Pythonでローカル環境にAI生成画像判定ツールを作る方法【サンプルコード付き】

pip install torch transformers pillow

from transformers import pipeline
from PIL import Image

# AI生成画像判定モデルを読み込み
detector = pipeline(
    "image-classification",
    model="umm-maybe/AI-image-detector"
)

# 判定する画像
image_path = "test.jpg"

# 画像読み込み
img = Image.open(image_path)

# 判定実行
results = detector(img)

print("\n判定結果:")

for result in results:
    print(
        f"{result['label']}: {result['score']:.4f}"
    )

# 最も高いスコアを取得
best = max(
    results,
    key=lambda x: x["score"]
)

print("\n最終判定:")
print(
    f"{best['label']} "
    f"({best['score']*100:.1f}%)"
)

python detect.py

from transformers import pipeline
from PIL import Image
import os

detector = pipeline(
    "image-classification",
    model="umm-maybe/AI-image-detector"
)

folder = "images"

for file in os.listdir(folder):

    if file.lower().endswith(
        (".jpg",".jpeg",".png",".webp")
    ):

        path = os.path.join(
            folder,
            file
        )

        img = Image.open(path)

        result = detector(img)

        best = max(
            result,
            key=lambda x:x["score"]
        )

        print(
            f"{file}"
            f" → {best['label']}"
            f" ({best['score']*100:.1f}%)"
        )