グレースケールやαチャンネル付きの画像でも変換できるように関数化しました。

Pillow → OpenCV

import numpy as np
import cv2

def pil2cv(image):
    ''' PIL型 -> OpenCV型 '''
    new_image = np.array(image, dtype=np.uint8)
    if new_image.ndim == 2:  # モノクロ
        pass
    elif new_image.shape[2] == 3:  # カラー
        new_image = cv2.cvtColor(new_image, cv2.COLOR_RGB2BGR)
    elif new_image.shape[2] == 4:  # 透過
        new_image = cv2.cvtColor(new_image, cv2.COLOR_RGBA2BGRA)
    return new_image

cv2を使わずに書くなら，

import numpy as np

def pil2cv(image):
    ''' PIL型 -> OpenCV型 '''
    new_image = np.array(image, dtype=np.uint8)
    if new_image.ndim == 2:  # モノクロ
        pass
    elif new_image.shape[2] == 3:  # カラー
        new_image = new_image[:, :, ::-1]
    elif new_image.shape[2] == 4:  # 透過
        new_image = new_image[:, :, [2, 1, 0, 3]]
    return new_image

OpenCV → Pillow

from PIL import Image
import cv2

def cv2pil(image):
    ''' OpenCV型 -> PIL型 '''
    new_image = image.copy()
    if new_image.ndim == 2:  # モノクロ
        pass
    elif new_image.shape[2] == 3:  # カラー
        new_image = cv2.cvtColor(new_image, cv2.COLOR_BGR2RGB)
    elif new_image.shape[2] == 4:  # 透過
        new_image = cv2.cvtColor(new_image, cv2.COLOR_BGRA2RGBA)
    new_image = Image.fromarray(new_image)
    return new_image

cv2を使わずに書くなら，

from PIL import Image

def cv2pil(image):
    ''' OpenCV型 -> PIL型 '''
    new_image = image.copy()
    if new_image.ndim == 2:  # モノクロ
        pass
    elif new_image.shape[2] == 3:  # カラー
        new_image = new_image[:, :, ::-1]
    elif new_image.shape[2] == 4:  # 透過
        new_image = new_image[:, :, [2, 1, 0, 3]]
    new_image = Image.fromarray(new_image)
    return new_image