magni takes a url and upscales all the images inside and returns a simple html page with the images embedded.

usage: magni.py [-h] [--url URL] [--method METHOD] [--port PORT]

options:
  -h, --help            show this help message and exit
  --url URL, -u URL     the url to the page containing the images
  --method METHOD, -m METHOD
                        the method to use. either fsrcnn or espcn
  --port PORT, -p PORT  the port to serve the images over

poetry install

poetry shell && HTTPS_PROXY=socks5h://127.0.0.1:9094 ./magni.py --url https://chapmanganato.com/manga-dt980702/chapter-184

you can obviously use poetry run as well:

HTTPS_PROXY=socks5h://127.0.0.1:9094 poetry run ./magni.py --url https://chapmanganato.com/manga-dt980702/chapter-184

docker build -t magni:latest --load .

docker run -p 8086:8086 \
  -e HTTPS_PROXY=socks5h://192.168.1.100:9050 \
  -e MAGNI_MODEL_PATH=/opt/magni_models \
  -e MAGNI_IMAGE_PATH=/opt/magni_images \
  -v ./models:/opts/magni_models \
  magni:latest --url https://chapmanganato.com/manga-dt980702/chapter-184

magni recognizes three environment variables:

You can also specify a socks5 proxy here since magni uses pysocks to make the connections.
If the env vars are not defined or are empty magni will not use any proxy.

Path to the directory where magni will store the models.
If the env var is not defined or is empty, magni will use ./models as a default value.

Path to the directory where magni will store the upscaled images.
If the env var is not defined or is empty magni will use ./images as a default value.

The user agent magni will use the download the images.
If the env var is not defined or is empty, magni will use a default user agent you can see below:

Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36

• currently the models we are using are not as effective. I should either fine ones that are specifically trained on greyscale images or just train some myself.