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#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")
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