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Add automatic nightly sanity check (#192)
* Add automatic nightly check * fix * Add badge * remove conditions * Remove develop badge * restore name
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Diff for: ‎.github/workflows/tests_sources.yml renamed to ‎.github/workflows/tests_suite.yml

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name: Test Sources
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name: Test Suite (master)
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on:
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pull_request:
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types: [opened, synchronize, reopened, ready_for_review, labeled, unlabeled]
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schedule:
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- cron: '0 23 * * *'
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defaults:
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run:

Diff for: ‎.github/workflows/tests_suite_develop.yml

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name: Test Suite (develop)
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on:
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schedule:
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- cron: '0 23 * * *'
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defaults:
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run:
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shell: bash
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jobs:
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cleanup-runs:
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if: ${{ contains(github.event.pull_request.labels.*.name, 'test sources') || contains(github.event.pull_request.labels.*.name, 'test tools') }}
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runs-on: ubuntu-latest
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steps:
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- uses: rokroskar/workflow-run-cleanup-action@master
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env:
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GITHUB_TOKEN: "${{ secrets.GITHUB_TOKEN }}"
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test-sources:
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needs: cleanup-runs
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if: ${{ contains(github.event.pull_request.labels.*.name, 'test sources') }}
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strategy:
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matrix:
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os: [ubuntu-18.04, ubuntu-20.04, macos-10.15]
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include:
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- os: ubuntu-18.04
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DEPENDENCIES_INSTALLATION: "sudo apt -y install clang-format-10 cppcheck"
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- os: ubuntu-20.04
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DEPENDENCIES_INSTALLATION: "sudo apt -y install clang-format-10 cppcheck"
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- os: macos-10.15
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DEPENDENCIES_INSTALLATION: "brew install clang-format cppcheck"
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runs-on: ${{ matrix.os }}
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steps:
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- uses: actions/checkout@v2
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if: matrix.os == 'ubuntu-20.04' || github.event.pull_request.draft == false
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with:
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submodules: true
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ref: develop
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- name: Set up Python 3.8
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if: matrix.os == 'ubuntu-20.04' || github.event.pull_request.draft == false
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uses: actions/setup-python@v2
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with:
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python-version: 3.8
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- name: Test Sources
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if: matrix.os == 'ubuntu-20.04' || github.event.pull_request.draft == false
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run: |
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${{ matrix.DEPENDENCIES_INSTALLATION }}
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export OPENDR_HOME=$PWD
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export OPENDR_DEVICE=cpu
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pip install -r tests/requirements.txt
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python -m unittest discover -s tests
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test-tools:
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needs: cleanup-runs
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if: ${{ contains(github.event.pull_request.labels.*.name, 'test tools') }}
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strategy:
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matrix:
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os: [ubuntu-20.04]
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package:
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- engine
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- utils
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- perception/activity_recognition
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- perception/compressive_learning
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- perception/face_recognition
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- perception/heart_anomaly_detection
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- perception/multimodal_human_centric
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- perception/object_tracking_2d
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- perception/object_detection_3d
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- perception/pose_estimation
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- perception/speech_recognition
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- perception/skeleton_based_action_recognition
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- perception/semantic_segmentation
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- control/mobile_manipulation
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- perception/object_detection_2d
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- simulation/human_model_generation
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- perception/facial_expression_recognition/landmark_based_facial_expression_recognition
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- control/single_demo_grasp
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# - perception/object_tracking_3d
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include:
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- os: ubuntu-20.04
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DEPENDENCIES_INSTALLATION: "sudo sh -c 'echo \"deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main\" > /etc/apt/sources.list.d/ros-latest.list' \
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&& curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | sudo apt-key add -"
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runs-on: ${{ matrix.os }}
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steps:
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- uses: actions/checkout@v2
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with:
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submodules: true
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ref: develop
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- name: Set up Python 3.8
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uses: actions/setup-python@v2
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with:
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python-version: 3.8
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- name: Test Tools
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if: ${{ contains(github.event.pull_request.labels.*.name, 'test tools') }}
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run: |
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${{ matrix.DEPENDENCIES_INSTALLATION }}
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export OPENDR_HOME=$PWD
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export OPENDR_DEVICE=cpu
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export PYTHONPATH=$OPENDR_HOME/src:$PYTHONPATH
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export DISABLE_BCOLZ_AVX2=true
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export ROS_DISTRO=noetic
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make install_compilation_dependencies
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make install_runtime_dependencies
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pip install -r tests/sources/requirements.txt
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if [ ${{ matrix.package }} = "ctests" ]; then
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make ctests
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else
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source tests/sources/tools/control/mobile_manipulation/run_ros.sh
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python -m unittest discover -s tests/sources/tools/${{ matrix.package }}
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fi

