measurement Object
• Data Backwarding Measurement Object
• Python example for the receiving side

Data Forwarding Measurement Object

Object: Processor Object
Name: Data Forwarding
Input: Generic Connector "*"
Output: -

Properties:

Property Name	Type	Default	Description
FPS Limit	uint32_t	5	FPS limit for the forwarding data stream
No Payload	bool	false	true: Only meta data is forwarded false: Meta data and data is forwarded

Once created, data packets coming in over a connection are forwarded to each connected client. By default, the forwarding frame rate is limited to 5 frames per second. This limit can be changed using the FPS Limit property.

By default, the complete packet data and additional metadata is forwarded. If you set the No Payload property to true, only the metadata is sent.

Data Backwarding Measurement Object

Object: Processor Object
Name: Data Backwarding
Input: -
Output: RGBA-Image and JSON meta data

After creation, the data sent from the client side is output through the output connectors.

Python example

The project includes a small Python example that allows the user to receive data from the AVETO site, display it, and return data that has been processed.

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Built With

3rd party components measurement objects:

• cppzmq 4.8.1
• msgpack 3.3.0

3rd party components python example:
See example/requirements.txt

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Getting Started

Clone this repository and make sure you fulfill following requirements

Prerequisites

• Installed AVETO.app >= 2.4.0
• Set AVETO_SDK_PATH as environment variable which by default points to the folder C:\Program Files\b-plus\AVETO.app\sdk
• Installed Windows SDK-Version 10.0.17763.0
• Installed cppzmq and msgpack
• The firewall must be set so that the AVETO Visualization host can be reached on the ports used for communication.
  • Default ports: 5770 - 5789 (TCP), 5870 - 5889 (TCP)

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Installation

1. Install AVETO.app
2. Clone the repo

   git clone https://github.com/bplus-group/aveto_mo_data_forwarding.git

3. Adapt the include and library directories in the Visual Studio Solution that it finds the cppzmq and msgpack dependencies
4. Build the project
5. Copy the DLLs to your AVETO MO directory (default: %USERPROFILE%\Documents\AVETO\measobj\)

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Usage

Right-click in the node graph editor of the configuration manager and choose Processor Objects -> Data Forwarding MO and Data Backwarding MO as seen below.

Connect the input and output connectors of the objects according to your requirements. An example is shown below.

Use the included python example

1. Build the example container:

   docker build ./example/ -t data-forwarding-example

2. Determine the ip address of the AVETO Visualization host.

3. Run the example:

   docker run -it --rm \
       -e AVETO_HOST="<HOST_IP>" \
       data-forwarding-example
   
   # or with gui access   
    docker run -it --rm \
       -e AVETO_HOST="<HOST_IP>" \
       -e DISPLAY=$DISPLAY \
       -v /tmp/.X11-unix:/tmp/.X11-unix \
       data-forwarding-example
    

NOTE: You can also use the example without docker

NOTE: By default the forwarding is limited to 5fps (can be changed via properties)

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Communication

ZeroMQ is used for forwarding and backwarding the data. Every datasource gets its own channel/port (starts at 0, default limit: 20)

The following data can currently be forwarded:

• image -> RGBA camera images
• raw -> every other data type
• metadata_only -> no payload only metadata (can be enabled via mo properties)

If you want to receive data, you have to connect to a ZeroMQ PubSocket (default port 5770 + Channel (TCP)) and subscribe to the corresponding topic.

List of current available topics:

• out/image0

If you want to send data, you have to connect to a PullSocket and send the corresponding message to it.

Direction	AVETO.vis socket type	AVETO.vis port	Application socket type
forwarding	publisher socket	5770 + Channel	subscriber socket
backwarding	pull socket	5870 + Channel	push socket

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Message format

For encoding the messages MsgPack is used.

Message formats:

//////////////////////////////////
// Forwarding Message Definition:
//////////////////////////////////


//////////// Base MSG ////////////
1. Source     | string        | the source where the message originates from (default: "image0")
2. Timestamp  | unit64        | the timestamp of the AVETO data packet
3. Type       | string        | the type of the payload (currently supported: ["image", "raw", "metadata_only"])
4. Format     | string        | the format of the payload ("RGBA" for image type and the name of the connector in Vis. for all other types)

5. FormatSize | array<int, 3> | description of the the payload format structure (width, height, bits per pixel) (only used for "image")
6. Image      | bin format    | the payload as 1D byte array



//////////////////////////////////
// Backwarding Message Definition:
//////////////////////////////////


//////////// Base MSG ////////////
1. Target     | string        | the destination (output channel) to which the msg should go (default: "image0")
2. Timestamp  | unit64        | the timestamp of the AVETO data packet (used to match the results to original frames)
3. Type       | string        | the type of the payload (currently supported: ["image"])
4. Format     | string        | the format of the payload (currently supported: ["RGBA"])

//////////// RGBA MSG ////////////
5. FormatSize | array<int, 3> | description of the the payload format structure (width, height, bits per pixel)
6. MetaData   | string        | used for the meta data channel (JSON format, e.g. for list of detections, ...)
7. Image      | bin format    | the image payload as 1D byte array

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Contributing

If you have a suggestion that would improve this, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/NewFeature)
3. Commit your Changes (git commit -m 'Add some NewFeature')
4. Push to the Branch (git push origin feature/NewFeature)
5. Open a Pull Request

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License

Check License information. See LICENSE for more information.

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