voibit / euclid

Euclid object labeller for object detection training purposes in Machine learning frameworks (KITTI, YOLO)

euclid

Euclid object labeller for object detection training purposes based on Python. Tested on Linux, Windows, and Mac.

• Supports Kitti format
• Supports Yolo darknet format (Generates bounding boxes, as well as training list file)

Dynamic selection of format is now supported.

Optimised box selection using keyboard shortcuts.

Typical object labelling workflow using Euclid:

Create a folder containing the images

• Ensure images are of uniform (not too big) shape using a command for resize like below. (Linux)

Resize all jpg images to 256x256, rename to sz-256-.jpg

for file in *.jpg; do convert $file -resize 256x256 sz-256-$file; done

• $python euclid.py

• Select the folder containing the images

• Euclid will show the first image in the folder.

• Select the class ID, and start labelling. Once done for this image, move to the next image, till all imagea are done.

• Euclid also generates a supplementary file "train.txt", containing the class ID and full path of training file. This can be used in YOLO format training.

YOLO training and detection.

Refer below link for YOLO training and detection on Linux and Windows.

https://github.com/prabindh/darknet

Dependencies

Python 2.7 pip install pillow pip install image Python 3 Python 3 + Pillow on Ubuntu, do the below sudo apt-get install python-imaging-tk sudo apt-get install python3-pil.imagetk