Spaces:
Running
Running
| #!/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() | |