Hi, thanks for releasing the code.
In the paper, Algorithm 1 and Fig. 4 describe a two-stage diffusion framework:
- Stage 1: train DM1 to predict the K² / map-outline from environmental inputs.
- Stage 2: use the predicted K² / map-outline as a condition to generate the final radio map.
I found caculate_k.py, which computes the K² / outline maps offline, and the DPMK / DPMCARK / IRT4K configs seem to use these computed K² maps as conditions for the final diffusion model.
Could you please point me to the code/config/checkpoint for training the Stage-1 model that predicts the K² / outline map itself?
Thanks!
Hi, thanks for releasing the code.
In the paper, Algorithm 1 and Fig. 4 describe a two-stage diffusion framework:
I found
caculate_k.py, which computes the K² / outline maps offline, and theDPMK / DPMCARK / IRT4Kconfigs seem to use these computed K² maps as conditions for the final diffusion model.Could you please point me to the code/config/checkpoint for training the Stage-1 model that predicts the K² / outline map itself?
Thanks!