How to crop rectangles from a image with opencv

edit

this is the full code. you can see i need to crop each rectangle but also i need to extract the text from each rectangle.

import cv2
import re
import os
import pytesseract
from PIL import Image

# obtengo la direccion donde se encuentra los recortes

lista = os.listdir('C:/Users/Usuario/Documents/Deteccion de Objetos/recortes')

# busco la ultima carpeta creada de los recortes

ultimo = lista.pop()
convertido = int(ultimo)

path = 'C:/Users/Usuario/Documents/Deteccion de Objetos/recortes/' + ultimo

# miro y busco la imagen que necesito para examinar
image = cv2.imread(
    "C:/Users/Usuario/Documents/Deteccion de Objetos/imagenes/Nuevacarpeta/ejemplo4.png")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (5, 5), 0)
thresh = cv2.threshold(
    blur, 127, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]


# Remove dotted lines
cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    area = cv2.contourArea(c)
    if area < 5000:
        cv2.drawContours(thresh, [c], -1, (0, 0, 0), -1)

# Fill contours
close_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
morph = 255 - cv2.morphologyEx(thresh, cv2.MORPH_CLOSE,
                               close_kernel, iterations=6)
cnts = cv2.findContours(morph, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    area = cv2.contourArea(c)
    if area < 15000:
        cv2.drawContours(morph, [c], -1, (0, 0, 0), -1)

# Smooth contours
close = 255 - morph
open_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (20, 20))
opening = cv2.morphologyEx(close, cv2.MORPH_OPEN, close_kernel, iterations=3)

# Busca los contornos y dibuja los resultados
ROI_number = 0
cnts = cv2.findContours(opening, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    #cv2.drawContours(image, [c], -1, (36, 255, 12), 3)
    # aqui se realiza el recorte de cada entidad
    x, y, w, h = cv2.boundingRect(c)
    ROI = image[y:y+h, x:x+w]
    cv2.imwrite(os.path.join(path, 'imagen_{}.png'.format(ROI_number)), ROI)
    cv2.rectangle(image, (x, y), (x+w, y+h), (36, 255, 12), 2)
    ROI_number += 1

# formo una lista con las imagenes de la ultima carpeta creada
listadeimagenes = os.listdir(path)
print(listadeimagenes)

# aqui realizo el reconociemiento de texto dentro de cada entidad
for imagenes in listadeimagenes:
    preprocess = "thresh"
    img = cv2.imread(path + "/" + imagenes)
    cv2.imshow('imagen de la ruta', img)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    if (preprocess == "thresh"):
        gray = cv2.threshold(
            gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
    elif (preprocess == "blur"):
        gray = cv2.medianBlur(gray, 3)
    filename = "{}.png".format(os.getpid())
    cv2.imwrite(filename, gray)

    imgtext = Image.open(filename)

    pytesseract.pytesseract.tesseract_cmd = 'C:/Program Files (x86)/Tesseract-OCR/tesseract.exe'
    # limpio el codigo de caracteres que no corresponden
    texto = pytesseract.image_to_string(imgtext)
    text = re.sub(r'[^\da-zA-Z0-9_() \n]+', '', texto)

    print("-------------------------------------------------------------------")
    print("   *  *  T E X T    D E T E C T E D  *  *")
    print("-------------------------------------------------------------------")
    if text:
        print("No está vacía")
        contenidolineas = text.splitlines()
        palabras = contenidolineas[0].split(" ")
        mensaje2 = ""
        for i in contenidolineas:
            if (contenidolineas.index(i) == 0):
                mensaje2 = mensaje2 + f"Entidad: " + contenidolineas[0]
            else:
                mensaje2 = mensaje2 + f ...