Source code for oumi.core.processors.default_image_processor
# Copyright 2025 - Oumi
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# limitations under the License.
from typing import Any, Callable, Optional
import PIL.Image
import transformers
from typing_extensions import override
from oumi.core.processors.base_image_processor import BaseImageProcessor
[docs]
class DefaultImageProcessor(BaseImageProcessor):
"""Default implementation of image processor that wraps a callable object."""
def __init__(self, worker_processor: Any):
"""Initializes the processor."""
if worker_processor is None:
raise ValueError("Worker image processor must be provided!")
elif not callable(worker_processor):
raise ValueError("Worker image processor is not callable!")
self._worker_processor: Callable = worker_processor
[docs]
@override
def __call__(
self,
images: list[PIL.Image.Image],
*,
return_tensors: Optional[str] = "pt",
) -> transformers.BatchFeature:
"""Extracts image features.
Args:
images: A list of input images.
return_tensors: The format of returned tensors.
Returns:
transformers.BatchFeature: The model-specific input features.
"""
result = self._worker_processor(images=images, return_tensors=return_tensors)
if result is None:
raise RuntimeError("Image processor returned `None`.")
elif not isinstance(result, transformers.BatchFeature):
raise RuntimeError(
"Image processor returned an object that is not a BatchFeature. "
f"Actual type: {type(result)}"
)
return result