simplabel 0.0.2

Simple tool to manually label images in disctinct categories to build training datasets.

Simplabel

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 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

Command line tools

Pass the categories and image directory on the command line to start labelling. Use the on-screen buttons to select a label for the current image and advance to the next one. Number keys correspond to labels and can be used instead.

simplabel --categories dog cat bird --directory path/to/image/directory

Once you are done labelling, use the flow_to_directory tool to copy images to distinct directories by label

flow_to_directory --rawDirectory data/raw --outDirectory data/labeled

Python object

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()

Saved labels

The app saves a labeled.pkl file that contains a pickeled dictionary {image_name: label}. To import the dictionary, use the following sample code:

import pickle

with open("labeled.pkl","rb") as f:
    label_dict = pickle.load(f)

Move labeled images to discrete directories

This utility copies labeled images from the raw directory to discrete folders by label in the labelled directory using the dictionary created by simplabel.

from simplabel import utils

utils.flow_to_dict(rawDirectory, labelledDirectory)