With the increase in ML applications, there is also an increase in the demand for quality data to train ML models. Oftentimes there is no or only limited training data readily available. In such cases, synthetic training data plays a vital role to train ML models. AMDC is capable of generating synthetic data for various computer vision applications such as classification and object detection models.
Synthetic Data for Object Detection and Classification
AMDC has built a pipeline that makes use of an open source graphical software to place 3D models into a scene and to render training images. The scene consists of several parameters that are modified each time when an image is rendered, thus simulating various real world scenarios such as sunlight, shadow, dust particles etc. The rendered images are saved along with information required for the training (ground truth information). The resulting dataset is directly used for training the AI models.
Training Data Generation Service
AMDC has developed a system to create 3D scenes of environments and place objects therein. Images of the objects can be rendered from any perspective and any distance with different terrain, weather, textures, and daylight conditions. Corresponding labels can be generated as well.
Based on a 3D-scene, more than 50.000 training images with labels can be generated in one day (24h) by a standard high performance PC. The system is also capable to provide data in the IR-spectrum.
Based on customer requirements we can provide a large amount of labeled images in short time. It is possible to mix the images with labeled photos to improve the robustness of the trained AI-system. If you have any questions, please contact email@example.com .