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image_processor.py

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+import copy
+from typing import Dict, Any
+
+from transformers.image_processing_utils import ImageProcessingMixin, BatchFeature
+from timm.data.transforms_factory import create_transform
+
+
+
+class ClassificationImageProprocessor(ImageProcessingMixin):
+    def __init__(self, data_config, **kwargs):
+        super().__init__(**kwargs)
+        self.data_config = data_config
+        self._transform = create_transform(**data_config)
+
+    def __call__(self, images, **kwargs) -> BatchFeature:
+        """Preprocess an image or a batch of images."""
+        return self.preprocess(images, **kwargs)
+
+    def preprocess(self, images, return_tensors=None, **kwargs) -> BatchFeature:
+        images = [self._transform(image) for image in images]
+        data = {"pixel_values": images} 
+        return BatchFeature(data=data, tensor_type=return_tensors)
+
+    def to_dict(self) -> Dict[str, Any]:
+        """
+        Serializes this instance to a Python dictionary.
+
+        Returns:
+            `Dict[str, Any]`: Dictionary of all the attributes that make up this image processor instance.
+        """
+        output = copy.deepcopy(self.__dict__)
+        output.pop("_transform", None)
+        output["image_processor_type"] = self.__class__.__name__
+
+        return output