BrandAnalysis/model/clip/train.py

from .clip_model import ClipModel
from db import MongoDao
from tqdm import tqdm
from utils.utils import load_image_from_url,load_image_from_cos

class ClipModelTrainer:
    def __init__(self, brand_name):
        self._brand_name = brand_name
        self._dao = MongoDao('ProductStandard')
        self._model = ClipModel()
        self._products_data = self.load_data()
        
    def load_data(self):
        """获取指定品牌的授权商品图片数据"""
        license_products_data = []
        records = self._dao.get_records_by_query({"brand_name": self._brand_name})
        for record in records:
            license_products_data.append(
                {
                    'product_name': record['product_name'],
                    'images': record['product_images']
                }
            )
            
        return license_products_data
        
    def train(self):
        """计算指定品牌所有授权商品的图片特征"""
        products_feature_map = []
        for data in tqdm(self._products_data, desc=f'正在计算{self._brand_name}的授权产品图像特征...'):
            if len(data['images']) == 0:
                continue
            for image_url in data['images']:
                image = load_image_from_cos(image_url).resize((512, 512))
                feat = self._model.extract_image_feature(image)
                products_feature_map.append(
                    {
                        'product_name': data['product_name'],
                        'image': image_url,
                        'image_feat': feat
                    }
                )
                
        return products_feature_map
    
    def extract_image_feat(self, image):
        return self._model.extract_image_feature(image)
    
if __name__ == '__main__':
    trainer = ClipModelTrainer('李宁')
    res = trainer.train()
    for item in res:
        print(item)