# coding=utf-8 # Copyright 2025 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. """ Image/Text processor class for SigLIP2. """ from typing import Optional from ...processing_utils import ImagesKwargs, ProcessingKwargs, ProcessorMixin class Siglip2ImagesKwargs(ImagesKwargs, total=False): max_num_patches: Optional[int] patch_size: Optional[int] class Siglip2ProcessorKwargs(ProcessingKwargs, total=False): images_kwargs: Siglip2ImagesKwargs _defaults = { "text_kwargs": { "padding": "max_length", "truncation": True, "max_length": 64, }, "images_kwargs": { "max_num_patches": 256, "patch_size": 16, }, } class Siglip2Processor(ProcessorMixin): r""" Constructs a Siglip2 processor which wraps a Siglip2 image processor and a Gemma tokenizer into a single processor. [`Siglip2Processor`] offers all the functionalities of [`Siglip2ImageProcessor`] and [`GemmaTokenizerFast`]. See the [`~Siglip2Processor.__call__`] and [`~Siglip2Processor.decode`] for more information. Args: image_processor ([`Siglip2ImageProcessor`]): The image processor is a required input. tokenizer ([`GemmaTokenizerFast`]): The tokenizer is a required input. """ attributes = ["image_processor", "tokenizer"] image_processor_class = "AutoImageProcessor" tokenizer_class = "AutoTokenizer" valid_processor_kwargs = Siglip2ProcessorKwargs def __init__(self, image_processor, tokenizer): super().__init__(image_processor, tokenizer) __all__ = ["Siglip2Processor"]