Merge branch 'Nehara' into 'master'

updated

See merge request !12

IT17075190/Data sets/PaintCoats/paint1.csv

+current,paint,coat
+red,red,1
+red,orange,1
+red,yellow,2
+red,green,1
+red,blue,1
+red,purple,2
+red,beige,3
+red,offwhite,3
+orange,orange,1
+orange,red,1
+orange,yellow,2
+orange,green,1
+orange,blue,1
+orange,purple,2
+orange,beige,3
+orange,offwhite,3
+yellow,yellow,1
+yellow,red,1
+yellow,orange,1
+yellow,green,1
+yellow,blue,1
+yellow,purple,1
+yellow,beige,2
+yellow,offwhite,2
+green,green,1
+green,red,1
+green,orange,2
+green,yellow,2
+green,blue,1
+green,purple,2
+green,beige,3
+green,offwhite,3
+blue,blue,1
+blue,red,1
+blue,orange,1
+blue,yellow,2
+blue,green,1
+blue,purple,2
+blue,beige,3
+blue,offwhite,3
+purple,purple,1
+purple,red,1
+purple,orange,2
+purple,yellow,2
+purple,green,1
+purple,blue,1
+purple,beige,3
+purple,offwhite,3
+beige,beige,1
+beige,red,1
+beige,orange,1
+beige,yellow,2
+beige,green,1
+beige,blue,1
+beige,purple,1
+beige,offwhite,2
+offwhite,offwhite,1
+offwhite,red,1
+offwhite,orange,1
+offwhite,yellow,2
+offwhite,green,1
+offwhite,blue,1
+offwhite,purple,1
+offwhite,beige,2

IT17075190/MachineLearning_PythonScript/Color Coats/Inputs/Current_color.txt

+purple
\ No newline at end of file

IT17075190/MachineLearning_PythonScript/Color Coats/Inputs/Pick_color.txt

+red
\ No newline at end of file

IT17075190/MachineLearning_PythonScript/Color Coats/Outputs/results.txt

+[1]
\ No newline at end of file

IT17075190/MachineLearning_PythonScript/Color Coats/paint.py

+# -*- coding: utf-8 -*-
+"""paint_coats.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1Z5k0mxozD6NAZ2sHFj2BlvIqZ8GE_COm
+"""
+
+# Commented out IPython magic to ensure Python compatibility.
+import numpy as np
+import matplotlib.pyplot as plt
+# %matplotlib inline
+import pandas as pd
+#to save model file
+import pickle
+#to load model file
+#from keras.models import load_model
+
+#define file paths
+csv_path = "D:\PaintVisualizer\Python\Color Coats Calculator\paint1.csv"
+input_captured_color_file_path = r'D:\PaintVisualizer\Python\Color Coats Calculator\Inputs\Current_color.txt'
+input_picked_color_file_path = r'D:\PaintVisualizer\Python\Color Coats Calculator\Inputs\Pick_color.txt'
+color_coat_output_file_path = r'D:\PaintVisualizer\Python\Color Coats Calculator\Outputs\results.txt'
+
+#load tarined model
+#modelDir=r'E:\My Project\Paint Visualizer\Python\Color Coats Calculator\Trained Model\finalized_model.h5'
+#modelTrained=load_model(modelDir)
+
+df = pd.read_csv(csv_path)
+df.head()
+
+#read captured and picked colors from input text files
+fileCapturedColor = open(input_captured_color_file_path, "r")
+capturedColor = fileCapturedColor.read()
+fileCapturedColor.close()
+#print(capturedColor)
+filePickedColor = open(input_picked_color_file_path, "r")
+pickedColor = filePickedColor.read()
+filePickedColor.close()
+#print(pickedColor)
+
+inputs = df.drop('coat', axis='columns')
+target = df['coat']
+#print("inputs " + str(inputs))
+#print("target " + str(target))
+
+from sklearn.preprocessing import LabelEncoder
+
+le_current = LabelEncoder()
+le_paint = LabelEncoder()
+
+inputs['current_n'] =le_current.fit_transform(inputs['current'])
+inputs['paint_n'] =le_current.fit_transform(inputs['paint'])
+#print("inputs['current_n'] " + str(inputs['current_n']))
+#print("inputs['paint_n'] " + str(inputs['paint_n']))
+
+inputs.head()
+
+inputs_n = inputs.drop(['current','paint'],axis = 'columns')
+#length = len(inputs_n)
+#print(inputs_n)
+#print(inputs_n.iloc[0]['current_n'])
+#print(inputs_n.iloc[7]['paint_n'])
+
+#assign label index for main 8 colors
+red = inputs_n.iloc[7]['current_n']
+orange = inputs_n.iloc[15]['current_n']
+yellow = inputs_n.iloc[23]['current_n']
+green = inputs_n.iloc[31]['current_n']
+blue = inputs_n.iloc[39]['current_n']
+purple = inputs_n.iloc[47]['current_n']
+beige = inputs_n.iloc[55]['current_n']
+offwhite = inputs_n.iloc[63]['current_n']
+
+def getColorIndex(color):
+    colorCode = 8
+    
+    if(color == "red"):
+        colorCode = red
+    elif(color == "orange"):
+        colorCode = orange
+    elif(color == "yellow"):
+        colorCode = yellow
+    elif(color == "green"):
+        colorCode = green
+    elif(color == "blue"):
+        colorCode = blue
+    elif(color == "purple"):
+        colorCode = purple
+    elif(color == "beige"):
+        colorCode = beige
+    elif(color == "offwhite"):
+        colorCode = offwhite
+    else:
+        colorCode = 8
+        
+    return colorCode
+
+capturedColorIndex = getColorIndex(capturedColor)
+pickedColorIndex = getColorIndex(pickedColor)
+
+from sklearn import tree
+
+model = tree.DecisionTreeClassifier()
+
+model.fit(inputs_n,target)
+
+#save model
+#filename = 'finalized_model.sav'
+#filename = 'finalized_model.h5'
+#pickle.dump(model, open(filename, 'wb'))
+
+#model.score(inputs_n,target)
+print(model.score(inputs_n,target))
+
+#model.predict([[27,27]])
+#print(model.predict([[6,7]]))
+colorCoats = model.predict([[capturedColorIndex,pickedColorIndex]])
+fileColorCoat = open(color_coat_output_file_path, "w+")
+fileColorCoat.write(str(colorCoats))
+fileColorCoat.close()
+print(colorCoats)
+
+#from sklearn.model_selection import train_test_split
+#x_train, x_test, y_train, y_test = train_test_split(inputs_n,target,test_size=0.2, random_state = 2656)
+#len(x_train)
+#len(x_test)
+
+#from sklearn import tree
+#model = tree.DecisionTreeClassifier()
+#model.fit(x_train,y_train)
+#model.score(x_test,y_test)
+

