cell_extract_test_1.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 28 19:58:03 2023

@author: mikewang
"""
import cv2
import numpy as np
from tqdm import tqdm

# Load image, grayscale, Otsu's threshold
image = cv2.imread('1f8f08ea-b5b3-4f68-94d4-3cc071b7dce8.png')
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = 255 - gray
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

# Morph open to remove noise
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=1)

# Find contours, obtain bounding box, extract and save ROI
ROI_number = 0
cnts = cv2.findContours(opening, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]

cnts_length = len(cnts)
bbox_array = np.zeros([4,cnts_length])
overlapped_check_array = np.ones([cnts_length,], dtype = 'int32')

#%% filter out all over lapping bounding boxs 
# first store the bbox coordinate
for i, c in enumerate(cnts):
    x,y,w,h = cv2.boundingRect(c) # bounding box parameters
    bbox_array[:,i] = np.array([x,y,x+w,y+h])
# second filter out all overlapping cases 
for i in range(cnts_length):
    if overlapped_check_array[i] != 0:
        x_tl,y_tl,x_br,y_br = bbox_array[:,i] # current bbox 
        w = x_br-x_tl
        h = y_br - y_tl
        if w/h > 1.5 or h/w > 1.5:
            overlapped_check_array[i] = 0
        # loop through all bbox
        for j in range(cnts_length):
            if overlapped_check_array[j] != 0 and overlapped_check_array[i] != 0 and i != j:
                x_tl_loop,y_tl_loop,x_br_loop,y_br_loop = bbox_array[:,j] # looped troughed bbox 
                # if not not overlapping
                if not ((x_tl > x_br_loop or x_tl_loop > x_br) or (y_br > y_tl_loop or y_br_loop > y_tl)):
                    overlapped_check_array[i] = 0
                    overlapped_check_array[j] = 0
                    
bbox_array_non_overlapping = bbox_array[:,overlapped_check_array==1]
non_overlapping_length = bbox_array_non_overlapping.shape[1]
# extract only non-overlapping bbox
for i in range(non_overlapping_length):
    x_tl,y_tl,x_br,y_br = bbox_array_non_overlapping[:,i]
    cv2.rectangle(image, (int(x_tl), int(y_tl)), (int(x_br), int(y_br)), (36,255,12), 2)
    ROI = original[int(y_tl):int(y_br), int(x_tl):int(x_br)]
    cv2.imwrite('ROI_{}.png'.format(ROI_number), ROI)
    ROI_number += 1