What We Do
We present a service for creating huge amounts of synthetic images for object detection and segmentation tasks which you can use to train your deep neural networks on. 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. With our solution it is possible to avoid the need of collecting large amounts of hand annotated real-world data.
The experience and know-how of our team allows us to create a synthetic dataset of objects of your choice. The only information we need is the task of the model in its final stage.
After the successful receipt of the object of interest, we convert the input data and the actual generation process begins.
You will receive the dataset in-between 2-5 days. The time span depends on the complexity of the models tasks.
The dataset contains ground truth images, ground truth labels, pixel wise annotations, depth maps,
Delivery of dataset in 2-5 days.
Due the data is physical calculated, it couldn't be more accurate.
Multi channel output
RGB, pixel wise annotation, zDepth, wireframe, normals.
Full control on dataset specifications
- min max camera angle/position and rotation
- the amount of labels per image
- environment and light setup