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#!/usr/bin/env python
from __future__ import annotations
import argparse
import functools
import io
import os
import pathlib
import tarfile
import gradio as gr
import numpy as np
import PIL.Image
from huggingface_hub import hf_hub_download
TITLE = 'TADNE (This Anime Does Not Exist) Image Viewer'
DESCRIPTION = '''The original TADNE site is https://thisanimedoesnotexist.ai/.
You can view images generated by the TADNE model with seed 0-99999.
The original images are 512x512 in size, but they are resized to 128x128 here.
Expected execution time on Hugging Face Spaces: 4s
Related Apps:
- [TADNE](https://huggingface.co/spaces/hysts/TADNE)
- [TADNE Image Viewer](https://huggingface.co/spaces/hysts/TADNE-image-viewer)
- [TADNE Image Selector](https://huggingface.co/spaces/hysts/TADNE-image-selector)
- [TADNE Interpolation](https://huggingface.co/spaces/hysts/TADNE-interpolation)
- [TADNE Image Search with DeepDanbooru](https://huggingface.co/spaces/hysts/TADNE-image-search-with-DeepDanbooru)
'''
ARTICLE = '<center><img src="https://visitor-badge.glitch.me/badge?page_id=hysts.tadne-image-viewer" alt="visitor badge"/></center>'
TOKEN = os.environ['TOKEN']
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument('--theme', type=str)
parser.add_argument('--live', action='store_true')
parser.add_argument('--share', action='store_true')
parser.add_argument('--port', type=int)
parser.add_argument('--disable-queue',
dest='enable_queue',
action='store_false')
parser.add_argument('--allow-flagging', type=str, default='never')
return parser.parse_args()
def download_image_tarball(size: int, dirname: str) -> pathlib.Path:
path = hf_hub_download('hysts/TADNE-sample-images',
f'{size}/{dirname}.tar',
repo_type='dataset',
use_auth_token=TOKEN)
return path
def run(start_seed: int, nrows: int, ncols: int, image_size: int,
min_seed: int, max_seed: int, dirname: str,
tarball_path: pathlib.Path) -> np.ndarray:
start_seed = int(start_seed)
num = nrows * ncols
images = []
dummy = np.ones((image_size, image_size, 3), dtype=np.uint8) * 255
with tarfile.TarFile(tarball_path) as tar_file:
for seed in range(start_seed, start_seed + num):
if not min_seed <= seed <= max_seed:
images.append(dummy)
continue
member = tar_file.getmember(f'{dirname}/{seed:07d}.jpg')
with tar_file.extractfile(member) as f:
data = io.BytesIO(f.read())
image = PIL.Image.open(data)
image = np.asarray(image)
images.append(image)
res = np.asarray(images).reshape(nrows, ncols, image_size, image_size,
3).transpose(0, 2, 1, 3, 4).reshape(
nrows * image_size,
ncols * image_size, 3)
return res
def main():
args = parse_args()
image_size = 128
min_seed = 0
max_seed = 99999
dirname = '0-99999'
tarball_path = download_image_tarball(image_size, dirname)
func = functools.partial(run,
image_size=image_size,
min_seed=min_seed,
max_seed=max_seed,
dirname=dirname,
tarball_path=tarball_path)
func = functools.update_wrapper(func, run)
gr.Interface(
func,
[
gr.inputs.Number(default=0, label='Start Seed'),
gr.inputs.Slider(1, 10, step=1, default=2, label='Number of Rows'),
gr.inputs.Slider(
1, 10, step=1, default=5, label='Number of Columns'),
],
gr.outputs.Image(type='numpy', label='Output'),
title=TITLE,
description=DESCRIPTION,
article=ARTICLE,
theme=args.theme,
allow_flagging=args.allow_flagging,
live=args.live,
).launch(
enable_queue=args.enable_queue,
server_port=args.port,
share=args.share,
)
if __name__ == '__main__':
main()
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