I’m trying to translate a C++ Code which is used for Soil Moisture Sensor and Raindrop Sensor to a MATLAB Code. I was hoping to convert the C++ Code to a MATLAB Code through faster means since I have no knowledge in C++ Coding. Following is the code.

const int capteur_D = 4;
const int capteur_A = A0;

int val_analogique;

int soilMoistureValue = 0;
int soilmoisturepercent=0;

void setup() {
pinMode(capteur_D, INPUT);
pinMode(capteur_A, INPUT);
Serial.begin(9600); // open serial port, set the baud rate to 9600 bps
}

void loop() {

soilMoistureValue = analogRead(A0); //put Sensor insert into soil
Serial.println(soilMoistureValue);
delay(250);

if(digitalRead(capteur_D) == LOW)
{
Serial.println("Digital value : wet");
delay(10);
}
else
{
Serial.println("Digital value : dry");
delay(10);
}
val_analogique=analogRead(capteur_A);
Serial.print("Analog value : ");
Serial.println(val_analogique);
Serial.println("");
delay(1000);

}I’m trying to translate a C++ Code which is used for Soil Moisture Sensor and Raindrop Sensor to a MATLAB Code. I was hoping to convert the C++ Code to a MATLAB Code through faster means since I have no knowledge in C++ Coding. Following is the code.

const int capteur_D = 4;
const int capteur_A = A0;

int val_analogique;

int soilMoistureValue = 0;
int soilmoisturepercent=0;

void setup() {
pinMode(capteur_D, INPUT);
pinMode(capteur_A, INPUT);
Serial.begin(9600); // open serial port, set the baud rate to 9600 bps
}

void loop() {

soilMoistureValue = analogRead(A0); //put Sensor insert into soil
Serial.println(soilMoistureValue);
delay(250);

if(digitalRead(capteur_D) == LOW)
{
Serial.println("Digital value : wet");
delay(10);
}
else
{
Serial.println("Digital value : dry");
delay(10);
}
val_analogique=analogRead(capteur_A);
Serial.print("Analog value : ");
Serial.println(val_analogique);
Serial.println("");
delay(1000);

} I’m trying to translate a C++ Code which is used for Soil Moisture Sensor and Raindrop Sensor to a MATLAB Code. I was hoping to convert the C++ Code to a MATLAB Code through faster means since I have no knowledge in C++ Coding. Following is the code.

const int capteur_D = 4;
const int capteur_A = A0;

int val_analogique;

int soilMoistureValue = 0;
int soilmoisturepercent=0;

void setup() {
pinMode(capteur_D, INPUT);
pinMode(capteur_A, INPUT);
Serial.begin(9600); // open serial port, set the baud rate to 9600 bps
}

void loop() {

soilMoistureValue = analogRead(A0); //put Sensor insert into soil
Serial.println(soilMoistureValue);
delay(250);

if(digitalRead(capteur_D) == LOW)
{
Serial.println("Digital value : wet");
delay(10);
}
else
{
Serial.println("Digital value : dry");
delay(10);
}
val_analogique=analogRead(capteur_A);
Serial.print("Analog value : ");
Serial.println(val_analogique);
Serial.println("");
delay(1000);

} c++, c++ to matlab MATLAB Answers — New Questions

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I’m trying to create a Simulink model that has an input value that I want to reduce down to zero in a specific time. It must decrease in linear decrements with a delay after each decrement. The initial input value can also be different, but must reduce down to zero in the same time no matter the starting value.
I have tried using a feedback loop to subtract the original value * the time step, but this just results in the output value decreasing to zero immediately.
Are there any specific blocks for this kind fo linear reduction, or is a more complex block system required?
Thanks for the helpI’m trying to create a Simulink model that has an input value that I want to reduce down to zero in a specific time. It must decrease in linear decrements with a delay after each decrement. The initial input value can also be different, but must reduce down to zero in the same time no matter the starting value.
I have tried using a feedback loop to subtract the original value * the time step, but this just results in the output value decreasing to zero immediately.
Are there any specific blocks for this kind fo linear reduction, or is a more complex block system required?
Thanks for the help I’m trying to create a Simulink model that has an input value that I want to reduce down to zero in a specific time. It must decrease in linear decrements with a delay after each decrement. The initial input value can also be different, but must reduce down to zero in the same time no matter the starting value.
I have tried using a feedback loop to subtract the original value * the time step, but this just results in the output value decreasing to zero immediately.
Are there any specific blocks for this kind fo linear reduction, or is a more complex block system required?
Thanks for the help simulink, feedback loop MATLAB Answers — New Questions

