Amazon SageMaker deploys Qwen-Image-Edit-2509 and Rekognition to augment industrial-safety datasets with synthetic people
Amazon demonstrates an end-to-end pipeline on SageMaker AI that uses the diffusion model Qwen-Image-Edit-2509 (hosted on an ml.g5.12xlarge with NVIDIA A10G GPUs) to insert photo-realistic synthetic people into real equipment images, then generates bounding-box annotations automatically via Amazon Rekognition DetectLabels; experiments reportedly showed up to 160% improvement in person-detection mAP50 without manual annotation. The workflow edits real scenes in-place to preserve background fidelity, deduplicates Rekognition boxes with NMS, and converts labels to YOLO format for training.