Diff for: ‎README.md

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<p align="center">
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<a href="https://www.opendr.eu/">Website</a> •
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<a href="#about">About</a> •
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<a href="docs/reference/installation.md">Installation</a> •
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<a href="docs/reference/installation.md">Installation</a> •
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<a href="#using-opendr-toolkit">Using OpenDR toolkit</a> •
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<a href="projects">Examples</a> •
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<a href="#roadmap">Roadmap</a> •
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<a href="#roadmap">Roadmap</a> •
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<a href="LICENSE">License</a>
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</p>
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[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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[![Test Suite (master)](https://github.com/opendr-eu/opendr/actions/workflows/tests_suite.yml/badge.svg)](https://github.com/opendr-eu/opendr/actions/workflows/tests_suite.yml)
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</div>
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## About
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The aim of [OpenDR Project](https://opendr.eu) is to develop a **modular, open** and **non-proprietary toolkit** for core **robotic functionalities** by harnessing **deep learning** to provide advanced perception and cognition capabilities, meeting in this way the general requirements of robotics applications in the applications areas of healthcare, agri-food and agile production.
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OpenDR provides the means to link the **robotics applications to software libraries** (deep learning frameworks, e.g., [PyTorch](https://pytorch.org/) and [Tensorflow](https://www.tensorflow.org/)) to the **operating environment ([ROS](https://www.ros.org/))**.
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The aim of [OpenDR Project](https://opendr.eu) is to develop a **modular, open** and **non-proprietary toolkit** for core **robotic functionalities** by harnessing **deep learning** to provide advanced perception and cognition capabilities, meeting in this way the general requirements of robotics applications in the applications areas of healthcare, agri-food and agile production.
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OpenDR provides the means to link the **robotics applications to software libraries** (deep learning frameworks, e.g., [PyTorch](https://pytorch.org/) and [Tensorflow](https://www.tensorflow.org/)) to the **operating environment ([ROS](https://www.ros.org/))**.
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OpenDR focuses on the **AI and Cognition core technology** in order to provide tools that make robotic systems cognitive, giving them the ability to:
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1. interact with people and environments by developing deep learning methods for **human centric and environment active perception and cognition**,
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2. **learn and categorize** by developing deep learning **tools for training and inference in common robotics settings**, and
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2. **learn and categorize** by developing deep learning **tools for training and inference in common robotics settings**, and
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3. **make decisions and derive knowledge** by developing deep learning tools for cognitive robot action and decision making.
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As a result, the developed OpenDR toolkit will also enable cooperative human-robot interaction as well as the development of cognitive mechatronics where sensing and actuation are closely coupled with cognitive systems thus contributing to another two core technologies beyond AI and Cognition.
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OpenDR aims to develop, train, deploy and evaluate deep learning models that improve the technical capabilities of the core technologies beyond the current state of the art.
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As a result, the developed OpenDR toolkit will also enable cooperative human-robot interaction as well as the development of cognitive mechatronics where sensing and actuation are closely coupled with cognitive systems thus contributing to another two core technologies beyond AI and Cognition.
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OpenDR aims to develop, train, deploy and evaluate deep learning models that improve the technical capabilities of the core technologies beyond the current state of the art.
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## Installing OpenDR Toolkit
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## Using OpenDR toolkit
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OpenDR provides an intuitive and easy to use **[Python interface](src/opendr)**, a **[C API](src/c_api) for performance critical application**, a wealth of **[usage examples and supporting tools](projects)**, as well as **ready-to-use [ROS nodes](projects/opendr_ws)**.
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OpenDR is built to support [Webots Open Source Robot Simulator](https://cyberbotics.com/), while it also extensively follows industry standards, such as [ONNX model format](https://onnx.ai/) and [OpenAI Gym Interface](https://gym.openai.com/).
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OpenDR is built to support [Webots Open Source Robot Simulator](https://cyberbotics.com/), while it also extensively follows industry standards, such as [ONNX model format](https://onnx.ai/) and [OpenAI Gym Interface](https://gym.openai.com/).
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You can find detailed documentation in OpenDR [wiki](https://github.com/tasostefas/opendr_internal/wiki), as well as in the [tools index](docs/reference/index.md).
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## Roadmap
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- **v3.0 (2023)**: Active perception-enabled deep learning tools for improved robotic perception
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## How to contribute
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Please follow the instructions provided in the [wiki](https://github.com/tasostefas/opendr_internal/wiki).
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Please follow the instructions provided in the [wiki](https://github.com/tasostefas/opendr_internal/wiki).
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## Acknowledgments

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