Subtle changes within stylize.sh, neuralart.py and the README.md files.

Mostly QoS changes and better instructions and error handling.

Changes to be committed:
    modified:   README.md
    modified:   neuralart.py
    modified:   stylize.sh

3 files changed, 52 insertions, 11 deletions

diff --git a/README.md b/README.md
index 0a6e3a7..e8d3e6d 100644
--- a/README.md
+++ b/README.md
@@ -2,15 +2,47 @@
 
 Neural Style Transfer done from the CLI using a VGG backbone and presented as an MP4.
 
-Weights can be downloaded from [here](https://m1.afileditch.ch/ajjMsHrRhnikrrCiUXgY.pth). The downloaded file should be placed in `./weights/` and any file will be ignored from there when pushing, as seen in `./.gitignore`. Update: Alternatively, if the `./weights/` directory is empty, `./neuralart.py` will automatically download the aforementioned default weights.
+Weights can be downloaded from [here](https://m1.afileditch.ch/ajjMsHrRhnikrrCiUXgY.pth). The downloaded file should be placed in `./weights/` and any file will be ignored from there 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).
 
 ### Why use this in 2023 ?
 
-Because Style Transfer hasn't changed drastically in terms of actual results in the past years. I personally find a certain beauty in inputting a style and content image rather than a well curated prompt with a dozen of switches. Consider this repo as a quick ***just works*** solution that can run on either CPU or GPU effectively.
+Because Style Transfer hasn't changed drastically in terms of actual results in the past years. I personally find a certain beauty in inputting a style and content image rather than a well curated prompt with a dozen of switches. Consider this repo as a quick and simple ***just works*** solution that can run on both CPU and GPU effectively.
+
+I developed this tool as a means to obtain fancy images and visuals for me and my friends. It somehow grew into something bigger that is actually usable, so much so that I got to integrate it in a workflow in conjunction with [Stable Diffusion](https://github.com/CompVis/stable-diffusion) (see also [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui)).
+
+### Requirements
+
+Clone the repository:
+
+```bash
+git clone https://github.com/xAlpharax/neural-art
+```
+
+Create a virtual environment to separate the required packages from system-wide packages:
+
+```bash
+virtualenv path/to/neural-art
+
+source path/to/neural-art/bin/activate
+```
+
+! When you're finished with the environment:
+
+```bash
+# deactivate
+```
+
+All the required packages are listed in `./requirements.txt` as per python etiquette:
+
+```bash
+pip install -r requirements.txt
+```
 
 ## Usage
 
-The script sits comfortably in `./stylize.sh` so run it (strictly from the project directory):
+The main script sits comfortably in `./stylize.sh` so run it from the project's directory:
 
 ```bash
 ./stylize.sh path/to/style_image path/to/content_image
@@ -22,13 +54,20 @@ A helper script is also available to run `./stylize.sh` for each distinct pair o
 ./all.sh
 ```
 
-If, at any point, curious of the individual frames that comprise the generated `./content_in_style.mp4` check `./Output/`
-There's also a (redundant) `./images.npy` file that contains raw array data. `./clear_dir.sh` removes redundant files each time they're no longer needed.
+Moreover, `./all.sh` is aware of the a;ready rendered mp4 files in the current working directory and will skip stylizing the combinations that are already present.
 
-### Requirements
+### Output videos/images and temporary files
 
-All requirements are specified in `./requirements.txt` as per python etiquette:
+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 the script in `./stylize.sh` is advised against; if you need something batched/automated, try `./all.sh`)
 
-```bash
-pip install -r requirements.txt
-```
+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.
+
+## Contribuiting
+
+Any sort of help, especially regarding the QoS of the project, is appreciated. Feel free to open an issue in the **Issues** tab and discuss the possible changes there. As of now, *neural-art* would be in great need of a clean and friendly arguments handler (i.e. like the ones the `argparse` python package provides) in order to provide a cleaner interface for working with `./neuralart.py` and/or `./stylize.sh`.
+
+Thank you.
+
+Happy neural-art-ing !
diff --git a/neuralart.py b/neuralart.py
index d556d2f..7aab03e 100644
--- a/neuralart.py
+++ b/neuralart.py
@@ -25,7 +25,7 @@ from PIL import Image
 ### path definitions
 
 model_path = 'weights/vgg_conv_weights.pth'
-image_path = '' # root (neural-art) directory
+image_path = '' # by default use neural-art as relative dir
 
 ### userland testing for multiple instances, a big nono currently
 
diff --git a/stylize.sh b/stylize.sh
index 939ec06..b83517b 100755
--- a/stylize.sh
+++ b/stylize.sh
@@ -2,6 +2,8 @@
 
 set -e ### exit the script if any part of it fails
 
+cd "$(dirname "${BASH_SOURCE[0]}")"
+
 cwd=$(pwd | sed -r 's%.*/%%g')
 if [ $cwd != "neural-art" ] ; then
     echo "You must be in the 'neural-art' directory when you run this"