%global _empty_manifest_terminate_build 0 Name: python-flockai Version: 0.1.18 Release: 1 Summary: A machine learning webots extension License: MIT License URL: https://github.com/unic-ailab/flockai-working Source0: https://mirrors.nju.edu.cn/pypi/web/packages/4b/4d/c8bec9ac1bdb5ebf6b3b8fe7d71ce88ddd10c70cc0cf0c4996feb82d4d0c/flockai-0.1.18.tar.gz BuildArch: noarch %description # FlockAI - A Framework for Rapidly Testing ML-Driven Drone Applications FlockAI, an open and modular by design framework supporting users with the rapid deployment and repeatable testing during the design phase of ML-driven drone applications. FlockAI can be used to design drone testbeds with "ready-to-go" drone templates, deploy ML models, configure on-board/remote inference, monitor and export drone resource utilization, network overhead and energy consumption to pinpoint performance inefficiencies and understand if various trade-offs can be exploited. Find out more about FlockAI by simply visiting our [website](https://unic-ailab.github.io/flockai/). ## Installing Webots Robotics Simulator FlockAI currently features integration endpoints with the Webots robotics simulator. Therefore, to use FlockAI, Webots must be previously installed on your computing environment. The installation of process of Webots is pretty straightforward for any OS environment (Linux, macOS, Windows) and instructions can be found [here](https://cyberbotics.com/doc/guide/installing-webots). Note: FlockAI requires a version of Webots above *R2021a* and we recommend using version **R2021a** where all offered tests and simulations worlds have been tested for. You can select versions from [here](https://github.com/cyberbotics/webots/releases) ## Installing FlockAI and Webots Endpoints Before we download dependencies and FlockAI, make sure that pip is up-to-date (>22.x) and that Cmake is [installed](https://cmake.org/install/). Integrating FlockAI with Webots requires the FlockAI controllers to be placed in the respected Python environment of Webots. We have made this process easy and requires only the following steps: ### Checking installed python version Upon launching Webots navigate to `Tools->Preferences` and identify the command that Webots uses to run its python controllers. ![webots python command](images/webots-python-command.png "Webots Python Command") Then, launch a terminal (or command prompt) and type the same command to identify your default python version. ![system python command](images/system-python-command.png "System Python Command") After the version is identified, the corresponding Webots controller directory needs to be noted down. ### Identifying Webots controller directory Navigate to the directory that Webots was installed and copy the corresponding controller path to your clipboard. ![webots controller directory](images/webots-controller-directory.PNG "Webots Controller Directory") ![copy path](copy-path.png "Copy Path") Once the controller path is copied, flockai should be installed in to that directory ### Installing FlockAI to the Webots controller directory Run the following command and make sure webots is installed in the destination directory `pip install --no-cache-dir --upgrade --target="your/webots/controller/directory" flockai` ![install flockai](images/install-flockai.PNG "Installing flockai") ## Download FlockAI Sample Worlds and Tests from Git Repo ### Clone the FlockAI repo on your system `git clone https://github.com/unic-ailab/flockai-working.git` ### Install requirements Navigate to the installed folder and execute the following command to install python requirements `pip install -r requirements.txt` ### Open one of the sample worlds located in the simulation directory In Webots, navigate to `File->Open World` and load one of the sample worlds our team has developed ![open world file](images/world-files.png "Open sample world file") #### Load sample controllers on your robots Check the relevant documentation on each controller to make the appropriate changes on your world's objects ![sample controllers](images/sample-controllers.PNG "Sample controllers") ## Give FlockAI a Go and Have Fun! 1. Keyboard-Based Navigation 2. Autopilot Navigation 3. ML sensor value prediction with linear regression 4. Face detection with deep learning 5. Crowd detection 6. and more! ![teaser](images/teaser.png "flockai teaser") %package -n python3-flockai Summary: A machine learning webots extension Provides: python-flockai BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-flockai # FlockAI - A Framework for Rapidly Testing ML-Driven Drone Applications FlockAI, an open and modular by design framework supporting users with the rapid deployment and repeatable testing during the design phase of ML-driven drone applications. FlockAI can be used to design drone testbeds with "ready-to-go" drone templates, deploy ML models, configure on-board/remote inference, monitor and export drone resource utilization, network overhead and energy consumption to pinpoint performance inefficiencies and understand if various trade-offs can be exploited. Find out more about FlockAI by simply visiting our [website](https://unic-ailab.github.io/flockai/). ## Installing Webots Robotics Simulator FlockAI currently features integration endpoints with the Webots robotics simulator. Therefore, to use FlockAI, Webots must be previously installed on your computing environment. The installation of process of Webots is pretty straightforward for any OS environment (Linux, macOS, Windows) and instructions can be found [here](https://cyberbotics.com/doc/guide/installing-webots). Note: FlockAI requires a version of Webots above *R2021a* and we recommend using version **R2021a** where all offered tests and simulations worlds have been tested for. You can select versions from [here](https://github.com/cyberbotics/webots/releases) ## Installing FlockAI and Webots Endpoints Before we download dependencies and FlockAI, make sure that pip is up-to-date (>22.x) and that Cmake is [installed](https://cmake.org/install/). Integrating FlockAI with Webots requires the FlockAI controllers to be placed in the respected Python environment of Webots. We have made this process easy and requires only the following steps: ### Checking installed python version Upon launching Webots navigate to `Tools->Preferences` and identify the command that Webots uses to run its python controllers. ![webots