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haixuanTao
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3 years ago | |
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| .gitignore | 3 years ago | |
| README.md | 3 years ago | |
| dataflow.yml | 3 years ago | |
| dataflow_without_webcam.yml | 3 years ago | |
| no_webcam.py | 3 years ago | |
| object_detection.py | 3 years ago | |
| plot.py | 3 years ago | |
| requirements.txt | 3 years ago | |
| run.rs | 3 years ago | |
| run.sh | 3 years ago | |
| utils.py | 3 years ago | |
| webcam.py | 3 years ago | |
README.md
Python Dataflow Example
This examples shows how to create and connect dora operators and custom nodes in Python.
Overview
The dataflow.yml defines a simple dataflow graph with the following three nodes:
- a webcam node, that connects to your webcam and feed the dataflow with webcam frame as jpeg compressed bytearray.
- an object detection node, that apply Yolo v5 on the webcam image. The model is imported from Pytorch Hub. The output is the bouding box of each object detected, the confidence and the class. You can have more info here: https://pytorch.org/hub/ultralytics_yolov5/
- a window plotting node, that will retrieve the webcam image and the Yolov5 bounding box and join the two together.
Getting started
cargo run --example python-dataflow
Installation
To install, you should run the install.sh script.
install.sh
Run the dataflow as a standalone
- Start the
dora-coordinator, passing the paths to the dataflow file and thedora-runtimeas arguments:
../../target/release/dora-coordinator --run-dataflow dataflow.yml ../../target/release/dora-runtime
DORA (Dataflow-Oriented Robotic Architecture) is middleware designed to streamline and simplify the creation of AI-based robotic applications. It offers low latency, composable, and distributed datafl
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