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https://github.com/hlgirard/Simplabel
Simple tool to manually label images in disctinct categories.
https://github.com/hlgirard/Simplabel
gui labeling-tool python training-dataset
Last synced: 8 days ago
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Simple tool to manually label images in disctinct categories.
- Host: GitHub
- URL: https://github.com/hlgirard/Simplabel
- Owner: hlgirard
- License: gpl-3.0
- Created: 2019-01-24T19:48:47.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2021-01-17T16:54:16.000Z (almost 4 years ago)
- Last Synced: 2024-09-20T01:07:13.124Z (about 2 months ago)
- Topics: gui, labeling-tool, python, training-dataset
- Language: Python
- Homepage:
- Size: 15.5 MB
- Stars: 4
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Simplabel
[](https://pypi.org/project/simplabel/)
[](https://travis-ci.com/hlgirard/Simplabel/branches)
[](https://github.com/hlgirard/Simplabel/blob/master/LICENSE)
Graphical tool to manually label images in distinct categories to build training datasets.
Simply pass a list of categories, a directory containing images and start labelling.
Supports multiple users, reconciliation and keyboard bindings to label even faster!
## Installation
### Install with pip
Simplabel is on PyPI so it can be installed with pip
```
pip install simplabel
```
### Install from source
Clone the repository to your computer
```
git clone https://github.com/hlgirard/Simplabel.git
```
and install with pip
```
cd Simplabel
pip install .
```
## Usage
### Quick start
Simplabel can be started from the command line without any argument:
```
simplabel
```
You will be prompted to select a directory containing images to label. Add labels with the '+' button and start labeling. Number keys correspond to labels and can be used instead.
The target directory and/or labels can also be passed directly from the command line:
```
simplabel --labels dog cat bird --directory path/to/image/directory
```
After the first use, labels are stored in `labels.json` and the `--labels` argument is ignored.
### Command line arguments
- `-d, --directory ` sets the directory to search for images and save labels to. Defaults to the current working directory.
- `-l, --labels ` sets the categories for the labelling task. Only passed on the first use in a given directory.
- `-u, --user ` sets the username. Defaults to the OS login name if none is passed.
- `-r, --redundant` does not display other labelers selections for independent labelling. Reconciliation and Make Master are unavailable in this mode.
- `-v, --verbose` increases the verbosity level.
- `--remove-label ` tries to safely remove a label from the list saved in `labels.json` (must also pass `-d`)
- `--reset-lock` overrides the lock preventing the same username from being used multiple times simultaneously.
- `--delete-all` removes all files created by simplabel in the directory (must also pass `-d`)
### Multiuser
The app relies on the filesystem to save each user's selection and display other user's selections. It works best if the working directory is on a shared drive or in a synced folder (Dropbox, Onedrive...). The Reconcile workflow allows any user to see and resolve conflicts. The Make Master option can be used to create and save a master dictionary - `labeled_master.json` - containing all labeled images (after reconciliation).
### Import saved labels
The app saves a `labeled_.json` file that contains a jsonified dictionary {image_name: label}. To import the dictionary, use the following sample code:
```python
import json
with open("labeled_user1.json","rb") as f:
label_dict = json.load(f)
```
## Advanced usage
### Utilities
Once you are done labelling, use the flow_to_directory tool to copy images to distinct directories by label
```
flow_to_directory --input-directory data/labeled --output-directory data/sorted
```
### Python object
The Tkinter app can also be started from a python environment
```python
from simplabel import ImageClassifier
import tkinter as tk
root = tk.Tk()
directory = "data/raw"
categories = ['dog', 'cat', 'bird']
MyApp = ImageClassifier(root, directory, categories)
tk.mainloop()
```
## License
This project is licensed under the GPLv3 License - see the [LICENSE.md](LICENSE.md) file for details.
## Acknowledgements
Testing of tkinter GUI is based on ivan_pozdeev's answer at Stackoverflow:
https://stackoverflow.com/questions/4083796/how-do-i-run-unittest-on-a-tkinter-app