Luiz doleron | Luiz d'Oleron doleron

## config_cmake_eclipse_git_project.sh
#!/bin/bash

###################################################################################################
# Bash script to import CMake project from Github and create local Eclipse CDT compatible project #
#                                                                                                 #
# The CMake Eclipse CDT strategy was taken from here: https://stackoverflow.com/a/9663686/3055724 #
# After run this script you need to import the project in eclipse:                                #
# File->Import->C/C++->Existing code as Makefile Project->Next                                    #
# Tested in Eclise Oxygen and Luna                                                                #
###################################################################################################

## forward.txt
// inverse kinematics
 // helper functions, calculates angle theta1 (for YZ-pane)
 int delta_calcAngleYZ(float x0, float y0, float z0, float &theta) {
     float y1 = -0.5 * 0.57735 * f; // f/2 * tg 30
     y0 -= 0.5 * 0.57735    * e;    // shift center to edge
     // z = a + b*y
     float a = (x0*x0 + y0*y0 + z0*z0 +rf*rf - re*re - y1*y1)/(2*z0);
     float b = (y1-y0)/z0;
     // discriminant
     float d = -(a+b*y1)*(a+b*y1)+rf*(b*b*rf+rf);

## wifi_relay_module.ino
void setup() {
  Serial.begin(9600);
}

void loop() {
  byte close[] = {0xA0, 0x01, 0x01, 0xA2};
  Serial.write(close, sizeof(close));
  delay(2000);

  byte open[] = {0xA0, 0x01, 0x00, 0xA1};

## sync your fork with original repo.md

      
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                doleron
                / sync your fork with original repo.md
            
            
              Last active
              June 18, 2020 03:01
            
              
                commands to synchronize your fork with original repo
              
          
    how to synchronize your fork with the original github repo

considering:

https://github.com/whoever/whatever.git is the address of original repo
https://github.com/youraccount/whatever.git is the address of fork repo

The first option is to merge your fork with the original repo

clone your fork if you haven't cloned already

  
## medium_yolov5_frame_input.py
def format_yolov5(source):

    # put the image in square big enough
    col, row, _ = source.shape
    _max = max(col, row)
    resized = np.zeros((_max, _max, 3), np.uint8)
    resized[0:col, 0:row] = source

    # resize to 640x640, normalize to [0,1[ and swap Red and Blue channels
    result = cv2.dnn.blobFromImage(resized, 1/255.0, (640, 640), swapRB=True)

## medium_yolov5_importing_model.cpp
#include <opencv2/opencv.hpp>

int main(int, char **)
{
    auto net = cv::dnn::readNet("yolov5s.onnx");

    return 0;
}

## medium_yolov5_importing_model.py
import cv2

net = cv2.dnn.readNet('yolov5s.onnx')

## medium_yolov5_calling_model.cpp
std::vector<cv::Mat> predictions;
net.forward(predictions, net.getUnconnectedOutLayersNames());
const cv::Mat &output = predictions[0];

## medium_yolov5_calling_model.py
predictions = net.forward()
output = predictions[0]

## medium_yolov5_unwrapping_data.py
def unwrap_detection(input_image, output_data):
    class_ids = []
    confidences = []
    boxes = []

    rows = output_data.shape[0]

    image_width, image_height, _ = input_image.shape

    x_factor = image_width / 640
	#!/bin/bash

	###################################################################################################
	# Bash script to import CMake project from Github and create local Eclipse CDT compatible project #
	# #
	# The CMake Eclipse CDT strategy was taken from here: https://stackoverflow.com/a/9663686/3055724 #
	# After run this script you need to import the project in eclipse: #
	# File->Import->C/C++->Existing code as Makefile Project->Next #
	# Tested in Eclise Oxygen and Luna #
	###################################################################################################
	// inverse kinematics
	// helper functions, calculates angle theta1 (for YZ-pane)
	int delta_calcAngleYZ(float x0, float y0, float z0, float &theta) {
	float y1 = -0.5 * 0.57735 * f; // f/2 * tg 30
	y0 -= 0.5 * 0.57735 * e; // shift center to edge
	// z = a + b*y
	float a = (x0x0 + y0y0 + z0z0 +rfrf - rere - y1y1)/(2*z0);
	float b = (y1-y0)/z0;
	// discriminant
	float d = -(a+by1)(a+by1)+rf(bbrf+rf);
	void setup() {
	Serial.begin(9600);
	}

	void loop() {
	byte close[] = {0xA0, 0x01, 0x01, 0xA2};
	Serial.write(close, sizeof(close));
	delay(2000);

	byte open[] = {0xA0, 0x01, 0x00, 0xA1};
	def format_yolov5(source):

	# put the image in square big enough
	col, row, _ = source.shape
	_max = max(col, row)
	resized = np.zeros((_max, _max, 3), np.uint8)
	resized[0:col, 0:row] = source

	# resize to 640x640, normalize to [0,1[ and swap Red and Blue channels
	result = cv2.dnn.blobFromImage(resized, 1/255.0, (640, 640), swapRB=True)
	#include <opencv2/opencv.hpp>

	int main(int, char **)
	{
	auto net = cv::dnn::readNet("yolov5s.onnx");

	return 0;
	}
	std::vector<cv::Mat> predictions;
	net.forward(predictions, net.getUnconnectedOutLayersNames());
	const cv::Mat &output = predictions[0];
	def unwrap_detection(input_image, output_data):
	class_ids = []
	confidences = []
	boxes = []

	rows = output_data.shape[0]

	image_width, image_height, _ = input_image.shape

	x_factor = image_width / 640