The Synthetic Image Generation Modeling API (SIGMA) is a microservice automation framework that provides the infrastructure for easy consumption of pre-trained synthetic image generation models, facilitating the integration of image-generation tools into third-party applications by abstracting the scalability and authorization needs of model inference.
Synthetic Image Generation Modeling is a technique used in computer vision to create large quantities of synthetic images that are similar to real ones but are generated by computer algorithms rather than captured by cameras. Generations can be useful in many applications where real images are scarce or difficult to obtain, such as training machine learning models or testing computer vision algorithms.
SIGMA provides a microservice infrastructure that serves pre-trained generative adversarial models. SIGMA takes care of scaling and distributing the requests to the appropriate backends, using the pre-trained GAN models to generate the requested images. The project is designed to be flexible, scalable, and easy to use, making it an ideal choice for engineers who want to incorporate synthetic images into their projects without training their own GANs or setting up their backend infrastructure.
Local Installation
- Build Docker images using Minikube's Docker daemon.
eval $(minikube docker-env) \
&& source scripts/build.sh \
|| eval $(minikube docker-env -u)- Install local Helm charts (review
deploy/values.yaml).
helm install sigma deploy/- Port forward the gateway service for API requests.
kubectl port-forward svc/sigma-gateway-service 8000:8000You may now test your connection with SIGMA at localhost:8000/ping
Cleanup
helm uninstall sigma