Update pipeline.py

pipeline.py

@@ -42,11 +42,11 @@ class PreTrainedPipeline():
             A :obj:`dict`:. The object returned should be a dict of one list like [[{"label": 0.9939950108528137}]] containing :
                 - "caption": A string corresponding to the generated caption.
         """
-        image = data.pop("inputs", data)
+        inputs = data.pop("inputs", data)
         parameters = data.pop("parameters", {})
 
         # decode base64 image to PIL
-        image = Image.open(BytesIO(base64.b64decode(image)))
+        image = Image.open(BytesIO(base64.b64decode(inputs['image'])))
         image = self.transform(image).unsqueeze(0).to(device)   
         with torch.no_grad():
             caption = self.model.generate(