A tool for labeling bounding boxes on images to be used for ML training.
- Python 3.6
- In a terminal, run
pip install git+https://github.com/robert-clayton/ILYA
cd
into desired directory- Have images in subfolders within
Images
- Run app with
ilya
orpython -m ilya
- Select the folder you want to label images for
- Select an image
- Click and drag a box around the desired area
- Configure label using the popup
- Repeat until finished with image
- Labels are stored in the
data.csv
file in the current working directory
Taking a cue from Google's Open Images Dataset V4, boxes are saved in CSV format with the following columns:
- ImageID: String - The image this box belongs to as a relative path inside
Images
- Source: String - How the box was made. Everything produced by
label-maker
will bexclick
- LabelName: String - What class this box is represents. Set the class list in
labels.txt
- Confidence: Float - Dummy value, always 1.0
- XMin, XMax, YMin, YMax: Float - Box coordinates, normalized to the image as [0.0 ... 1.0]
- IsOccluded: Bool - Whether the object is occluding by another object
- IsTruncated: Bool - Whether the object is a part of the LabelName object
- IsGroupOf: Bool - Whether the object is a group of the LabelName object
- IsDepiction: Bool - Whether the object is a depiction of the LabelName object
- IsInside: Bool - Whether the object is the inside of the LabelName object