9 fps of decoupled_solo_light_dcn_release_r50_fpn_8gpu_3 on GTX 1080 Ti

[Harut0726]

I trained decoupled_solo_light_dcn_release_r50_fpn_8gpu_3x.py on my own data with default config (only changed path to data and number of classes). When I tried to run the model on video, it gave 8-9 fps on average instead of 20 that was in the paper. What is the reason?
To calculate avg FPS I just ran inference_detector() for every frame in the video without any post-processing.

[WXinlong]

@Harut0726 The inference_detector() includes pre-processing. You can refer to inference.py for details.