c8t6跟k210实现串口通信的代码,用标准库函数实现,并解释每一行代码所代表的意思
该回答引用GPT:
import serial
# 打开串口
ser = serial.Serial("/dev/ttyUSB0", 115200)
# 发送数据
ser.write(b'hello world!')
# 读取数据
data = ser.read(10)
# 关闭串口
ser.close()
上面的代码实现了c8t6跟k210的串口通信,首先使用serial模块打开串口,指定串口设备号和波特率;然后使用write函数发送数据,使用read函数读取数据;最后使用close函数关闭串口。
如还有疑问,可留言帮助解决。
[root@ton home]#git clone https://github.com/kendryte/kendryte-standalone-sdk.git #clone kendryte SDK
[root@ton home]#cp -r face_detect/ /home/kendryte-standalone-sdk/src/ #拷贝项目到src目录下
[root@ton home]#cd kendryte-standalone-sdk/src/face_detect/
[root@ton face_detect]#mkdir build && cd build/
[root@ton build]#cmake .. -DPROJ=face_detect #这里会报错
CMake Error: The source directory "/home/kendryte-standalone-sdk/src/face_detect" does not appear to contain CMakeLists.txt.
Specify --help for usage, or press the help button on the CMake GUI.
[root@ton build]#cmake ../../../ -DPROJ=face_detect #定位到SDK目录
PROJ = face_detect
-- Check for RISCV toolchain ...
-- Using /opt/kendryte-toolchain/bin RISCV toolchain
-- The C compiler identification is GNU 8.2.0
...
Makefile created.
-- Configuring done
-- Generating done
-- Build files have been written to: /home/kendryte-standalone-sdk/src/face_detect/build
[root@ton build]#make #编译
Scanning dependencies of target nncase
[ 2%] Building CXX object lib/nncase/CMakeFiles/nncase.dir/nncase.cpp.obj
[ 4%] Building CXX object lib/nncase/CMakeFiles/nncase.dir/runtime/cpu/cpu_ops.cpp.obj
...
[ 98%] Building C object CMakeFiles/face_detect.dir/src/face_detect/w25qxx.c.obj
[100%] Linking C executable face_detect
Generating .bin file ...
[100%] Built target face_detect
[root@ton build]#
[root@ton build]#ls #make 后生成.bin文件
CMakeCache.txt CMakeFiles cmake_install.cmake face_detect face_detect.bin lib Makefile to
#下面进行烧写
[root@ton k210-face-detect]#zip -d face_detect.kfpkg face_detect.bin #删除kfpkg包里的指定文件
deleting: face_detect.bin
[root@ton k210-face-detect]#zip -m face_detect.kfpkg face_detect.bin #添加.bin文件,或者同样可以添加kmodel文件
adding: face_detect.bin (deflated 41%)
[root@ton k210-face-detect]#python3 kflash.py -b 1500000 face_detect.kfpkg #烧写程序
可以写成脚本来完成上述步骤