Synthetic images are computer generated images which represent the real world
By simulating the data in a virtual environment, it is possible to influence every parameter that has an impact on the images. All possible light scenarios, as well as camera positions, environments and actions can be displayed.
Synthetic datasets can therefore be used for every computer vision task from image classification over instance segmentation or anomaly detection.
More data to establish new technologies
Due to the lack of affordable, high quality data for custom object detection and segmentation tasks there are a lot of fields being unexplored.
Our solution helps to generate meaningful synthetic images for training of neural networks in a short amount of time containing pixel wise annotation with a high, stable quality of annotations throughout the whole dataset.
The game changer
Our data generator helps you overcome the problem of missing or non-existent image data by allowing you to create large scale, annotated datasets.
The data can be used for any kind of computer vision tasks such as object detection, image classification and instance segmentation.
Thanks to scalable computing, the data can be created in the shortest possible time. You can expect large scale datasets within days.
Since the data and annotations are digitally simulated, no human error or biases can occur.
Compared to conventional image data collecting methods, synthetic data is usually half the price.