如何在图像上找到仅棕色区域的轮廓？

Question

I have been trying to find contours of brown areas on my frame.

I tried to find these contours in a for loop.

    for c in cntrs:
        area = cv2.contourArea(c)
        if area > 1200:   # i obtanied threshold with trial end error
            x, y, w, h = cv2.boundingRect(c) #find coordinates of brown area
            roi2 = results[y:y + h, x:x + w] #copy these parts to the another image

but i can see only one contour as result

i couldn't understand why i see only one contour. because when i print number of thresholded contours i see 2

here is what i tried

import cv2
import numpy as np
cv2.destroyAllWindows()
capture = cv2.VideoCapture(0) ##masaustunde 1, laptopta 0


def nothing(x):
    pass

roi = cv2.imread('savedImage.jpg')
cv2.imshow('input', roi)
hsv = cv2.cvtColor(roi, cv2.COLOR_RGB2HSV)

lower_green = np.array([0, 0, 0])
upper_green = np.array([40, 255, 255])

mask = cv2.inRange(hsv, lower_green, upper_green)
mask_inv = cv2.bitwise_not(mask)

fg = cv2.bitwise_and(roi, roi, mask=mask_inv)

gray = cv2.cvtColor(fg, cv2.COLOR_BGR2GRAY)
gray = cv2.cvtColor(fg, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 32, 255, 0)[1]
cntrs = cv2.findContours(thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
cntrs = cntrs[0] if len(cntrs) == 2 else cntrs[1]
area_thresh = 0
syc = 0
results = fg.copy()
for c in cntrs:
    area = cv2.contourArea(c)
    if area > 1200: #esige dikkat
        syc = syc + 1
        x, y, w, h = cv2.boundingRect(c)
        roi2 = results[y:y + h, x:x + w]
cv2.imshow('roi2', roi2)

cv2.waitKey(0)


capture.release()  # release the camera from video capture
cv2.destroyAllWindows()

Answer 1

You are writing over the results (roi2) in your loop without waiting to view each one. You have to put the waitKey() into the loop.

Also as I said before, your area threshold was too high.

I also chose better lower and upper thresholds. (I save the hsv file and then measured its values in GUI tool)

This works for me in Python/OpenCV. Press the return key after each roi2 is displayed to go on to the next one.

import cv2
import numpy as np

roi = cv2.imread('green_areas.jpg')
#cv2.imshow('input', roi)

hsv = cv2.cvtColor(roi, cv2.COLOR_RGB2HSV)
#cv2.imshow('hsv', hsv)

lower_green = np.array([30, 30, 30])
upper_green = np.array([60, 140, 100])

mask = cv2.inRange(hsv, lower_green, upper_green)
#cv2.imshow('mask', mask)

mask_inv = cv2.bitwise_not(mask)

fg = cv2.bitwise_and(roi, roi, mask=mask_inv)
#cv2.imshow('fg', fg)

gray = cv2.cvtColor(fg, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 32, 255, 0)[1]
#cv2.imshow('thresh', thresh)

cntrs = cv2.findContours(thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
cntrs = cntrs[0] if len(cntrs) == 2 else cntrs[1]
area_thresh = 0
syc = 0
results = fg.copy()
for c in cntrs:
    area = cv2.contourArea(c)
    if area > 500: #esige dikkat
        syc = syc + 1
        x, y, w, h = cv2.boundingRect(c)
        roi2 = results[y:y + h, x:x + w]
        cv2.imshow('roi2', roi2)
        cv2.waitKey(0)

cv2.destroyAllWindows()