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| author | Alphara <42233094+xAlpharax@users.noreply.github.com> | 2023-10-28 12:25:04 +0300 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2023-10-28 12:25:04 +0300 |
| commit | 071ee6bd004a4c17a444c5bdd48d7a28b0aff108 (patch) | |
| tree | d541eecc752d72bb1da834cf2ded40b8e9b15a70 | |
| parent | 011b3f325f5f931f5457f05c8cf13a10c8ec91d9 (diff) | |
Update README.md with better video gallery
| -rw-r--r-- | README.md | 8 |
1 files changed, 4 insertions, 4 deletions
@@ -2,7 +2,7 @@ Neural Style Transfer done from the CLI using a VGG backbone and presented as an MP4. -Weights can be downloaded from [here](https://files.catbox.moe/wcao20.pth). The downloaded file (renamed to `vgg_conv_weights.pth`) should be placed in `./weights/` and it will be ignored when pushing, as seen in `./.gitignore`. Update: Alternatively, if the `./weights/` directory is empty, `./neuralart.py` will automatically download publicly available VGG19 weights for the user. +Weights can be downloaded from [here](https://files.catbox.moe/wcao20.pth). The downloaded file (renamed to `vgg_conv_weights.pth`) should be placed in `./weights/` and it will be ignored when pushing, as seen in `./.gitignore`. **Update:** Alternatively, if the `./weights/` directory is empty, `./neuralart.py` will automatically download publicly available VGG19 weights for the user. More in depth information about Neural Style Transfer ( NST ) can be found in this great [paper](https://arxiv.org/abs/1705.04058). Make sure to check [Requirements](#requirements) and [Usage](#usage). @@ -58,16 +58,16 @@ Moreover, `./all.sh` is aware of the already rendered mp4 files and will skip st ### Output videos / images and temporary files -If, at any point, curious of the individual frames that comprise the generated `./content_in_style.mp4` check `./Output/` for PNG images with exactly that. Keep in mind that these files get removed and overwritten each time ./stylize.sh is called ( this is also why running multiple instances of `./stylize.sh` is advised against; if you need to batch/automate the process, try `./all.sh`) +If, at any point, curious of the individual frames that comprise the generated `./content_in_style.mp4` check `./Output/` for PNG images with exactly that. Keep in mind that these files get removed and overwritten each time ./stylize.sh is called ( this is also why running multiple instances of `./stylize.sh` is advised against; if you need to batch/automate the process, try `./all.sh` ) The `./images.npy` file contains raw numpy array data generated by `./neuralart.py` and is manipulated by `./renderer.py` to achieve the `./Output` directory of PNG images. Considering this workflow, `./clear_dir.sh` removes temporary files each time a new call to `./stylize.sh` is made. -## Results after running neural-art - <details> +<summary><h2>Results after running neural-art (Click on dropdown for video gallery)</h2></summary> + [//]: # (Bunnies in Monet) https://github.com/xAlpharax/neural-art/assets/42233094/0094a10b-e452-4284-b0d6-08df471d1848 |