The colab works perfectly fine but when I try to run the code locally, the final result is always a black image.

Everything seems to be working as intended. The face, contextual, noise and etc all show up correctly and begin to process. You can even visualize this data on tensorboard. However after a few steps -- it's random.. sometime 10 steps sometimes 20 steps .. all the data gets changed to "nan" and as a result the output goes black.

Not sure what is going wrong. Any help? Happens the same with any image and any model/checkpoint. Any help would be greatly appreciated. @roxanneluo

Thanks' very much for this code release.

I get these errors running the Colab notebook at the end.

`FileNotFoundError Traceback (most recent call last) in () 19 results_dir="results/" 20 )) ---> 21 main(args)

5 frames /usr/local/lib/python3.7/dist-packages/torch/serialization.py in init(self, name, mode) 209 class _open_file(_opener): 210 def init(self, name, mode): --> 211 super(_open_file, self).init(open(name, mode)) 212 213 def exit(self, *args):

FileNotFoundError: [Errno 2] No such file or directory: 'checkpoint/encoder/checkpoint_b.pt'`

Hi, There's a problem on "Download models". with access

Permission denied: https://drive.google.com/uc?id=1hWc2JLM58_PkwfLG23Q5IH3Ysj2Mo1nr Maybe you need to change permission over 'Anyone with the link'?

I've created my own copy of the colab project and have managed to successfully implement it up until the final stage. I get this error when running the program using the sample image of Lincoln:

`/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. "See the documentation of nn.Upsample for details.".format(mode)

python test.py /content/Time-Travel-Rephotography/results/Abraham Lincoln_01/input_sibling /content/Time-Travel-Rephotography/results/Abraham Lincoln_01/skin_mask/face_parsing

0it [00:00, ?it/s]

error Traceback (most recent call last)

in () 19 results_dir="results/" 20 )) ---> 21 main(args)

2 frames

/content/Time-Travel-Rephotography/tools/match_histogram.py in main(args) 144 145 mask_A = cv2.resize(cv2.imread(args.ref_mask, 0), A.shape[:2][::-1], --> 146 interpolation=cv2.INTER_NEAREST) > 0 if args.ref_mask else None 147 mask_B = cv2.resize(cv2.imread(args.src_mask, 0), B.shape[:2][::-1], 148 interpolation=cv2.INTER_NEAREST) > 0 if args.src_mask else None

error: OpenCV(4.1.2) /io/opencv/modules/imgproc/src/resize.cpp:3720: error: (-215:Assertion failed) !ssize.empty() in function 'resize''

Hi

First and foremost, thank you for making this awesome project public for us to play with, i greatly appreciate it.

So I am running this project locally on an Nvidia ampere card using CUDA 11.3.

Everything seems to work, but 9 out of 10 Pictures produce unstable optimization runs.

Also some pictures need multiple runs, or they crash. So it is a big hit or miss, if a picture will process.

By crash I mean the optimization loss values all become "nan". Example: Optimizing 64x64 face: nan; eye: nan; contextual: nan; color_transfer: nan; noise: nan: 100%| 750/750 [08:49<00:00, 1.42it/s]

As you can see in the above picture, the optimizing runs for a while, then the loss values turn into "nan's".

What can I do to troubleshoot this?

My environment: python 3.8.5 pytorch: 1.10.1 py3.8_cuda11.3_cudnn8_0 torchvision: 0.11.2 py38_cu113 cudatoolkit: 11.3.1

It would be great to provide a Docker file so people can run this code easily without having to install all of the AI frameworks that were used for training the model.

Greetings, when trying to download models, the Colab swears at all links that there is no access and it would be better to change the file access parameters.. How to solve this problem?

I connect successfully in Colab and run the first two actions, but on the third (download models) an error occurs which has been persistent for the past couple of weeks, making the demo of no use. Is there a way around this?

When i try to play Download models thing i get error.

If the script above fails, which is largely due to exceeding download quota, try run the script below.

!./scripts/download_checkpoints.sh

it doesn't work too..

