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from __future__ import annotations |
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from concurrent.futures import ThreadPoolExecutor |
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from gradio.components.gallery import ( |
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GalleryImageType, |
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CaptionedGalleryImageType, |
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GalleryImage, |
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GalleryData, |
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) |
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from pathlib import Path |
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from urllib.parse import urlparse |
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import gradio |
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import numpy as np |
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import PIL.Image |
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from gradio_client.utils import is_http_url_like |
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from gradio import processing_utils, utils, wasm_utils |
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from gradio.data_classes import FileData |
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class Gallery(gradio.Gallery): |
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def postprocess( |
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self, |
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value: list[GalleryImageType | CaptionedGalleryImageType] | None, |
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) -> GalleryData: |
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""" |
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This is a patched version of the original function, wherein the format for PIL is computed based on the data type: |
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format = "png" if img.mode == "I;16" else "webp" |
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""" |
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if value is None: |
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return GalleryData(root=[]) |
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output = [] |
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def _save(img): |
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url = None |
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caption = None |
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orig_name = None |
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if isinstance(img, (tuple, list)): |
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img, caption = img |
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if isinstance(img, np.ndarray): |
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file = processing_utils.save_img_array_to_cache( |
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img, cache_dir=self.GRADIO_CACHE, format=self.format |
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) |
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file_path = str(utils.abspath(file)) |
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elif isinstance(img, PIL.Image.Image): |
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format = "png" |
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file = processing_utils.save_pil_to_cache( |
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img, cache_dir=self.GRADIO_CACHE, format=format |
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) |
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file_path = str(utils.abspath(file)) |
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elif isinstance(img, str): |
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file_path = img |
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if is_http_url_like(img): |
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url = img |
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orig_name = Path(urlparse(img).path).name |
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else: |
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url = None |
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orig_name = Path(img).name |
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elif isinstance(img, Path): |
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file_path = str(img) |
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orig_name = img.name |
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else: |
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raise ValueError(f"Cannot process type as image: {type(img)}") |
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return GalleryImage( |
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image=FileData(path=file_path, url=url, orig_name=orig_name), |
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caption=caption, |
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) |
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if wasm_utils.IS_WASM: |
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for img in value: |
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output.append(_save(img)) |
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else: |
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with ThreadPoolExecutor() as executor: |
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for o in executor.map(_save, value): |
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output.append(o) |
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return GalleryData(root=output) |
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