No project description provided
Project description
TilesetParser
find single tile image in folder full of tilesets. It's very common that many tilesets are unorganized and contains unrecognaizable names. With TileParser you can take one tile (for example screenshot from web) and find whitch tileset contains that tile. To parse large amount of files TilesetParser uses AI (openCV)
Instalation
pip install TilesetParser
How to use?
tilesetparser /path/to/source/image.bmp /path/to/folder_with_tilesets
After parsing every file, preview window will appear. You can browse tilesets that program found similar to the source tile.
Program takes a few arguments:
Algorithms
By default TilesetParser calculates historgrams for input tile and every tile in tileset. You can use SSIM algorithm, whitch gives far more accurate results, but takes a bit more time.
positional arguments:
- source_image_path
Path to single source tile you need to find
- tiles_folder
Path to tileset folder you want to parse
options:
- -h, --help
Show help message and exit
- -s, --size
Size of a tile (default: 32)
- -q, --similarity
Similarity level for openCV (default: 0.8)
- -e, --extension
Extension of the files (default: bmp)
- -t, --tiles_per_tileset
How many tiles are in single tileset (default: 12)
- -d, --ssim_algorithm
Use SSIM algorithm (default: false)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for TilesetParser-1.0.5.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | fdf26b43edae448702b6e2a28bf94770ba17e406aa21fa9cc5f33c744b3db433 |
|
MD5 | db7bb47c76000c202995b56e5cb0f339 |
|
BLAKE2b-256 | 6ac7e5d54aa4d8b4b0f15643edba9ed7231fc3c8d200a6b384b5378cd9545175 |