Python - Color detection advice

Python
1

I have a code working just fine, detecting the blue color as follows and creating a square around the object, like on the top image

But if something gets in between(the pencil in this example), the square goes to the side that is bigger:

Camera Detection
Camera Detection1367×914 159 KB

Is there a way so even if the pencil gets in between, the code just ignores this noise and the square still works the same as the first example ?

Here’s the code, thanks for reading !

import cv2
import numpy as np
import time


# Camera Connection/Setup
cap = cv2.VideoCapture(0)

cap.set(3, 480)
cap.set(4, 320)
_, frame = cap.read()
rows, cols, _ = frame.shape

x_medium = int(cols / 2)
centerx = int(rows / 2)
centerl = int(cols / 2)
while True:
    _, frame = cap.read()
    hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    
    # red color
    low_red = np.array([100, 100, 100])
    high_red = np.array([120, 255, 255])
    red_mask = cv2.inRange(hsv_frame, low_red, high_red)
    contours, _ = cv2.findContours(red_mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    contours = sorted(contours, key=lambda x:cv2.contourArea(x), reverse=True)

    for cnt in contours:
        (x, y, w, h) = cv2.boundingRect(cnt)

        x_medium = int((x + x + w) / 2)
   
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
        #print("X = ", x)
        #print("Y = ", y)
        #print("\n")
        break

    center = (centerl, centerx)
    cv2.circle(frame, center, 2, (0, 0, 255), -1)

    
    cv2.imshow("Frame", frame)
    cv2.imshow("Mask", red_mask)

    
    key = cv2.waitKey(1)

    if key == 27:
        break
    

cap.release()
cv2.destroyAllWindows()
2

problem is, that you’ll never know, if you have a ‘split’ contour, or 2 (or more !?) originally seperate objects.

otherwise, you could join the 2 contours (cv2…vconcat())
and get the boundingRect() from that

1 Like
3

Ohh, didn’t know you could join them, thank you !! There’ll only ever be one object, but possible noises such as discontinuation of the contour, so the concat should work.

4

… famous last words, hehe :wink: