Merge pull request #4 from DavidNorthup/dev

Dev

README.md

@@ -20,3 +20,17 @@ This file is meant to be run with an image captured from the webcam you are atte
 
 ## Mask Viewer
 The current implementation of the software uses opencv to select ranges of pixels defined by HSV value bounds in "Camera.h" for each of the colors on the cube. Opencv iterates through the image once for each color and generates a binary matrix of pixels with value 0 everywhere any given pixel is outside of the bounds for the speicifed color. Then it uses the sampling centers to count the number of pixels in range inside each circle defined by the center and a radius that match each color. The software then counts the number of matches for each color and whichever is highest is determined as the color for that point. This utility allows you to see the masks for a given sample image, and then reveals what it would conclude given the current bounds. Example usage is: ./training-mask.exe [image_file] [sampling locations].
+
+
+# Installation Details:
+1.) The first step is to install opencv, I used [this page](https://docs.opencv.org/master/d7/d9f/tutorial_linux_install.html).
+
+2.) Install SFML, I used my package manager to install using: apt-get install libsfml-dev.
+
+3.) Clone this repository and the kociemba repository, and make the target within 'ckociemba'.
+
+4.) Place the executable compiled in hte step prior into the application directory.
+
+5.) Compile all of the executables within the application directory.
+
+6.) Install the arduino software on the boards, with the sketch and libraries included.

application/Camera.cpp

@@ -161,17 +161,27 @@ std::vector<int> CSRImageProcessing::highlightMat(cv::Mat& image, std::vector<cv
     return data;
 }
 
-
+/*
+This function saves the opencv Mat object into an image specified by the variable path
+*/
 void CSRImageProcessing::saveImageToFile(std::string path, cv::Mat& image) {
     cv::imwrite(path, image);
     std::cout << "Saved image to file." << std::endl;
 }
 
+/*
+This helper function is used by the color reccomendation function. It is used to 
+determine if the point P is geometrically within the circle given by center and radius.
+*/
 bool CSRImageProcessing::pointInCircle(cv::Point p, cv::Point center, int radius) {
     int dx = p.x - center.x, dy = p.y - center.y;
     return std::sqrt(dx*dx + dy*dy) <= radius;
 }
 
+/*
+This function gives a recommendation for the cube facelet color by examining each of the color 
+masks. We sample in a circle with center (x,y) with radius rad.
+*/
 int CSRImageProcessing::getReccomendation(int x, int y, int rad, cv::Mat masks[]) {
     int maxCount = 0, maxIndex = 0;
     for (int i = 0; i < 6; i++) {

application/Camera.h

@@ -6,17 +6,17 @@
 #include <fstream>
 #include <vector>
 
-#define RADIUS 7
+#define RADIUS 8
 
 #define DATA_ORDER {"BLUE", "GREEN", "ORANGE", "RED", "WHITE", "YELLOW"}
 #define COLOR_ORDER {cv::Scalar(255,0,0), cv::Scalar(26,112,0), cv::Scalar(0, 130, 255), cv::Scalar(0,0,255), cv::Scalar(255,255,255), cv::Scalar(0,255,255)}
 #define SFML_COLOR_ORDER {sf::Color(0, 0, 255), sf::Color(0, 112,26), sf::Color(255, 130,0), sf::Color(255, 0, 0), sf::Color(255,255,255), sf::Color(255,255,0)} 
 
-#define BLUE_LOW    cv::Scalar(100, 50, 20)
+#define BLUE_LOW    cv::Scalar(95, 50, 20)
 #define BLUE_HIGH   cv::Scalar(140, 250, 250)
 
-#define GREEN_LOW   cv::Scalar(40, 30, 0)
-#define GREEN_HIGH  cv::Scalar(95, 255, 255)
+#define GREEN_LOW   cv::Scalar(40, 30, 20)
+#define GREEN_HIGH  cv::Scalar(85, 255, 255)
 
 #define ORANGE_LOW  cv::Scalar(15, 40, 40)
 #define ORANGE_HIGH cv::Scalar(23, 255, 255)
@@ -29,7 +29,7 @@
 #define RED_HIGH_2  cv::Scalar(255, 200, 200)
 
 #define WHITE_LOW   cv::Scalar(0, 0, 60)
-#define WHITE_HIGH  cv::Scalar(255, 40, 255)
+#define WHITE_HIGH  cv::Scalar(255, 30, 255)
 
