OpenCV/Pillow – 画像を base64 形式にエンコードする方法

概要

OpenCV または Pillow で読み込んだ画像を base64 文字列に変換する方法について解説します。

Pillow の画像形式から base64 文字列にエンコードする

Pillow の PIL.Image から base64 文字列にエンコードするコードを紹介します。

In [1]:

import base64
from io import BytesIO
from PIL import Image


def pil_to_base64(img, format="jpeg"):
    buffer = BytesIO()
    img.save(buffer, format)
    img_str = base64.b64encode(buffer.getvalue()).decode("ascii")

    return img_str


img = Image.open("sample.jpg")

# base64 文字列 (jpeg) に変換する。
img_base64 = pil_to_base64(img, format="jpeg")

変換が行えたことを、img タグで表示して確認します。

In [2]:

from IPython.display import HTML, display

# インライン画像として表示して確認する。
img_tag = f'<img src="data:image/png;base64,{img_base64}">'
display(HTML(img_tag))

base64 文字列から Pillow の画像形式にデコードする

base64 文字列から Pillow の PIL.Image にデコードするコードを紹介します。

In [3]:

import base64
from io import BytesIO

from PIL import Image


def base64_to_pil(img_str):
    if "base64," in img_str:
        # DARA URI の場合、data:[<mediatype>][;base64], を除く
        img_str = img_str.split(",")[1]
    img_raw = base64.b64decode(img_str)
    img = Image.open(BytesIO(img_raw))

    return img


# base64 文字列
img_base64 = "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"

# PIL.Image 形式に変換する。
img = base64_to_pil(img_base64)

# インライン画像として表示して確認する。
img

OpenCV の画像形式から base64 文字列にエンコードする

OpenCV の ndarray から base64 文字列にエンコードするコードを紹介します。

In [4]:

import base64

import cv2


def cv_to_base64(img):
    _, encoded = cv2.imencode(".jpg", img)
    img_str = base64.b64encode(encoded).decode("ascii")

    return img_str


# 画像を読み込む。
img = cv2.imread("sample.jpg")
img_str = cv_to_base64(img)

変換が行えたことを、img タグで表示して確認します。

In [5]:

# インライン画像として表示して確認する。
from IPython.display import HTML, display

img_tag = f'<img src="data:image/jpeg;base64,{img_str}">'
display(HTML(img_tag))

base64 文字列から OpenCV の画像形式にデコードする

base64 文字列から OpenCV の画像形式 ndarray にデコードするコードを紹介します。

In [6]:

import base64

import cv2
import numpy as np


def base64_to_cv(img_str):
    if "base64," in img_str:
        # DARA URI の場合、data:[<mediatype>][;base64], を除く
        img_str = img_str.split(",")[1]
    img_raw = np.frombuffer(base64.b64decode(img_str), np.uint8)
    img = cv2.imdecode(img_raw, cv2.IMREAD_UNCHANGED)

    return img


# base64 文字列
img_base64 = "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"

# ndarray 形式に変換する。
img = base64_to_cv(img_base64)

In [7]:

from IPython.display import Image, display


def imshow(img):
    """ndarray 配列をインラインで Notebook 上に表示する。"""
    ret, encoded = cv2.imencode(".jpg", img)
    display(Image(encoded))


# インライン画像として表示して確認する。
imshow(img)