readme: <!--
   * @Description: 
   * @Version: 
   * @Author: Hardy
   * @Date: 2022-02-09 15:13:53
   * @LastEditors: Hardy
   * @LastEditTime: 2022-02-09 16:59:01
  -->
  
  <br />
  <p align="center">
    <h1 align="center">clip-product-title-chinese</h1>
  </p>
  
  ## 基于有赞商品图片和标题语料训练的clip模型。
  
  
  ## Usage
  使用模型前，请 git clone https://github.com/youzanai/trexpark.git
  
  
  ```python
  import torch
  from src.clip.clip import ClipProcesserChinese, ClipChineseModel
  import requests
  from PIL import Image
  
  clip_processor = ClipProcesserChinese.from_pretrained('youzanai/clip-product-title-chinese')
  model = ClipChineseModel.from_pretrained('youzanai/clip-product-title-chinese')
  
  url = 'http://img.yzcdn.cn/upload_files/2015/04/21/0140dac4657f874f2acff9294b28088c.jpg'
  img = Image.open(requests.get(url, stream=True).raw).convert('RGB')
  imgs = [img]
  texts = ['运动鞋', '红色连衣裙', '黑色连衣裙', '大衣', '文具']
  
  f = clip_processor(texts, imgs, return_tensors='pt', truncation=True, padding=True)
  del f['token_type_ids']
  with torch.no_grad():
      out = model(**f)
  logits_per_image, logits_per_text = out['logits_per_image'], out['logits_per_text']
  
  print(logits_per_image.softmax(dim=-1).cpu().detach().numpy())
  
  # 结果： [[1.1700666e-07 9.9948394e-01 5.1582896e-04 4.7687358e-11 6.9604440e-08]]
  ```
  
  
  