Color-Detection: A Python repository from sahaavi

Demo

The Dataset

Colors are made up of 3 primary colors; red, green, and blue. In computers, we define each color value within a range of 0 to 255. So in how many ways we can define a color? The answer is 256 * 256 * 256 = 16,581,375. There are approximately 16.5 million different ways to represent a color. In our dataset, we need to map each color’s values with their corresponding names. But don’t worry, we don’t need to map all the values. We will be using a dataset that contains RGB values with their corresponding names. The CSV file for our dataset has been taken from this link:

Colors Dataset
The colors.csv file includes 865 color names along with their RGB and hex values.

Prerequisites

OpenCV
Pandas
numpy

Taking an image from the user

Using argparse library to create an argument parser. Directly give an image path from the command prompt:

import argparse
ap = argparse.ArgumentParser()
ap.add_argument('-i', '--image', required=True, help="Image Path")
args = vars(ap.parse_args())
img_path = args['image']
#Reading image with opencv
img = cv2.imread(img_path)

Read the CSV file with pandas

The pandas library is very useful to perform various operations on data files like CSV. pd.read_csv() reads the CSV file and loads it into the pandas DataFrame. Here assigned each column with a name for easy accessing.

#Reading csv file with pandas and giving names to each column
index=["color","color_name","hex","R","G","B"]
csv = pd.read_csv('colors.csv', names=index, header=None)

Set a mouse callback event on a window

First, created a window in which the input image will display. Then, set a callback function which will be called when a mouse event happens.

cv2.namedWindow('image')
cv2.setMouseCallback('image',draw_function)

With these lines, named window as ‘image’ and set a callback function which will call the draw_function() whenever a mouse event occurs.

Create the draw_function

It will calculate the rgb values of the pixel which will be double clicked. The function parameters have the event name, (x,y) coordinates of the mouse position, etc. In the function, first check if the event is double-clicked then calculated and set the r,g,b values along with x,y positions of the mouse.

def draw_function(event, x,y,flags,param):
    if event == cv2.EVENT_LBUTTONDBLCLK:
        global b,g,r,xpos,ypos, clicked
        clicked = True
        xpos = x
        ypos = y
        b,g,r = img[y,x]
        b = int(b)
        g = int(g)
        r = int(r)

Calculate distance to get color name

We have the r,g and b values. Now, we need another function which will return us the color name from RGB values. To get the color name, we calculate a distance(d) which tells us how close we are to color and choose the one having minimum distance.

Distance is calculated by this formula:

d = abs(Red – ithRedColor) + (Green – ithGreenColor) + (Blue – ithBlueColor)

def getColorName(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

Display image on the window

Whenever a double click event occurs, it will update the color name and RGB values on the window.

Using the cv2.imshow() function, we draw the image on the window. When the user double clicks the window, we draw a rectangle and get the color name to draw text on the window using cv2.rectangle and cv2.putText() functions.

while(1):
    cv2.imshow("image",img)
    if (clicked):
        #cv2.rectangle(image, startpoint, endpoint, color, thickness) -1 thickness fills rectangle entirely
        cv2.rectangle(img,(20,20), (750,60), (b,g,r), -1)

        #Creating text string to display ( Color name and RGB values )
        text = getColorName(r,g,b) + ' R='+ str(r) + ' G='+ str(g) + ' B='+ str(b)

        #cv2.putText(img,text,start,font(0-7), fontScale, color, thickness, lineType, (optional bottomLeft bool) )
        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 the loop when user hits 'esc' key 
    if cv2.waitKey(20) & 0xFF ==27:
        break

cv2.destroyAllWindows()

Run Python File

Run the Python file from the command prompt. Make sure to give an image path using ‘-i’ argument. If the image is in another directory, then you need to give full path of the image:

python color_detection.py -i <add your image path here>

Output:

Double click on the window to know the name of the pixel color.

sahaavi/Color-Detection