find a range of pixel values and replace them with another value in a HSV image

i have a dataset consists of skin cancer images. i want to remove skin area from those images. To do so,

1. first convert images to hsv and split it into h,s,v channels.
2. take 4 patches from the corners of the image(skin area) and find the pixel range of skin area.
3. in the hsv image if the pixels are in the range which found earlier replace it with 1 and otherwise 0 final output image should be a black and white image. since i am new to python i am not able to figure out where i am doing wrong.please kindly help me.

image_array=[]
for category in CATEGORIES:  
    path = os.path.join(DATADIR,'train')# create path 
    for img in os.listdir(path):  # iterate over each image
        image_array=cv2.imread(os.path.join(path,img),cv2.IMREAD_COLOR)
        image_array=cv2.cvtColor(image_array, cv2.COLOR_BGR2RGB)
        plt.imshow(image_array) 
        plt.title('Original image')
        plt.show()
        break  
    break  

# hsv image array
hsv_image=cv2.cvtColor(image_array, cv2.COLOR_RGB2HSV)
plt.imshow(hsv_image)
#hue image
h_image=[]
h_image =hsv_image.copy() # Make a copy
h_image[:,:,1] = 0
h_image[:,:,2] = 0
plt.imshow(h_image)

#calculating min and max values
htr_patch = Rectangle((180,0), 60, 60, edgecolor='r', facecolor='none')
hbr_patch = Rectangle((180,180), 60, 60, edgecolor='r', facecolor='none')
htl_patch = Rectangle((0,0), 60, 60, edgecolor='r', facecolor='none')
hbl_patch = Rectangle((0,180), 60, 60, edgecolor='r', facecolor='none')
h_min=[]
h_max=[]
h_patches=[htr_patch,hbr_patch,htl_patch,hbl_patch]
for h in h_patches:
    print(h)
    coord = Rectangle.get_bbox(h).get_points()
    h=h_image[int(coord[0][1]):int(coord[1][1]),int(coord[0][0]):int(coord[1][0])]
    
    min_val=np.min(h)
    print("min val=",min_val)
    h_min.append(min_val)
    max_val=np.max(h)
    print("max val=",max_val)
    h_max.append(max_val)
    plt.imshow(h)
    plt.show()
print("min vals",h_min) 
print("max vals",h_max)
#binary image
binary_image=cv2.inRange(h_image,h_min_,h_max_)