Color detection

Python
1

Hi, I am trying to detect between two types of White (Alaskan White and Pearl White) but I am not getting results, can anyone help me? This is my code and these are the two types of white.

WhatsApp Image 2021-07-22 at 10.45.40
WhatsApp Image 2021-07-22 at 10.45.40958×1280 77.5 KB 

import cv2
import numpy as np

# capturing video through webcam

cap = cv2.VideoCapture(0)

while(1):
    _, img = cap.read()

    # converting frame(img == BGR) to HSV(hue-saturation-value)

    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

    # red color

    red_lower = np.array([136,87,111],np.uint8)
    red_upper = np.array([180,255,255],np.uint8)

    # blue color

    blue_lower = np.array([99,115,150],np.uint8)
    blue_upper = np.array([110,255,255],np.uint8)

    # yellow color

    yellow_lower = np.array([22,60,200],np.uint8)
    yellow_upper = np.array([60,255,255],np.uint8)

    # white color

    white_lower = np.array([0,0,200],np.uint8)
    white_upper = np.array([180,20,255],np.uint8)

    # black color

    black_lower = np.array([0,0,0],np.uint8)
    black_upper = np.array([180,255,30],np.uint8)

    # all color together

    red = cv2.inRange(hsv, red_lower, red_upper)
    blue = cv2.inRange(hsv, blue_lower, blue_upper)
    yellow = cv2.inRange(hsv, yellow_lower, yellow_upper)
    white = cv2.inRange(hsv, white_lower, white_upper)
    black = cv2.inRange(hsv, black_lower, black_upper)

    # Morphological Transform, Dilation

    kernal = np.ones((5, 5), "uint8")

    red = cv2.dilate(red, kernal)
    res_red = cv2.bitwise_and(img, img, mask = red)

    blue = cv2.dilate(blue, kernal)
    res_blue = cv2.bitwise_and(img, img, mask = blue)

    yellow = cv2.dilate(yellow, kernal)
    res_yellow = cv2.bitwise_and(img, img, mask = yellow)

    white = cv2.dilate(white, kernal)
    res_white = cv2.bitwise_and(img, img, mask = white)

    black = cv2.dilate(black, kernal)
    res_black = cv2.bitwise_and(img, img, mask = black)

    # Tracking red
    contours, hierarchy = cv2.findContours(red, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for pic, contour in enumerate(contours):
        area = cv2.contourArea(contour)
        if(area > 300):
            x, y, w, h = cv2.boundingRect(contour)
            img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 2)
            cv2.putText(img, "ROJO: ", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255))    

    # Tracking blue
    contours, hierarchy = cv2.findContours(blue, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for pic, contour in enumerate(contours):
        area = cv2.contourArea(contour)
        if(area > 300):
            x, y, w, h = cv2.boundingRect(contour)
            img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
            cv2.putText(img, "AZUL: ", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 0))
            

    # Tracking yellow
    contours, hierarchy = cv2.findContours(yellow, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for pic, contour in enumerate(contours):
        area = cv2.contourArea(contour)
        if(area > 300):
            x, y, w, h = cv2.boundingRect(contour)
            img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
            cv2.putText(img, "AMARILLO: ", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 0))

    # Tracking white
    contours, hierarchy = cv2.findContours(white, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for pic, contour in enumerate(contours):
        area = cv2.contourArea(contour)
        if(area > 300):
            x, y, w, h = cv2.boundingRect(contour)
            img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 255, 255), 2)
            cv2.putText(img, "BLANCO: ", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255))

    # Tracking black
    contours, hierarchy = cv2.findContours(black, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for pic, contour in enumerate(contours):
        area = cv2.contourArea(contour)
        if(area > 300):
            x, y, w, h = cv2.boundingRect(contour)
            img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 0), 2)
            cv2.putText(img, "NEGRO: ", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 0))
    
    cv2.imshow("Color Tracking", img)
    if cv2.waitKey(10) & 0xFF == ord('q'):
        cap.release()
        cv2.destroyAllWindows()
        break