 #define YELLOW_LOW cv::Scalar(23, 40, 20)
 #define YELLOW_HIGH  cv::Scalar(45, 255, 255)

application/Driver.cpp

@@ -266,6 +266,20 @@ int main(int argc, char *argv[]) {
                     if (event.key.code == sf::Keyboard::B) {
                         robot.performMove("B");
                     }
+
+                    if (event.key.code == sf::Keyboard::V) {
+                        int counts[] = {0,0,0,0,0,0};
+                        for (int i = 0; i < 54; i++) {
+                            counts[data[i]]++;
+                        }
+
+                        bool valid = true;
+                        for (int i = 0; i < 6 && valid; i++) {
+                            valid = counts[i] == 9;
+                        }
+
+                        std::cout << "Valid: " << valid << std::endl;
+                    }
                 } else if (alt_held) {
                     if (event.key.code == sf::Keyboard::R) {
                         robot.performMove("R'");

application/DriverSampling.cpp

@@ -1,11 +1,13 @@
 #include <SFML/Graphics.hpp>
-#include "Camera.h"
 #include <iostream>
 #include <fstream>
 
+#include "Camera.h"
+
+
 int main (int argc, char* argv[]) {
     if (argc < 3) {
-        std::cout << "Not enough args, example use: " << argv[0] << " [sample image file]   [facelet name (ex: B9)]" << std::endl; 
+        std::cout << "Not enough args, example use: " << argv[0] << " [sample image file]   [sampling center output file]" << std::endl; 
         return 1;
     }
     sf::Image image; 

application/Makefile

@@ -6,20 +6,19 @@ OBJECTS=$(SOURCES:.cpp=.o)
 EXECUTABLE=csr.exe
 
 
-all: $(EXECUTABLE)
+all: $(EXECUTABLE) sampling-config.exe training-mask.exe
 
-$(EXECUTABLE): $(OBJECTS) *.h
+$(EXECUTABLE): $(OBJECTS) 
 	$(CC) $(OBJECTS) -o $@  $(LDFLAGS)
 
-.cpp.o: $< *.h
-	$(CC) $(CFLAGS) $< -o $@ $(LDFLAGS)
+.cpp.o: $<
+	$(CC) $(CFLAGS) $< -c $(LDFLAGS)
 
 clean:
 	rm *.o *.exe
 
-
 sampling-config.exe: DriverSampling.cpp
 	$(CC) DriverSampling.cpp -o sampling-config.exe $(LDFLAGS)
 
-training-mask.exe: TrainingTestMask.cpp
+training-mask.exe: TrainingTestMask.cpp Camera.o
 		$(CC) TrainingTestMask.cpp -o training-mask.exe $(LDFLAGS)

application/TrainingTestMask.cpp

@@ -79,6 +79,7 @@ int main (int argc, char* argv[]) {
     cv::inRange(hsv, ORANGE_LOW_2 , ORANGE_HIGH_2, orange_mask_2);
     cv::inRange(hsv, YELLOW_LOW , YELLOW_HIGH, yellow_mask);
     orange_mask = orange_mask | orange_mask_2;
+    red_mask = red_mask | red_mask_2;
 
     Mat masks[] = {blue_mask, green_mask, orange_mask, red_mask, white_mask, yellow_mask};
     Scalar colors[] = COLOR_ORDER;

application/options.opt

@@ -3,10 +3,10 @@ Camera_brightness_frd 95
 Camera_brightness_flu 100
 Camera_brightness_bru 90
 Camera_contrast_bld 25
-Camera_contrast_frd 25
+Camera_contrast_frd 30
 Camera_contrast_flu 30
-Camera_contrast_bru 20
+Camera_contrast_bru 25
 Camera_saturation_bld 30
 Camera_saturation_frd 30
 Camera_saturation_flu 30
-Camera_saturation_bru 20
+Camera_saturation_bru 30

application/training/sampling_locations_bld.dat

@@ -4,12 +4,12 @@
 142 55 L8
 152 27 L9
 40 127 B3
-81 127 B6
-128 129 B9
+76 122 B6
+128 139 B9
 143 158 B8
 155 184 B7
 158 103 D7
 171 71 D4
 180 42 D1
 172 139 D8
-181 166 D9
+176 171 D9

application/training/sampling_locations_bru.dat

@@ -1,7 +1,7 @@
-141 199 U1
+141 202 U1
 133 167 U2
 122 129 U3
-134 101 U6
+133 105 U6
 144 78 U9
 92 149 B1
 104 186 B2

application/training/sampling_locations_frd.dat

@@ -11,5 +11,5 @@
 161 185 D1
 154 158 D2
 144 124 D3
-155 91 D6
+155 98 D6
 165 63 D9