https://github.com/tgxs002/HPSv2

hpsv2.py

from PIL import Image
import hpsv2
import torch

class HPSv2:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "images": ("IMAGE", ),
                "prompt": ("STRING", {"multiline": True}),
            },
        }

    RETURN_TYPES = ("IMAGE", "STRING")
    FUNCTION = "apply"
    CATEGORY = "_for_testing"

    def apply(self, images, prompt):
        images_numpy = (images * 255).numpy().astype('uint8')
        images_pillow = [Image.fromarray(image) for image in images_numpy]

        scores = []

        for image in images_pillow:
            score = hpsv2.score(image, prompt, hps_version="v2.1")[0]
            scores.append(score)

        

        # 画像とスコアをペアにしてソート
        images_scores = sorted(zip(images, scores), key=lambda x: x[1], reverse=True)

        # ソートされた結果から画像とスコアを再取得
        sorted_images, sorted_scores = zip(*images_scores)

        result_string = "\n".join([f"image_{i+1}:{result:4f}" for i, result in enumerate(sorted_scores)])
        sorted_images = torch.stack(sorted_images)

        return (sorted_images, result_string)

NODE_CLASS_MAPPINGS = {
    "HPSv2": HPSv2,
}

__all__ = ["NODE_CLASS_MAPPINGS"]