Create new file

pipeline.py

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+from typing import Dict, List, Any
+from PIL import Image
+from io import BytesIO
+from transformers import pipeline
+
+
+class PreTrainedPipeline():
+    def __init__(self, path=""):
+        self.pipeline=pipeline("zero-shot-image-classification",model=path)
+    
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+       data args:
+            images (:obj:`PIL.Image`)
+            candiates (:obj:`list`)
+      Return:
+            A :obj:`list`:. The list contains items that are dicts should be liked {"label": "XXX", "score": 0.82}
+        """
+        # decode base64 image to PIL
+        image = Image.open(BytesIO(base64.b64decode(data['image'])))
+
+        # run prediction one image wit provided candiates
+        prediction = self.pipeline(images=[image], candidate_labels=data["candiates"])
+        return prediction[0]