Weight-Activation Co-Adaptive Quantization for RT-DETR

This code is the supporting research code for the paper "Weight Activation Co Adaptive Quantization Method for RT-DETR", which implements the weight activation co adaptive quantization (WCAQ) framework for studying the post training quantization of real-time object detection model RT-DETR under low bit conditions. This framework combines group weight pseudo quantization, sample adaptive activation scale adjustment, operator output activation quantization, sensitive branch protection, and layer by layer reconstruction to alleviate the degradation of detection accuracy caused by joint quantization of weights and activations without the need for task level retraining. The code covers model quantization configuration, calibration, layer by layer reconstruction, and detection performance evaluation.

It supports conducting 8-bit, 6-bit, and 4-bit quantization experiments on the COCO 2017 dataset and can be used for paper method reproduction and related model quantization research. The current implementation uses pseudo quantization to simulate low bit numerical calculations, and some sensitive modules retain floating-point operations, which is not yet a fully networked pure integer inference implementation.