#通过modelscope接口对问题图片予以删除，保证过审


import base64
import json
import os
from io import BytesIO
import pandas as pd
from PIL import Image
from dotenv import load_dotenv
import requests
from transformers import pipeline


def get_nsfw_score(image_path:str,model:"模型")->float:
    #输入图片和模型,返回是否有问题
    img = Image.open(image_path)
    result = model(images=img)
    nsfw_score = next((item['score'] for item in result if item['label']=='nsfw'),None)
    return nsfw_score
    

if __name__ == '__main__':
    load_dotenv()
    model = pipeline("image-classification", model="Falconsai/nsfw_image_detection")#加载模型
    # 获取当前目录的子目录的路径
    img_path = 'manga'
    subdir_path = os.path.join(os.getcwd(), img_path)

    # 图片素材获取（包含子目录下所有图片）
    image_files = []
    for root, dirs, files in os.walk(subdir_path):
        for file in files:
            if file.endswith(".jpg") or file.endswith(".png"):
                image_files.append(os.path.relpath(os.path.join(root, file)))
    for image_path in image_files:
        result = get_nsfw_score(image_path)#返回float的得分
        if result> 0.5:
            print("发现问题图片,需要删除以过审:",image_path)
            os.remove(image_path)
        else:
            print(image_path, "图片没有问题")