path: root/README.md

# magni
magni takes a url and upscales all the images inside and returns a simple html page with the images embedded.</br>

```sh
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
```

## Install and Run

### Install
```sh
poetry install
```

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

### Docker

#### Build
```sh
docker build -t magni:latest --load .
```

#### Run
```sh
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
```

## Env Vars
magni recognizes three environment variables:</br>

### HTTP_PROXY/HTTPS_PROXY
You can also specify a socks5 proxy here since magni uses `pysocks` to make the connections.</br>
If the env vars are not defined or are empty magni will not use any proxy.</br>

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

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

### MAGNI_USER_AGENT
The user agent magni will use the download the images.</br>
If the env var is not defined or is empty, magni will use a default user agent you can see below:</br>
```
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36
```

## TODO
* 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.</br>