Image processing on the drawcontours area

Python
1

I’d like to convert only the drawcontours area to RGB images, then convert it to HSV again in order to update lower and upper values every frame over time.
Note: I’d like to avoid using the ROI of the rectangle area because of drawcontours is the actual area.

Full my code:

import cv2
import numpy as np
import time

cap = cv2.VideoCapture(0)
width = cap.get(3)  # float
height = cap.get(4)  # float
time.sleep(2.0)
while (1):
    _, img = cap.read()
    clone1 = img.copy()
    if _ is True:
        hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    else:
        continue

    black_lower = np.array([0, 0, 0], np.uint8)
    black_upper = np.array([180, 255, 30], np.uint8)
    black = cv2.inRange(hsv, black_lower, black_upper)
    # Morphological Transform, Dilation

    kernal = np.ones((5, 5), "uint8")
    black = cv2.dilate(black, kernal)
    res_black = cv2.bitwise_and(img, img, mask=black)
    (_, contours, hierarchy) = cv2.findContours(black, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    cnts = sorted(contours, key=cv2.contourArea, reverse=True)[:1]  # get largest  contour area
    for pic, contour in enumerate(cnts):
        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)
            roi1 = clone1[y:y + h, x:x + h]
            cv2.imshow("roi1", roi1)
            cv2.putText(img, "Black Colour", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 0))
            bbbbb = cv2.drawContours(img, [contour], -1, (0, 255, 0), 3)  # segmentation
            # roi2 = clone1[contour[[0]]]
            # cv2.imshow("roi2", roi2)

    cv2.imshow("Color Tracking", img)
    if cv2.waitKey(10) & 0xFF == ord('q'):
        cap.release()
        cv2.destroyAllWindows()
        break
2

If I understand well your question you can

  • draw contour in a mask
  • convert image in hsv
  • copy hsv pixel in bgr image using mask