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from typing import Dict, List, Any
from PIL import Image
from io import BytesIO
from transformers import pipeline
import base64
class EndpointHandler():
def __init__(self, path=""):
self.pipeline = pipeline("zero-shot-image-classification", model="openai/clip-vit-large-patch14-336")
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
data args:
images (:obj:`string`)
candiates (:obj:`list`)
Return:
A :obj:`list`:. The list contains items that are dicts like {"label": "XXX", "score": 0.82}
"""
inputs = data.pop("inputs", data)
# decode base64 image to PIL
image = Image.open(BytesIO(base64.b64decode(inputs['image'])))
# run prediction with provided candiates
prediction = self.pipeline(images=[image], candidate_labels=inputs["candiates"])
return prediction[0]
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