How to separate objects on their color?

Question

I am trying to extract small objects from this image. I have applied Watershed algorithm for segmentation. How do I separate objects based on their color? I am trying to follow this guide but I am getting stuck with an exception error.

Image that needs extraction:

Code screenshot:

Answer 1

There's no need for real color detection here, since processing is done on the output of cv2.watershed . That's an "image" markers of type np.int32 with values 0, 1, 2, 3, ... for the single markers detected by cv2.watershed , whereas 0 is the background. So, there's nothing more to do than iterating all marker values (let's say i ), mask the portion where markers == i , and find the corresponding coordinates of the bounding rectangle, copy that part to a new image and save this to some file.

Here's some code, where the cv2.watershed was mimicked by using cv2.findContours and cv2.drawContours accordingly ( the interesting part regarding the question is solely the second for loop ):

import cv2
import numpy as np
from matplotlib import pyplot as plt
from skimage import io          # Only needed for web grabbing images

# Load some image with circles from web
image = io.imread('https://www.teachertoolsinc.com/images/detailed/26/TCR77379.png')
plt.figure(1), plt.imshow(image), plt.title('original image'), plt.tight_layout()

# Mimic watershed result using findContours and drawContours
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
gray = cv2.threshold(gray, 16, 255, cv2.THRESH_BINARY)[1]
cnts = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
markers = np.zeros_like(gray).astype(np.int32)
for i, cnt in enumerate(cnts):
    markers = cv2.drawContours(markers, [cnt], -1, i+1, cv2.FILLED)
plt.figure(2), plt.imshow(markers), plt.title('markers'), plt.colorbar(), plt.tight_layout()
plt.show()

# Assuming we only have markers now; iterate all values and crop image part
for i in np.arange(1, np.max(markers[:, :])+1):
    pixels = np.array(np.where(markers == i)).astype(np.int32)
    x1 = np.min(pixels[1, :])
    x2 = np.max(pixels[1, :])
    y1 = np.min(pixels[0, :])
    y2 = np.max(pixels[0, :])
    cv2.imwrite(str(i) + '.png', image[y1:y2, x1:x2, :])

That's the input image:

That's the mimicked markers "image" (cf. to provided image in question):

And, here are two of the cut circles:

Hope that helps!

-----------------------
System information
-----------------------
Python:      3.8.1
Matplotlib:  3.2.0rc1
NumPy:       1.18.1
OpenCV:      4.1.2
-----------------------