i am trying to remove noise in an image less and am currently running this code

```
import numpy as np
import argparse
import cv2
from skimage import morphology

# Construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required = True,
    help = "Path to the image")
args = vars(ap.parse_args())

# Load the image, convert it to grayscale, and blur it slightly
image = cv2.imread(args["image"])

cv2.imshow("Image", image)
cv2.imwrite("image.jpg", image)

greenLower = np.array([50, 100, 0], dtype = "uint8")
greenUpper = np.array([120, 255, 120], dtype = "uint8")

green = cv2.inRange(image, greenLower, greenUpper)
#green = cv2.GaussianBlur(green, (3, 3), 0)

cv2.imshow("green", green)
cv2.imwrite("green.jpg", green)

cleaned = morphology.remove_small_objects(green, min_size=64, connectivity=2)

cv2.imshow("cleaned", cleaned)
cv2.imwrite("cleaned.jpg", cleaned)

cv2.waitKey(0)

```

However, the image does not seem to have changed from "green" to "cleaned" despite using the remove\_small\_objects function. why is this and how do i clean the image up? Ideally i would like to isolate only the image of the cabbage. 

My thought process is after thresholding to remove pixels less than 100 in size, then smoothen the image with blur and fill up the black holes surrounded by white - that is what i did in matlab. If anybody could direct me to get the same results as my matlab implementation, that would be greatly appreciated. Thanks for your help.

Edit: made a few mistakes when changing the code, updated to what it currently is now and display the 3 images

image:

[![enter image description here](https://i.stack.imgur.com/RcVLq.jpg)](https://i.stack.imgur.com/RcVLq.jpg)

green:

[![enter image description here](https://i.stack.imgur.com/i36uk.jpg)](https://i.stack.imgur.com/i36uk.jpg)

clean:

[![enter image description here](https://i.stack.imgur.com/pz5SI.jpg)](https://i.stack.imgur.com/pz5SI.jpg)

my goal is to get somthing like this picture below from matlab implementation:

[![enter image description here](https://i.stack.imgur.com/6roQh.png)](https://i.stack.imgur.com/6roQh.png)