I've just uploaded the missing files and integrated them to the colab project so that it is no longer necessary to download each file manually and upload them one by one, here is the project link: https://colab.research.google.com/drive/1j2_gdzgyW-VapI4GTG48DAxgeYhJUdgb

Sadly, when I try to execute the last step I get this error:

https://user-images.githubusercontent.com/115443146/203861085-8a90d6a5-5ca1-489d-b190-c48abfe9a4b7.mp4

I hope there is a solution to this problem, I love this project, it would help me a lot in restoring old photos of my relatives.

Hi, i'm tryna to use the the colab demo but when i arrive at the "Run" part i get this error:

ModuleNotFoundError Traceback (most recent call last)

in 3 4 from argparse import Namespace ----> 5 from projector import ( 6 ProjectorArguments, 7 main,

ModuleNotFoundError: No module named 'projector'

### Are there solutions to make the code work? These are the errors that made the program not work:

The autoreload extension is already loaded. To reload it, use: %reload_ext autoreload ------------ Parameters ------------- camera_lr: 0.01 ckpt: checkpoint/stylegan2-ffhq-config-f.pt coarse_min: 32 color_transfer: 10000000000.0 contextual: 0.1 cx_layers: ['relu3_4', 'relu2_2', 'relu1_2'] e4e_ckpt: checkpoint/e4e_ffhq_encode.pt e4e_size: 256 encoder_ckpt: checkpoint/encoder/checkpoint_b.pt encoder_name: b encoder_size: 256 eye: 0.1 gaussian: 0.75 generator_size: 1024 init_latent: None input: dataset/أنا1_01.png log_dir: log/ log_freq: 10 log_visual_freq: 1000 lr: 0.1 mix_layer_range: [10, 18] noise_ramp: 0.75 noise_regularize: 50000.0 noise_strength: 0.0 rand_seed: None recon_size: 256 results_dir: results/ spectral_sensitivity: b vgg: 1 vggface: 0.3 wplus_step: [250, 750]

b-G0.75-init(10,18)-s256-vgg1-vggface0.3-eye0.1-color1.0e+10-cx0.1(relu3_4,relu2_2,relu1_2)-NR5.0e+04-lr0.1_0.01-c32-wp(250,750)

FileNotFoundError Traceback (most recent call last) in () 19 results_dir="results/" 20 )) ---> 21 main(args)

5 frames /content/Time-Travel-Rephotography/projector.py in main(args) 113 # initialize 114 with torch.no_grad(): --> 115 init = Initializer(args).to(device) 116 latent_init = init(imgs_orig) 117

/content/Time-Travel-Rephotography/tools/initialize.py in init(self, args) 114 115 assert args.encoder_size is not None --> 116 self.color_encoder = create_color_encoder(args) 117 self.color_encoder.eval() 118 self.color_encoder_size = args.encoder_size

/content/Time-Travel-Rephotography/tools/initialize.py in create_color_encoder(args) 73 def create_color_encoder(args: Namespace): 74 encoder = Encoder(1, args.encoder_size, 512) ---> 75 ckpt = torch.load(args.encoder_ckpt) 76 encoder.load_state_dict(ckpt["model"]) 77 return encoder

/usr/local/lib/python3.7/dist-packages/torch/serialization.py in load(f, map_location, pickle_module, **pickle_load_args) 592 pickle_load_args['encoding'] = 'utf-8' 593 --> 594 with _open_file_like(f, 'rb') as opened_file: 595 if _is_zipfile(opened_file): 596 # The zipfile reader is going to advance the current file position.

/usr/local/lib/python3.7/dist-packages/torch/serialization.py in _open_file_like(name_or_buffer, mode) 228 def _open_file_like(name_or_buffer, mode): 229 if _is_path(name_or_buffer): --> 230 return _open_file(name_or_buffer, mode) 231 else: 232 if 'w' in mode:

/usr/local/lib/python3.7/dist-packages/torch/serialization.py in init(self, name, mode) 209 class _open_file(_opener): 210 def init(self, name, mode): --> 211 super(_open_file, self).init(open(name, mode)) 212 213 def exit(self, *args):

FileNotFoundError: [Errno 2] No such file or directory: 'checkpoint/encoder/checkpoint_b.pt'