How to define a threshold value to detect only green colour objects in an image with Python OpenCV?

Update:

I make a HSV colormap. It’s more easy and accurate to find the color range using this map than before.

And maybe I should change use (40, 40,40) ~ (70, 255,255) in hsv to find the green.

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Original answer:

1. Convert to HSV color-space,
2. Use cv2.inRange(hsv, hsv_lower, hsv_higher) to get the green mask.

We use the range (in hsv): (36,0,0) ~ (86,255,255) for this sunflower.

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The source image:

The masked green regions:

More steps:

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The core source code:

import cv2
import numpy as np

## Read
img = cv2.imread("sunflower.jpg")

## convert to hsv
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

## mask of green (36,25,25) ~ (86, 255,255)
# mask = cv2.inRange(hsv, (36, 25, 25), (86, 255,255))
mask = cv2.inRange(hsv, (36, 25, 25), (70, 255,255))

## slice the green
imask = mask>0
green = np.zeros_like(img, np.uint8)
green[imask] = img[imask]

## save 
cv2.imwrite("green.png", green)

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Similar:

1. Choosing the correct upper and lower HSV boundaries for color detection with`cv::inRange` (OpenCV)