pip install -r requirements.txt
gives me this error

ERROR: torch-1.11.0+cu113-cp37-cp37m-linux_x86_64.whl is not a supported wheel on this platform.

Tested installation on the following OS.

Distributor ID: Ubuntu
Description: Ubuntu 23.04
Release: 23.04
Codename: lunar

Distributor ID: Ubuntu
Description: Ubuntu 20.04.6 LTS
Release: 20.04
Codename: focal

Hi authors,

Thanks for the great work! I am curious how long does it takes to train the model?

• Use RRDB in colorization model
• Train on 32x32 crops
• 1 channel input and 3 channel output

ERROR: torch-1.11.0+cu113-cp37-cp37m-linux_x86_64.whl is not a supported wheel on this platform.

We need script to easily update system if it does not match our requirements.

does this project convert only the images exists in dataset and downloaded images or can I use it to convert my own images?

This is an interesting work. but i got an error when I try to run the project by follow command
python run.py './src/config/baseline.py'
but I have download IMGUR5K dataset and put it under data floder. So waht should i do to generate training dataset from IMGUR5K?

Did you train the autoencoder model up to 500epoch?
How long does it take?

I wrote inference code based off config and training stylegan_adversarial.py but the results look nothing like what is shown in the repository, have I skipped any important step? Code and results attached below

import torch
import numpy as np
from PIL import Image
from pathlib import Path
from random import shuffle
from stylegan import StyleBased_Generator
from embedders import ContentResnet, StyleResnet
from draw import draw_word, img_to_tensor
from nlayer_discriminator import NLayerDiscriminator

from torchvision import transforms as T

def main():
    device = 'cuda:0' if torch.cuda.is_available() else 'cpu'

    weights_folder_name = 'Stylegan (pretrained on content)'
    weights_folder = f'models/{weights_folder_name}'

    model_G = StyleBased_Generator(dim_latent=512)
    model_G.load_state_dict(torch.load(f'{weights_folder}/model'))
    model_G.to(device)

    style_embedder = StyleResnet().to(device) 
    style_embedder.load_state_dict(torch.load(f'{weights_folder}/style_embedder'))

    content_embedder = ContentResnet().to(device)
    content_embedder.load_state_dict(torch.load(f'{weights_folder}/content_embedder'))

    model_G.eval()
    content_embedder.eval()
    style_embedder.eval()

    # Word 'dictionary'
    with open('br-utf8.txt', 'r', encoding='UTF-8') as f:
        lines = f.readlines()

    shuffle(lines)

    style_imgs = []

    # same as draw.img_to_tensor
    transform = T.Compose([
        T.ToTensor(),
        T.Resize((64, 192)),
    ])

    to_pil_image = T.ToPILImage()

    for img_path in Path('images').glob('*.png'):
        with Image.open(img_path) as im:
            img_style = transform(im.convert('RGB'))
            style_imgs.append(img_style)

    desired_content = []
    for i, word in enumerate(lines[:len(style_imgs)]):
        img = draw_word(word)

        img.save(f'results/sample_{i}.png')

        img_content = transform(img)
        desired_content.append(img_content)

    style_imgs = torch.from_numpy(np.array(style_imgs))
    desired_content = torch.from_numpy(np.array(desired_content))

    style_imgs = style_imgs.to(device)
    desired_content = desired_content.to(device)

    style_embeds = style_embedder(style_imgs)
    content_embeds = content_embedder(desired_content)

    preds = model_G(content_embeds, style_embeds)

    for i, pred in enumerate(preds):
        img = to_pil_image(pred)
        img.save(f'results/{i}.png')

if __name__ == '__main__':
    main()

when train the model ,there is a error:

RuntimeError: Error(s) in loading state_dict for DataParallel:
Missing key(s) in state_dict: "module.Transformation.GridGenerator.inv_delta_C", "module.Transformation.GridGenerator.P_hat".

When trying to build this tool, it didn't run, so is there an already built tool to use right away

Encountered an error when running prepare_dataset.py with the following command.

python prepare_dataset.py

mainly due to the following error.

TypeError: crop_minAreaRect() takes 6 positional arguments but 33 were given.

This has to do with the format of imageur5k_annotations_train.json where "bounding_box" data is stored in a string format.

This can be fixed by replacing *info['bounding_box'] with *eval(info['bounding_box']).

Hi, I'm finetuning this model to my problem, where i need to edit document text. However, even after finetuning (200 images, 20 epochs), the images generated by model continue to look handwritten, whereas I need them to resemble printed text, like my ground truth is. Is there a way to adapt this approach to generate proper (not handwritten or scene) text? Should I try training from scratch on my images?

Some generated images:

It should resemble the Arial font here (the background and the colors are pretty spot on though)

I am really interested in this amazing work. And currently I am looking for a code implementation to study.
Really looking forward to your code.🙂️

