Update pipeline.py

pipeline.py

@@ -34,10 +34,8 @@ class PreTrainedPipeline():
                 {"feature_vector": [0.6331314444541931,...,-0.7866355180740356,]} containing :
                 - "feature_vector": A list of floats corresponding to the image embedding.
         """
-        inputs = data.pop("inputs", data)
-
         # decode base64 image to PIL
-        image = PIL.Image.open(io.BytesIO(base64.b64decode(inputs['image'])))
+        image = PIL.Image.open(io.BytesIO(base64.b64decode(data)))
         inputs = self.processor(images=image, return_tensors="pt")
         outputs = self.model(**inputs)
         feature_vector = outputs.last_hidden_state[0, 0].tolist()