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# file-tagger
*file-tagger* is a tool for bulk-tagging files.
It uses the tagging system [TMSU](https://tmsu.org/) as backend.
For images, it uses tensorflow and ResNet50 to predict keywords automatically,
and comes with a GUI to fastly preview the image and add new tags.
## Requirements
- [TMSU](https://tmsu.org/)
- OpenCV (optional)
- Numpy (optional)
- tkinter (optional)
- tensorflow (optional)
## Usage
```
usage: file-tagger.py [-h] [-b [BASE]] [-f [FILE_DIR]] [-g [GUI]] [--predict-images [PREDICT_IMAGES]] [--predict-images-top [PREDICT_IMAGES_TOP]]
[--gui-tag [GUI_TAG]] [--open-system [OPEN_SYSTEM]] [-i [INDEX]] [-v]
Tag multiple files using TMSU.
options:
-h, --help show this help message and exit
-b [BASE], --base [BASE]
Base directory with database (default: .)
-f [FILE_DIR], --file-dir [FILE_DIR]
File directory for walking (default: .)
-g [GUI], --gui [GUI]
Show main GUI (default: False)
--predict-images [PREDICT_IMAGES]
Use prediction for image tagging (default: False)
--predict-images-top [PREDICT_IMAGES_TOP]
Defines how many top prediction keywords should be used (default: 10)
--gui-tag [GUI_TAG] Show GUI for tagging (default: False)
--open-system [OPEN_SYSTEM]
Open all files with system default (default: False)
-i [INDEX], --index [INDEX]
Start tagging at the given file index (default: 0)
-v, --verbose Verbosity level
```
## Getting started
1. Install requirements `pip install tensorflow numpy tkinter opencv-python`
2. Run the main script given the base directory `python file-tagger.py --base <base> --gui --gui-tag --predict-images`
3. Consecutively tag the files by entering comma-separated tags to the entry and pressing `Next`
4. If you want to take a break from tagging, remember the current index and give it as start index next time. Mind that adding/removing files will invalidate the index.
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