Make kwargs uniform for SAM

src/transformers/models/sam/processing_sam.py

@@ -17,13 +17,14 @@
 """
 
 from copy import deepcopy
-from typing import Optional, Union
+from typing import List, Optional, Union
 
 import numpy as np
 
-from ...processing_utils import ProcessorMixin
-from ...tokenization_utils_base import BatchEncoding
-from ...utils import TensorType, is_tf_available, is_torch_available
+from ...image_utils import ImageInput
+from ...processing_utils import ImagesKwargs, ProcessingKwargs, ProcessorMixin
+from ...tokenization_utils_base import BatchEncoding, PreTokenizedInput, TextInput
+from ...utils import is_tf_available, is_torch_available
 
 
 if is_torch_available():
@@ -33,6 +34,18 @@
     import tensorflow as tf
 
 
+class SamImagesKwargs(ImagesKwargs):
+    segmentation_maps: Optional[ImageInput]
+    input_points: Optional[List[List[float]]]
+    input_labels: Optional[List[List[int]]]
+    input_boxes: Optional[List[List[List[float]]]]
+
+
+class SamProcessorKwargs(ProcessingKwargs, total=False):
+    images_kwargs: SamImagesKwargs
+    _defaults = {}
+
+
 class SamProcessor(ProcessorMixin):
     r"""
     Constructs a SAM processor which wraps a SAM image processor and an 2D points & Bounding boxes processor into a
@@ -55,25 +68,41 @@ def __init__(self, image_processor):
         self.point_pad_value = -10
         self.target_size = self.image_processor.size["longest_edge"]
 
+    @staticmethod
+    def _add_args_for_backward_compatibility(args):
+        """
+        Remove this function once support for args is dropped in __call__
+        """
+        if len(args) > 4:
+            raise ValueError("Too many positional arguments")
+        return dict(zip(("segmentation_maps", "input_points", "input_labels", "input_boxes"), args))
+
     def __call__(
         self,
         images=None,
-        segmentation_maps=None,
-        input_points=None,
-        input_labels=None,
-        input_boxes=None,
-        return_tensors: Optional[Union[str, TensorType]] = None,
+        *args,  # to be deprecated
+        text: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None,
+        audio=None,
+        video=None,
         **kwargs,
     ) -> BatchEncoding:
         """
         This method uses [`SamImageProcessor.__call__`] method to prepare image(s) for the model. It also prepares 2D
         points and bounding boxes for the model if they are provided.
         """
+        output_kwargs = self._merge_kwargs(
+            SamProcessorKwargs,
+            tokenizer_init_kwargs={},
+            **kwargs,
+            **self._add_args_for_backward_compatibility(args),
+        )
+        input_points = output_kwargs["images_kwargs"].pop("input_points", None)
+        input_labels = output_kwargs["images_kwargs"].pop("input_labels", None)
+        input_boxes = output_kwargs["images_kwargs"].pop("input_boxes", None)
+
         encoding_image_processor = self.image_processor(
             images,
-            segmentation_maps=segmentation_maps,
-            return_tensors=return_tensors,
-            **kwargs,
+            **output_kwargs["images_kwargs"],
         )
 
         # pop arguments that are not used in the foward but used nevertheless
@@ -94,7 +123,7 @@ def __call__(
             input_points=input_points,
             input_labels=input_labels,
             input_boxes=input_boxes,
-            return_tensors=return_tensors,
+            return_tensors=output_kwargs["common_kwargs"].get("return_tensors"),
         )
 
         return encoding_image_processor