%global _empty_manifest_terminate_build 0 Name: python-control-scnu Version: 0.8.6 Release: 1 Summary: The code package for HuaGuang AI Education License: MIT License URL: https://github.com/pypa/sampleproject Source0: https://mirrors.nju.edu.cn/pypi/web/packages/be/2e/332cdac2c8242f5ec48c00f478f896cdf10fbbf250dd6a67dfdec069bc10/control_scnu-0.8.6.tar.gz BuildArch: noarch Requires: python3-baidu-aip Requires: python3-certifi Requires: python3-charset-normalizer Requires: python3-future Requires: python3-idna Requires: python3-iso8601 Requires: python3-joblib Requires: python3-numpy Requires: python3-opencv-contrib-python Requires: python3-opencv-python Requires: python3-Pillow Requires: python3-pygame Requires: python3-pyzbar Requires: python3-redis Requires: python3-requests Requires: python3-scikit-learn Requires: python3-scipy Requires: python3-threadpoolctl Requires: python3-urllib3 Requires: python3-pandas Requires: python3-cvzone Requires: python3-imutils Requires: python3-websocket Requires: python3-websocket-client Requires: python3-protobuf Requires: python3-pyttsx3 Requires: python3-wordcloud Requires: python3-jieba Requires: python3-py7zr Requires: python3-tqdm Requires: python3-browser-cookie3 %description English | [简体中文](README_cn.md) - [0.control_scnu](#0control_scnu) - [1.Install control](#1install-control) - [2.Each corresponding file description](#2each-corresponding-file-description) - [template](#template) - [_init_.py](#initpy) - [file_operation.py](#file_operationpy) - [gpio.py](#gpiopy) - [jiami.py](#jiamipy) - [machine_learning.py](#machine_learningpy) - [maths.py](#mathspy) - [requirements.txt](#requirementstxt) - [shijue (shijue0,shijue1,shijue2)](#shijue-shijue0shijue1shijue2) - [unique.py](#uniquepy) - [yuyin.py](#yuyinpy) # 0.control_scnu The library was developed for Huaguang AI Education Innovation Team [Case Department] Applicable to artificial intelligence education # 1.Install control ```python pip3 install control-scnu ``` # 2.Each corresponding file description ## template Where the various model files are saved ## _init_.py The init file The version information of the software, programming block and library is indicated in this file ## file_operation.py File manipulation related libraries ## gpio.py Car hardware related library The car forward routine (This item needs to run on the car): ``` from control import gpio import time m=gpio.Mecanum_wheel() m.uart_init() m.car_go(200) time.sleep(2) m.car_stop() ``` ## jiami.py A library for encrypted files ## machine_learning.py Library for machine learning Iris machine learning routine: ``` from control import machine_learning as ml datasets=ml.DatasetsNew(ml.data_name["鸢尾花"]) model= ml.ModelNew(ml.model_name['神经网络']) model.train(datasets.x_train, datasets.y_train,dataName=datasets.data_name) model.test(datasets.x_test,datasets.y_test) print(model.test_score,flush=True) model.predict(datasets.x_test) print(model.pred,flush=True) model.save(name='myFirstModel') model1=ml.ModelNew('myFirstModel.proto') model1.test(datasets.x_test,datasets.y_test) print(model.pred,flush=True) ``` ## maths.py Library related to basic mathematics ## requirements.txt Library dependent TXT file ## shijue (shijue0,shijue1,shijue2) Visual related libraries The camera obtains the image and binarizes the display routine: ``` from control import shijue1 a=shijue1.Img() a.camera(0) a.name_windows('img') while True: a.get_img() a.BGR2GRAY() a.GRAY2BIN() a.show_image('img') a.delay(1) ``` ## unique.py Put something special in it ## yuyin.py Speech correlation library Routines for speech recognition and retelling: ``` from control import yuyin s=yuyin.Yuyin(online=True) s.my_record(3,"speech") print(s.stt("speech"),flush=True) s.play_txt(s.stt("speech")) %package -n python3-control-scnu Summary: The code package for HuaGuang AI Education Provides: python-control-scnu BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-control-scnu English | [简体中文](README_cn.md) - [0.control_scnu](#0control_scnu) - [1.Install control](#1install-control) - [2.Each corresponding file description](#2each-corresponding-file-description) - [template](#template) - [_init_.py](#initpy) - [file_operation.py](#file_operationpy) - [gpio.py](#gpiopy) - [jiami.py](#jiamipy) - [machine_learning.py](#machine_learningpy) - [maths.py](#mathspy) - [requirements.txt](#requirementstxt) - [shijue (shijue0,shijue1,shijue2)](#shijue-shijue0shijue1shijue2) - [unique.py](#uniquepy) - [yuyin.py](#yuyinpy) # 0.control_scnu The library was developed for Huaguang AI Education Innovation Team [Case Department] Applicable to artificial intelligence education # 1.Install control ```python pip3 