90 lines
3.4 KiB
Python
90 lines
3.4 KiB
Python
# coding=utf-8
|
|
# Copyright 2023 The HuggingFace Inc. team.
|
|
#
|
|
# 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.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
"""
|
|
Processor class for TVLT.
|
|
"""
|
|
|
|
from ...processing_utils import ProcessorMixin
|
|
|
|
|
|
class TvltProcessor(ProcessorMixin):
|
|
r"""
|
|
Constructs a TVLT processor which wraps a TVLT image processor and TVLT feature extractor into a single processor.
|
|
|
|
[`TvltProcessor`] offers all the functionalities of [`TvltImageProcessor`] and [`TvltFeatureExtractor`]. See the
|
|
docstring of [`~TvltProcessor.__call__`] for more information.
|
|
|
|
Args:
|
|
image_processor (`TvltImageProcessor`):
|
|
An instance of [`TvltImageProcessor`]. The image processor is a required input.
|
|
feature_extractor (`TvltFeatureExtractor`):
|
|
An instance of [`TvltFeatureExtractor`]. The feature extractor is a required input.
|
|
"""
|
|
|
|
attributes = ["image_processor", "feature_extractor"]
|
|
image_processor_class = "TvltImageProcessor"
|
|
feature_extractor_class = "TvltFeatureExtractor"
|
|
|
|
def __init__(self, image_processor, feature_extractor):
|
|
super().__init__(image_processor=image_processor, feature_extractor=feature_extractor)
|
|
|
|
self.image_processor = image_processor
|
|
self.feature_extractor = feature_extractor
|
|
|
|
def __call__(
|
|
self,
|
|
images=None,
|
|
audio=None,
|
|
images_mixed=None,
|
|
sampling_rate=None,
|
|
mask_audio=False,
|
|
mask_pixel=False,
|
|
*args,
|
|
**kwargs,
|
|
):
|
|
"""
|
|
Forwards the `images` argument to TvltImageProcessor's [`~TvltImageProcessor.preprocess`] and the `audio`
|
|
argument to TvltFeatureExtractor's [`~TvltFeatureExtractor.__call__`]. Please refer to the docstring of the
|
|
above two methods for more information.
|
|
"""
|
|
|
|
if images is None and audio is None:
|
|
raise ValueError("You need to specify either an `images` or `audio` input to process.")
|
|
|
|
images_mixed_dict = None
|
|
if images is not None:
|
|
images_dict = self.image_processor(images, mask_pixel=mask_pixel, *args, **kwargs)
|
|
if images_mixed is not None:
|
|
images_mixed_dict = self.image_processor(images_mixed, is_mixed=True, *args, **kwargs)
|
|
if audio is not None:
|
|
audio_dict = self.feature_extractor(
|
|
audio, *args, sampling_rate=sampling_rate, mask_audio=mask_audio, **kwargs
|
|
)
|
|
|
|
output_dict = {}
|
|
if audio is not None:
|
|
output_dict.update(audio_dict)
|
|
if images is not None:
|
|
output_dict.update(images_dict)
|
|
if images_mixed_dict is not None:
|
|
output_dict.update(images_mixed_dict)
|
|
return output_dict
|
|
|
|
@property
|
|
def model_input_names(self):
|
|
image_processor_input_names = self.image_processor.model_input_names
|
|
feature_extractor_input_names = self.feature_extractor.model_input_names
|
|
return list(dict.fromkeys(image_processor_input_names + feature_extractor_input_names))
|