fashxp/zero-shot-image-classification

1from typing import Dict, List, Any2from PIL import Image3from io import BytesIO4from transformers import pipeline5import base646 7 8class EndpointHandler():9    def __init__(self, path=""):10        self.pipeline=pipeline("zero-shot-image-classification",model="openai/clip-vit-large-patch14-336")11 12    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:13        """14       data args:15            inputs (:obj:`string`)16            parameters (:obj:)17      Return:18            A :obj:`list`:. The list contains items that are dicts should be liked {"label": "XXX", "score": 0.82}19        """20        image_data = data.pop("inputs", data)21        # decode base64 image to PIL22        image = Image.open(BytesIO(base64.b64decode(image_data)))23 24        parameters = data.pop("parameters", data)25        candidate_labels = parameters['candidate_labels']26 27        candidate_labels_array = list(map(str.strip, candidate_labels.split(',')))28 29        # run prediction one image wit provided candiates30        prediction = self.pipeline(images=[image], candidate_labels=candidate_labels_array)31        return prediction[0]