o h$@sddlmZmZddlZddlmZmZmZm Z m Z ddl m Z m Z er1ddlmZddlmZer:dd lmZe eZee Gd d d e ZdS) )ListUnionN)add_end_docstringsis_torch_availableis_vision_availableloggingrequires_backends)PIPELINE_INIT_ARGSPipeline)Image) load_image)&MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMEScsxeZdZdZfddZddZdeeeededfdededfffd d Z d d Z dddZ ddZ Z S)ImageToImagePipelineao Image to Image pipeline using any `AutoModelForImageToImage`. This pipeline generates an image based on a previous image input. Example: ```python >>> from PIL import Image >>> import requests >>> from transformers import pipeline >>> upscaler = pipeline("image-to-image", model="caidas/swin2SR-classical-sr-x2-64") >>> img = Image.open(requests.get("http://images.cocodataset.org/val2017/000000039769.jpg", stream=True).raw) >>> img = img.resize((64, 64)) >>> upscaled_img = upscaler(img) >>> img.size (64, 64) >>> upscaled_img.size (144, 144) ``` This image to image pipeline can currently be loaded from [`pipeline`] using the following task identifier: `"image-to-image"`. See the list of available models on [huggingface.co/models](https://huggingface.co/models?filter=image-to-image). cs*tj|i|t|d|tdS)Nvision)super__init__r check_model_typer)selfargskwargs __class__[/var/www/html/ai/venv/lib/python3.10/site-packages/transformers/pipelines/image_to_image.pyrFs zImageToImagePipeline.__init__cKs>i}i}i}d|vr|d|d<d|vr|d|d<|||fS)Ntimeout head_maskr)rrpreprocess_paramspostprocess_paramsforward_paramsrrr_sanitize_parametersKs   z)ImageToImagePipeline._sanitize_parametersimagesz Image.Imagereturnc stj|fi|S)a Transform the image(s) passed as inputs. Args: images (`str`, `List[str]`, `PIL.Image` or `List[PIL.Image]`): The pipeline handles three types of images: - A string containing a http link pointing to an image - A string containing a local path to an image - An image loaded in PIL directly The pipeline accepts either a single image or a batch of images, which must then be passed as a string. Images in a batch must all be in the same format: all as http links, all as local paths, or all as PIL images. timeout (`float`, *optional*, defaults to None): The maximum time in seconds to wait for fetching images from the web. If None, no timeout is used and the call may block forever. Return: An image (Image.Image) or a list of images (List["Image.Image"]) containing result(s). If the input is a single image, the return will be also a single image, if the input is a list of several images, it will return a list of transformed images. )r__call__)rr"rrrrr$WszImageToImagePipeline.__call__cCs|jdi|}|S)Nr)model)r model_inputs model_outputsrrr_forwardsszImageToImagePipeline._forwardNcCs t||d}|j|gdd}|S)N)rpt)r"return_tensors)rimage_processor)rimagerinputsrrr preprocessws zImageToImagePipeline.preprocesscCsg}d|vr |j}|D]+}|jdd}tj |ddd}|d tj }| t|q t|dkrA|S|dS)Nreconstructionrr )source destinationgo@)keysr/datasqueezefloatcpuclamp_numpynpmoveaxisroundastypeuint8appendr fromarraylen)rr'r"outputsoutputrrr postprocess|s z ImageToImagePipeline.postprocess)N)__name__ __module__ __qualname____doc__rr!rstrrr$r(r.rD __classcell__rrrrr's   r)typingrrr9r:utilsrrrrr baser r PILr image_utilsrmodels.auto.modeling_autor get_loggerrEloggerrrrrrs