Traceback (most recent call last):
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/types.py", line 608, in convert
st = os.stat(rv)
FileNotFoundError: [Errno 2] No such file or directory: 'dataset_info'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "prepare_dataset.py", line 90, in
main() # pylint: disable=no-value-for-parameter
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 829, in call
return self.main(*args, **kwargs)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 781, in main
with self.make_context(prog_name, args, **extra) as ctx:
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 700, in make_context
self.parse_args(ctx, args)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1048, in parse_args
value, args = param.handle_parse_result(ctx, opts, args)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1623, in handle_parse_result
value = self.full_process_value(ctx, value)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1965, in full_process_value
return Parameter.full_process_value(self, ctx, value)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1592, in full_process_value
value = self.get_default(ctx)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1917, in get_default
return Parameter.get_default(self, ctx)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1534, in get_default
return self.type_cast_value(ctx, rv)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1568, in type_cast_value
return _convert(value, (self.nargs != 1) + bool(self.multiple))
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1565, in _convert
return self.type(value, self, ctx)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/types.py", line 46, in call
return self.convert(value, param, ctx)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/types.py", line 614, in convert
self.path_type, filename_to_ui(value)
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/_compat.py", line 474, in filename_to_ui
value = value.encode("utf-8", "surrogateescape").decode("utf-8", "replace")
AttributeError: 'PosixPath' object has no attribute 'encode'
(venv) [jorj@jorj-systemproductname text-deep-fake-main]$ cd /home/jorj/Загрузки/text-deep-fake-main/IMGUR5K-Handwriting-Dataset-main/
(venv) [jorj@jorj-systemproductname IMGUR5K-Handwriting-Dataset-main]$ python prepare_dataset.py
0it [00:00, ?it/s] 2023-07-07 18:57:47.034 | ERROR | main:main:84 - An error has been caught in function 'main', process 'MainProcess' (252331), thread 'MainThread' (140470161389376):
Traceback (most recent call last):

File "prepare_dataset.py", line 90, in
main() # pylint: disable=no-value-for-parameter
└

File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 829, in call
return self.main(*args, **kwargs)
│ │ │ └ {}
│ │ └ ()
│ └ <function BaseCommand.main at 0x7fc1c157a8c0>
└
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 782, in main
rv = self.invoke(ctx)
│ │ └ <click.core.Context object at 0x7fc1baaf79d0>
│ └ <function Command.invoke at 0x7fc1c150ab90>
└
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1066, in invoke
return ctx.invoke(self.callback, **ctx.params)
│ │ │ │ │ └ {'annotations_path': PosixPath('dataset_info'), 'save_path': PosixPath('cropped'), 'no_split': False, 'reduce': None}
│ │ │ │ └ <click.core.Context object at 0x7fc1baaf79d0>
│ │ │ └ <function main at 0x7fc1ba7d9e60>
│ │ └
│ └ <function Context.invoke at 0x7fc1c150b050>
└ <click.core.Context object at 0x7fc1baaf79d0>
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 610, in invoke
return callback(*args, **kwargs)
│ │ └ {'annotations_path': PosixPath('dataset_info'), 'save_path': PosixPath('cropped'), 'no_split': False, 'reduce': None}
│ └ ()
└ <function main at 0x7fc1ba7d9e60>

File "prepare_dataset.py", line 84, in main
img_cropped = crop_minAreaRect(img, *info['bounding_box'])
│ │ └ {'word': 'SIRIÜS', 'bounding_box': '[97.0, 1011.5, 103.0, 36.0, 4.5]'}
│ └ array([[[165, 210, 224],
│ [163, 210, 224],
│ [163, 210, 224],
│ ...,
│ [148, 200, 213],
│ [150...
└ <function crop_minAreaRect at 0x7fc1c156ecb0>

TypeError: crop_minAreaRect() takes 6 positional arguments but 33 were given
0it [00:00, ?it/s]
2023-07-07 18:57:47.039 | ERROR | click.core:invoke:610 - An error has been caught in function 'invoke', process 'MainProcess' (252331), thread 'MainThread' (140470161389376):
Traceback (most recent call last):

File "prepare_dataset.py", line 90, in
main() # pylint: disable=no-value-for-parameter
└

File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 829, in call
return self.main(*args, **kwargs)
│ │ │ └ {}
│ │ └ ()
│ └ <function BaseCommand.main at 0x7fc1c157a8c0>
└
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 782, in main
rv = self.invoke(ctx)
│ │ └ <click.core.Context object at 0x7fc1baaf79d0>
│ └ <function Command.invoke at 0x7fc1c150ab90>
└
File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 1066, in invoke
return ctx.invoke(self.callback, **ctx.params)
│ │ │ │ │ └ {'annotations_path': PosixPath('dataset_info'), 'save_path': PosixPath('cropped'), 'no_split': False, 'reduce': None}
│ │ │ │ └ <click.core.Context object at 0x7fc1baaf79d0>
│ │ │ └ <function main at 0x7fc1ba7d9e60>
│ │ └
│ └ <function Context.invoke at 0x7fc1c150b050>
└ <click.core.Context object at 0x7fc1baaf79d0>

File "/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/click/core.py", line 610, in invoke
return callback(*args, **kwargs)
│ │ └ {'annotations_path': PosixPath('dataset_info'), 'save_path': PosixPath('cropped'), 'no_split': False, 'reduce': None}
│ └ ()
└ <function main at 0x7fc1ba7d9e60>

File "prepare_dataset.py", line 85, in main
cv2.imwrite(str(output_path / f'{ann_id}.png'), img_cropped)
│ │ │ └ None
│ │ └ PosixPath('cropped/train')
│ └
└ <module 'cv2.cv2' from '/home/jorj/Загрузки/text-deep-fake-main/venv/lib/python3.7/site-packages/cv2/cv2.cpython-37m-x86_64-l...

cv2.error: OpenCV(4.1.2) /io/opencv/modules/imgcodecs/src/loadsave.cpp:715: error: (-215:Assertion failed) !_img.empty() in function 'imwrite'

How can I access to Yandex.disk of your project?
it needs a token and pass.