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