IT17075190/MachineLearning_PythonScript/Color Identify/Outputs/Result_color.txt

+#59453e
\ No newline at end of file

IT17075190/MachineLearning_PythonScript/Color Identify/color_detector.py

+import numpy as np
+import pandas as pd
+import cv2
+
+img_path = r'D:\PaintVisualizer\Python\Color Identify\Images\test.jpg'
+#img_path = "E:\My Project\Paint Visualizer\Color Identify\Images\color_image2.jpg"
+#img_path = "E:\My Project\Paint Visualizer\Color Identify\Images\color_image3.jpg"
+#img_path = r'E:\My Project\Paint Visualizer\Color Identify\Images\colorpic.jpg'
+#img_path = "E:\My Project\Paint Visualizer\Color Identify\Images\ic_logo.png"
+#img_path = 'E:\My Project\Paint Visualizer\Color Identify\Images\test.jpg'
+csv_path = "D:\PaintVisualizer\Python\Color Identify\Colors\colors.csv"
+color_output_file_path = "D:\PaintVisualizer\Python\Color Identify\Outputs\Result_color.txt"
+
+img = cv2.imread(img_path)
+
+index = ["color", "color_name", "hex", "R", "G", "B"]
+csv = pd.read_csv(csv_path, names=index, header=None)
+
+clicked = True
+r = g = b = xpos = ypos = 0
+
+def recognize_color(R,G,B):
+    minimum = 10000
+    for i in range(len(csv)):
+        d = abs(R- int(csv.loc[i,"R"])) + abs(G- int(csv.loc[i,"G"]))+ abs(B- int(csv.loc[i,"B"]))
+        if(d<=minimum):
+            minimum = d
+            cname = csv.loc[i,"color_name"]
+    return cname
+
+#b,g,r = img[0,0]
+#b = int(b)
+#g = int(g)
+#r = int(r)
+
+cv2.namedWindow('Color Recognition App')
+
+#print(cv2.getWindowImageRect(cv2.imshow("Color Recognition App",img)))
+
+while(1):
+    cv2.imshow("Color Recognition App",img)
+    if (clicked):
+        scale = str(cv2.getWindowImageRect("Color Recognition App"))
+        scale2 = scale.replace("(","")
+        scale3 = scale2.replace(")","")
+        slitScale = scale3.split(",")
+        xpos = int(int(slitScale[2].strip())/2)
+        ypos = int(int(slitScale[3].strip())/2)
+        #print(scale)
+        #print(xpos)
+        #print(ypos)
+
+        b,g,r = img[ypos,xpos]
+        b = int(b)
+        g = int(g)
+        r = int(r)
+        
+        #cv2.rectangle(image, startpoint, endpoint, color, thickness)-1 fills entire rectangle 
+        cv2.rectangle(img,(20,20), (750,60), (b,g,r), -1)
+        #Creating text string to display( Color name and RGB values )
+        text = recognize_color(r,g,b) + ' R='+ str(r) +  ' G='+ str(g) +  ' B='+ str(b)
+        #text_write = str(r) +  ',' + str(g) +  ',' + str(b)
+        #text_write = recognize_color(r,g,b) + '|'+ str(r) +  ','+ str(g) +  ','+ str(b)
+
+        #convert rgb to hex
+        text_write = '#{:02x}{:02x}{:02x}'.format(r,g,b)
+
+        f = open(color_output_file_path, "w+")
+        f.write(str(text_write))
+        f.close()
+        
+        #cv2.putText(img,text,start,font(0-7),fontScale,color,thickness,lineType )
+        cv2.putText(img, text,(50,50),2,0.8,(255,255,255),2,cv2.LINE_AA)
+        #For very light colours we will display text in black colour
+        if(r+g+b>=600):
+            cv2.putText(img, text,(50,50),2,0.8,(0,0,0),2,cv2.LINE_AA)
+            
+        clicked=False
+        break
+
+    #Break the loop when user hits 'esc' key    
+    #if cv2.waitKey(20) & 0xFF ==27:
+        #break
+    
+cv2.destroyAllWindows()
+