install control-scnu ``` # 2.Each corresponding file description ## template Where the various model files are saved ## _init_.py The init file The version information of the software, programming block and library is indicated in this file ## file_operation.py File manipulation related libraries ## gpio.py Car hardware related library The car forward routine (This item needs to run on the car): ``` from control import gpio import time m=gpio.Mecanum_wheel() m.uart_init() m.car_go(200) time.sleep(2) m.car_stop() ``` ## jiami.py A library for encrypted files ## machine_learning.py Library for machine learning Iris machine learning routine: ``` from control import machine_learning as ml datasets=ml.DatasetsNew(ml.data_name["鸢尾花"]) model= ml.ModelNew(ml.model_name['神经网络']) model.train(datasets.x_train, datasets.y_train,dataName=datasets.data_name) model.test(datasets.x_test,datasets.y_test) print(model.test_score,flush=True) model.predict(datasets.x_test) print(model.pred,flush=True) model.save(name='myFirstModel') model1=ml.ModelNew('myFirstModel.proto') model1.test(datasets.x_test,datasets.y_test) print(model.pred,flush=True) ``` ## maths.py Library related to basic mathematics ## requirements.txt Library dependent TXT file ## shijue (shijue0,shijue1,shijue2) Visual related libraries The camera obtains the image and binarizes the display routine: ``` from control import shijue1 a=shijue1.Img() a.camera(0) a.name_windows('img') while True: a.get_img() a.BGR2GRAY() a.GRAY2BIN() a.show_image('img') a.delay(1) ``` ## unique.py Put something special in it ## yuyin.py Speech correlation library Routines for speech recognition and retelling: ``` from control import yuyin s=yuyin.Yuyin(online=True) s.my_record(3,"speech") print(s.stt("speech"),flush=True) s.play_txt(s.stt("speech")) %package help Summary: Development documents and examples for control-scnu Provides: python3-control-scnu-doc %description help English | [简体中文](README_cn.md) - [0.control_scnu](#0control_scnu) - [1.Install control](#1install-control) - [2.Each corresponding file description](#2each-corresponding-file-description) - [template](#template) - [_init_.py](#initpy) - [file_operation.py](#file_operationpy) - [gpio.py](#gpiopy) - [jiami.py](#jiamipy) - [machine_learning.py](#machine_learningpy) - [maths.py](#mathspy) - [requirements.txt](#requirementstxt) - [shijue (shijue0,shijue1,shijue2)](#shijue-shijue0shijue1shijue2) - [unique.py](#uniquepy) - [yuyin.py](#yuyinpy) # 0.control_scnu The library was developed for Huaguang AI Education Innovation Team [Case Department] Applicable to artificial intelligence education # 1.Install control ```python pip3 install control-scnu ``` # 2.Each corresponding file description ## template Where the various model files are saved ## _init_.py The init file The version information of the software, programming block and library is indicated in this file ## file_operation.py File manipulation related libraries ## gpio.py Car hardware related library The car forward routine (This item needs to run on the car): ``` from control import gpio import time m=gpio.Mecanum_wheel() m.uart_init() m.car_go(200) time.sleep(2) m.car_stop() ``` ## jiami.py A library for encrypted files ## machine_learning.py Library for machine learning Iris machine learning routine: ``` from control import machine_learning as ml datasets=ml.DatasetsNew(ml.data_name["鸢尾花"]) model= ml.ModelNew(ml.model_name['神经网络']) model.train(datasets.x_train, datasets.y_train,dataName=datasets.data_name) model.test(datasets.x_test,datasets.y_test) print(model.test_score,flush=True) model.predict(datasets.x_test) print(model.pred,flush=True) model.save(name='myFirstModel') model1=ml.ModelNew('myFirstModel.proto') model1.test(datasets.x_test,datasets.y_test) print(model.pred,flush=True) ``` ## maths.py Library related to basic mathematics ## requirements.txt Library dependent TXT file ## shijue (shijue0,shijue1,shijue2) Visual related libraries The camera obtains the image and binarizes the display routine: ``` from control import shijue1 a=shijue1.Img() a.camera(0) a.name_windows('img') while True: a.get_img() a.BGR2GRAY() a.GRAY2BIN() a.show_image('img') a.delay(1) ``` ## unique.py Put something special in it ## yuyin.py Speech correlation library Routines for speech recognition and retelling: ``` from control import yuyin s=yuyin.Yuyin(online=True) s.my_record(3,"speech") print(s.stt("speech"),flush=True) s.play_txt(s.stt("speech")) %prep %autosetup -n control-scnu-0.8.6 %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-control-scnu -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Mon May 15 2023 Python_Bot - 0.8.6-1 - Package Spec generated