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