We decided to create a tool for generation of artificial marked images (in the form of bitmasks and bounding boxes), and the final result would be used to enrich the dataset for training deep convolutional architectures.
With the help of the synthetic data generator we managed to save much time and money comparing to the manual dataset collection and creation.
- Article. Synthetic data generator. Neural network training for industrial defectoscopy