Stable Diffusion为秋叶大佬的绘世2.2.4
WEBUI api后台：Http://127.0.0.1:7860/docs

数据获取结果，python代码在文章尾部

1girl: 0.9883618950843811, 98%solo: 0.9468605518341064, 94%horns: 0.9203381538391113, 92%braid: 0.7536494731903076, 75%brown_hair: 0.7361204624176025, 73%sensitive: 0.7181869745254517, 71%looking_at_viewer: 0.6558270454406738, 65%long_hair: 0.6555134654045105, 65%portrait: 0.5619801878929138, 56%hair_ornament: 0.5276427268981934, 52%lips: 0.5271897912025452, 52%realistic: 0.47530364990234375, 47%brown_eyes: 0.44382530450820923, 44%fur_trim: 0.44058263301849365, 44%red_hair: 0.4004508852958679, 40%upper_body: 0.39194822311401367, 39%mole: 0.35748565196990967, 35%general: 0.2813188433647156, 28%questionable: 0.004140794277191162, 0%explicit: 0.0005668997764587402, 0%

使用/tagger/v1/interrogate，先使用get方法获取model模组有十多个，然后把JSON_data提交上去就可以了。记得把图片转码为base64。本文章仅用于测试，请仔细阅读api docs，model和threshold按照需求调整即可

import requestsimport base64from collections import OrderedDictfrom PIL import Imageurl = 'http://127.0.0.1:7860/tagger/v1/interrogate'image_path = 'D:/code/image/6.jpg'model = 'wd14-convnext'threshold = 0.35#确认照片为上传照片image = Image.open(image_path)image.show()# 将图片转换为Base64字符串with open(image_path, 'rb') as file:    image_data = file.read()    base64_image = base64.b64encode(image_data).decode('utf-8')# 构建请求体的jsON数据data = {    "image": base64_image,    "model": model,    "threshold": threshold}# 发送POST请求response = requests.post(url, json=data)# 检查响应状态码if response.status_code == 200:    json_data = response.json()    # 处理返回的JSON数据    caption_dict = json_data['caption']    sorted_items = sorted(caption_dict.items(), key=lambda x: x[1], reverse=True)    output = '\n'.join([f'{k}: {v}, {int(v * 100)}%' for k, v in sorted_items])    print(output) else:    print('Error:', response.status_code)    print('Response body:', response.text)

来源地址：https://blog.csdn.net/weixin_42375356/article/details/130904119