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|
%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.aliyun.com/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
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.8.6-1
- Package Spec generated
|
