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Steps for Color Detection Project

Here are the steps to build an application in Python that can detect colors:

1. Download the files • Color_detection.py – main source code of the project. • Colorpic.jpg – sample image for experimenting. • Colors.csv – a file that contains dataset.

2. Taking an image from the user use argparse library to create an argument parser. Then 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)

3. Next, read the CSV file with pandas The pandas library is very useful when you need to perform various operations on data files like CSV. pd.read_csv() reads the CSV file and loads it into the pandas DataFrame. you have 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)

4. Set a mouse callback event on a window First, you create 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, name the window as ‘image’ and set a callback function which will call the draw_function() whenever a mouse event occurs.

5. Create the draw_function It will calculate the rgb values of the pixel which you double click. The function parameters have the event name, (x,y) coordinates of the mouse position, etc. In the function, check if the event is double-clicked then calculate 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)

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

7. 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, you draw the image on the window. When the user double clicks the window, you 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 you 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()

8. 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