python command](images/webots-python-command.png "Webots Python Command") Then, launch a terminal (or command prompt) and type the same command to identify your default python version. ![system python command](images/system-python-command.png "System Python Command") After the version is identified, the corresponding Webots controller directory needs to be noted down. ### Identifying Webots controller directory Navigate to the directory that Webots was installed and copy the corresponding controller path to your clipboard. ![webots controller directory](images/webots-controller-directory.PNG "Webots Controller Directory") ![copy path](copy-path.png "Copy Path") Once the controller path is copied, flockai should be installed in to that directory ### Installing FlockAI to the Webots controller directory Run the following command and make sure webots is installed in the destination directory `pip install --no-cache-dir --upgrade --target="your/webots/controller/directory" flockai` ![install flockai](images/install-flockai.PNG "Installing flockai") ## Download FlockAI Sample Worlds and Tests from Git Repo ### Clone the FlockAI repo on your system `git clone https://github.com/unic-ailab/flockai-working.git` ### Install requirements Navigate to the installed folder and execute the following command to install python requirements `pip install -r requirements.txt` ### Open one of the sample worlds located in the simulation directory In Webots, navigate to `File->Open World` and load one of the sample worlds our team has developed ![open world file](images/world-files.png "Open sample world file") #### Load sample controllers on your robots Check the relevant documentation on each controller to make the appropriate changes on your world's objects ![sample controllers](images/sample-controllers.PNG "Sample controllers") ## Give FlockAI a Go and Have Fun! 1. Keyboard-Based Navigation 2. Autopilot Navigation 3. ML sensor value prediction with linear regression 4. Face detection with deep learning 5. Crowd detection 6. and more! ![teaser](images/teaser.png "flockai teaser") %package help Summary: Development documents and examples for flockai Provides: python3-flockai-doc %description help # FlockAI - A Framework for Rapidly Testing ML-Driven Drone Applications FlockAI, an open and modular by design framework supporting users with the rapid deployment and repeatable testing during the design phase of ML-driven drone applications. FlockAI can be used to design drone testbeds with "ready-to-go" drone templates, deploy ML models, configure on-board/remote inference, monitor and export drone resource utilization, network overhead and energy consumption to pinpoint performance inefficiencies and understand if various trade-offs can be exploited. Find out more about FlockAI by simply visiting our [website](https://unic-ailab.github.io/flockai/). ## Installing Webots Robotics Simulator FlockAI currently features integration endpoints with the Webots robotics simulator. Therefore, to use FlockAI, Webots must be previously installed on your computing environment. The installation of process of Webots is pretty straightforward for any OS environment (Linux, macOS, Windows) and instructions can be found [here](https://cyberbotics.com/doc/guide/installing-webots). Note: FlockAI requires a version of Webots above *R2021a* and we recommend using version **R2021a** where all offered tests and simulations worlds have been tested for. You can select versions from [here](https://github.com/cyberbotics/webots/releases) ## Installing FlockAI and Webots Endpoints Before we download dependencies and FlockAI, make sure that pip is up-to-date (>22.x) and that Cmake is [installed](https://cmake.org/install/). Integrating FlockAI with Webots requires the FlockAI controllers to be placed in the respected Python environment of Webots. We have made this process easy and requires only the following steps: ### Checking installed python version Upon launching Webots navigate to `Tools->Preferences` and identify the command that Webots uses to run its python controllers. ![webots python command](images/webots-python-command.png "Webots Python Command") Then, launch a terminal (or command prompt) and type the same command to identify your default python version. ![system python command](images/system-python-command.png "System Python Command") After the version is identified, the corresponding Webots controller directory needs to be noted down. ### Identifying Webots controller directory Navigate to the directory that Webots was installed and copy the corresponding controller path to your clipboard. ![webots controller directory](images/webots-controller-directory.PNG "Webots Controller Directory") ![copy path](copy-path.png "Copy Path") Once the controller path is copied, flockai should be installed in to that directory ### Installing FlockAI to the Webots controller directory Run the following command and make sure webots is installed in the destination directory `pip install --no-cache-dir --upgrade --target="your/webots/controller/directory" flockai` ![install flockai](images/install-flockai.PNG "Installing flockai") ## Download FlockAI Sample Worlds and Tests from Git Repo ### Clone the FlockAI repo on your system `git clone https://github.com/unic-ailab/flockai-working.git` ### Install requirements Navigate to the installed folder and execute the following command to install python requirements `pip install -r requirements.txt` ### Open one of the sample worlds located in the simulation directory In Webots, navigate to `File->Open World` and load one of the sample worlds our team has developed ![open world file](images/world-files.png "Open sample world file") #### Load sample controllers on your robots Check the relevant documentation on each controller to make the appropriate changes on your world's objects ![sample controllers](images/sample-controllers.PNG "Sample controllers") ## Give FlockAI a Go and Have Fun! 1. Keyboard-Based Navigation 2. Autopilot Navigation 3. ML sensor value prediction with linear regression 4. Face detection with deep learning 5. Crowd detection 6. and more! ![teaser](images/teaser.png "flockai teaser") %prep %autosetup -n flockai-0.1.18 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-flockai -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Wed Apr 12 2023 Python_Bot - 0.1.18-1 - Package Spec generated