How a Serverless AWS Lambda Container Segments and Straightens Card Photos Using AI

A developer has built an image segmentation pipeline on AWS Lambda that takes a crooked, background-filled photo of an AWS Builder Card and returns a clean, cropped, straightened version. The system uses two Lambda functions: one to classify whether the uploaded image contains a valid card, and a second called image-processor to isolate and clean it. The segmentation work is handled by the BiRefNet-General-Lite model, loaded via the rembg library and running on CPU through ONNX Runtime, with no PyTorch required. Memory management proved a key challenge, as the full BiRefNet-General model caused out-of-memory errors even on AWS Lambda's largest available configuration. The lighter Lite variant was ultimately adopted to stay within Lambda's memory limits, with costs and vCPU allocation tied directly to the memory size chosen.