IT17075190/MachineLearning_PythonScript/Readme.txt

+There are two pythons scipts used. Those file names are 'paint' (inside the color coats folder)
+and 'color_detector' (color identify folder).
+
+In the 'paint' python script, it should give the file paths which is typed under the comment 
+of '#define file paths' 
+
+In the 'color_detector' pyhton script, change the file paths according to the locations of the files.
\ No newline at end of file

IT17075190/Readme.txt

-Wall paint
-implement on camera

IT17075190/Xampp/ColorIdentify/ColorFound.php

+<?php
+class ColorFound 
+{
+	public $baseColors = 
+	[
+		'ff0000' => 'red',
+		'ff7f00' => 'orange',
+		'ffff00' => 'yellow',
+		'00ff00' => 'green',
+		'0000ff' => 'blue',
+		'9400d3' => 'purple',
+		'f5f5dc' => 'beige',
+		'ffffff' => 'offwhite'
+	];
+
+	function __construct($baseColors = false) 
+	{
+		if ($baseColors && is_array($baseColors)) 
+		{
+			$this->baseColors = $baseColors;
+		}
+	}
+
+	/**
+	 * Convert A HEX Code to an array of RGB values
+	 * @param  string $color Hex Code of Color with or without "#"
+	 * @return array|boolean Array of RGB values
+	 */
+	public function hex2RGB($color) 
+	{
+		if ($color != "") 
+		{
+			$color = ltrim($color, '#');
+			list($r,$g,$b) = array_map('hexdec',str_split($color,2));
+	        return array
+	        (
+	        	'r' => $r,
+	        	'g' => $g,
+	        	'b'=>$b
+	        );
+		}
+
+		return false;
+	}
+
+	/**
+	 * Calculate distance between the 2 colors
+	 *
+	 * @param  array $color1 RGB values of Color 1
+	 * @param  array $color RGB values of Color 2
+	 * @return int Distance of the 2 RGB values
+	 */
+	public function dist2Colors($color1, $color2) 
+	{
+		if (is_array($color1) && is_array($color2)) 
+		{
+			$delta_r = $color1['r'] - $color2['r'];
+  			$delta_g = $color1['g'] - $color2['g'];
+  			$delta_b = $color1['b'] - $color2['b'];
+  			return $delta_r * $delta_r + $delta_g * $delta_g + $delta_b * $delta_b;
+		} 
+		else
+		{
+			return false;
+		}
+	}
+
+	/**
+	 * Get the color name from the pre-defined base colors
+	 *
+	 * @param  string $color1 Hex Code of Color 1
+	 * @param  array $baseColors Base Colors to check from
+	 * @return array|string Color name or False
+	 */
+	public function getName($color, $baseColors = false) 
+	{
+		$dist_arr = [];
+		$nearest = false;
+		if ($baseColors && is_array($baseColors)) 
+		{
+			$this->baseColors = $baseColors;
+		}
+
+		foreach ($this->baseColors as $k => $v) 
+		{
+			$dist = $this->dist2Colors($this->hex2RGB($color), $this->hex2RGB($k));
+			if ($nearest === false) 
+			{
+				$nearest = $dist;
+			} 
+			else 
+			{
+				if ($nearest > $dist) 
+				{
+					$nearest = $dist;
+				}
+			}
+
+			$dist_arr[$dist] = $v;
+		}
+
+		if (isset($dist_arr[$nearest])) 
+		{
+			return $dist_arr[$nearest];
+		} 
+		else
+		{
+			return false;
+		}
+	}
+}
+?>
\ No newline at end of file

