Anno-Mage: A Semi Automatic Image Annotation Tool

Semi Automatic Image Annotation Toolbox with RetinaNet as the suggesting algorithm. The toolbox suggests 80 class objects from the MS COCO dataset using a pretrained RetinaNet model.

Installation

1. Clone this repository.

2. In the repository, execute pip install -r requirements.txt. Note that due to inconsistencies with how tensorflow should be installed, this package does not define a dependency on tensorflow as it will try to install that (which at least on Arch Linux results in an incorrect installation). Please make sure tensorflow is installed as per your systems requirements. Also, make sure Keras 2.1.3 or higher and OpenCV 3.x is installed.

3. Download the pretrained weights and save it in /snapshots.

Dependencies

1. Tensorflow >= 1.7.0

2. OpenCV = 3.x

3. Keras >= 2.1.3

For, Python >= 3.5

Instructions

1. Select the COCO object classes for which you need suggestions from the drop-down menu and add them.

2. When annotating manually, select the object class from the List and while keep it selected, select the BBox.

3. The final annotations can be found in the file annotations.csv in ./annotations/

Usage

python main.py

Tested on:

1. Windows 10

2. Linux 16.04

3. macOS High Sierra

Acknowledgments

1. Meditab Software Inc.

2. Keras implementation of RetinaNet object detection

3. Computer Vision Group, L.D. College of Engineering