fashion-clip-embedding / pipeline.py
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Initial pipeline setup
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import base64
from io import BytesIO
from typing import Any, Dict, List
from fashion_clip.fashion_clip import FashionCLIP
from PIL import Image
class PreTrainedPipeline:
def __init__(self, path=""):
self.model = FashionCLIP("fashion-clip")
def __call__(self, inputs: str) -> List[float]:
"""
Args:
inputs (:obj:`str`):
a string to get the features from.
Return:
A :obj:`list` of floats: The features computed by the model.
"""
image = Image.open(BytesIO(base64.b64decode(inputs)))
return self.model.encode_images([image], batch_size=1)[0].tolist()