IT17075190/Xampp/ColorIdentify/color_identify_service.php

+<?php
+//ini_set('display_errors',1);  
+//error_reporting(E_ALL);
+require_once('ColorFound.php');
+$colorFound = new ColorFound;
+
+$data = array();
+
+$imageData = "";
+$pickedColorHEX = "";
+$imageName = "";
+$capturedImageColorHEX = "";
+
+$savedImagePath = "D:/PaintVisualizer/Python/Color Identify/Images/";
+$pythonScriptPathForColorPick = "D:/PaintVisualizer/Python/Color Identify/color_detector.py";
+$pythonScriptPathForColorCoats = "D:/PaintVisualizer/Python/Color Coats Calculator/paint.py";
+$capturedColorHEXOutputFilePath = "D:/PaintVisualizer/Python/Color Identify/Outputs/Result_color.txt";
+$inputCapturedColorPath = "D:/PaintVisualizer/Python/Color Coats Calculator/Inputs/Current_color.txt";
+$inputPickedColorPath = "D:/PaintVisualizer/Python/Color Coats Calculator/Inputs/Pick_color.txt";
+$colorCoatOutputPath = "D:/PaintVisualizer/Python/Color Coats Calculator/Outputs/results.txt";
+
+if(isset($_POST['image_data']) && isset($_POST['pick_color_hex']))
+{
+	$imageData = $_POST['image_data'];
+	$pickedColorHEX = $_POST['pick_color_hex'];
+
+	//write picked color hex value
+	$pickColorFile = fopen($inputPickedColorPath, "w");
+	fwrite($pickColorFile, $colorFound->getName($pickedColorHEX));
+	fclose($pickColorFile);
+
+	$imageName = "test";//$_POST['image_name'];
+
+	$ImagePathPC = $savedImagePath . $imageName . ".jpg";
+
+	//save image to pc folder
+	file_put_contents($ImagePathPC, base64_decode($imageData));
+	sleep(4);
+
+	//run color idendify python script
+	$command = escapeshellcmd($pythonScriptPathForColorPick);
+	$output = shell_exec($command);	
+	sleep(4);
+
+	//read captured image color output
+	$resultColor = fopen($capturedColorHEXOutputFilePath, "r");
+	$capturedImageColorHEX = fread($resultColor, filesize($capturedColorHEXOutputFilePath));
+	fclose($resultColor);
+
+	//write captured image color hex value
+	$captureColorFile = fopen($inputCapturedColorPath, "w");
+	fwrite($captureColorFile, $colorFound->getName($capturedImageColorHEX));
+	fclose($captureColorFile);
+
+	//run color coat python script
+	$commandCoat = escapeshellcmd($pythonScriptPathForColorCoats);
+	$outputCoat = shell_exec($commandCoat);	
+	sleep(6);
+
+	//read color coats as final output 
+	$resultColorCoats = fopen($colorCoatOutputPath, "r");
+	$colorCoats = fread($resultColorCoats, filesize($colorCoatOutputPath));
+	fclose($resultColorCoats);
+
+	$data['respond'] = "OK";
+	$data['result_color_coats'] = $colorCoats;
+}
+else
+{
+	$data['respond'] = "data not set";
+}
+
+header('Content-Type: application/json');
+echo json_encode($data);
+?>
\ No newline at end of file

IT17075190/Xampp/ColorIdentify/testColor.php

+<?php
+require_once('ColorFound.php');
+
+$colorFound = new ColorFound;
+echo $colorFound->getName("#3385ff");
+
+?>
\ No newline at end of file

IT17075190/Xampp/Readme.txt

+Here having the php scripts to call the APIs
\ No newline at end of file