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Hello everyone. I am trying to train the YOLOX net for cell detection in brightfield. My original images are 2048×2048. I read on matworks that yolox, being anchor-free, can be trained on tiled images and the inference can be done on full-size images. So what I did was tiliing my images in 4 blocks, 1024×1024 each, then size down everything to 512×512 pixels and do the training. Doing the inference on full-size images gives me 0 precision, as well as scaling down the test set to 1024×1024 pixels, which makes the size of the cells I want to detect the same size as they would be in the preprocessed training set. Is there something I am not grasping due to my scarce experience? thank you to whoever will suggest something. ThanksHello everyone. I am trying to train the YOLOX net for cell detection in brightfield. My original images are 2048×2048. I read on matworks that yolox, being anchor-free, can be trained on tiled images and the inference can be done on full-size images. So what I did was tiliing my images in 4 blocks, 1024×1024 each, then size down everything to 512×512 pixels and do the training. Doing the inference on full-size images gives me 0 precision, as well as scaling down the test set to 1024×1024 pixels, which makes the size of the cells I want to detect the same size as they would be in the preprocessed training set. Is there something I am not grasping due to my scarce experience? thank you to whoever will suggest something. Thanks Hello everyone. I am trying to train the YOLOX net for cell detection in brightfield. My original images are 2048×2048. I read on matworks that yolox, being anchor-free, can be trained on tiled images and the inference can be done on full-size images. So what I did was tiliing my images in 4 blocks, 1024×1024 each, then size down everything to 512×512 pixels and do the training. Doing the inference on full-size images gives me 0 precision, as well as scaling down the test set to 1024×1024 pixels, which makes the size of the cells I want to detect the same size as they would be in the preprocessed training set. Is there something I am not grasping due to my scarce experience? thank you to whoever will suggest something. Thanks yolo, deep learning, detection, machine learning, image processing, computer vision MATLAB Answers — New Questions

​

Hello,
I am facing something rather curious, I am noticing a behaviour different on Matlab function findobj in Windows(10/11) or Unix ( ubuntu 22).
My issue roots to the search of figures by name, in windows I use the function like this
figHandle = findobj(groot,’Name’,figName);
so providing the figName finds the figure as expected, but running same command under Matlab unix version it returns empty figHandle. I use the Matlab unix version in my CI environment where I found the issue.
Does it rely on lower OS functions that do not behave the same? Can I overcome this issue?

Thanks in advance,

RegardsHello,
I am facing something rather curious, I am noticing a behaviour different on Matlab function findobj in Windows(10/11) or Unix ( ubuntu 22).
My issue roots to the search of figures by name, in windows I use the function like this
figHandle = findobj(groot,’Name’,figName);
so providing the figName finds the figure as expected, but running same command under Matlab unix version it returns empty figHandle. I use the Matlab unix version in my CI environment where I found the issue.
Does it rely on lower OS functions that do not behave the same? Can I overcome this issue?

Thanks in advance,

Regards Hello,
I am facing something rather curious, I am noticing a behaviour different on Matlab function findobj in Windows(10/11) or Unix ( ubuntu 22).
My issue roots to the search of figures by name, in windows I use the function like this
figHandle = findobj(groot,’Name’,figName);
so providing the figName finds the figure as expected, but running same command under Matlab unix version it returns empty figHandle. I use the Matlab unix version in my CI environment where I found the issue.
Does it rely on lower OS functions that do not behave the same? Can I overcome this issue?

Thanks in advance,

Regards findobj MATLAB Answers — New Questions

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