17.12.2022, 11:18
Hello Selur!
I downloaded your dev version, the torch addons, and now RealESRGAN in Hybrid is working as expected.
I done some tests and despite the jump in version (from 3.0.0 to 4.0.1) I was unable to observe significant improvement in quality for RealESRGAN.
The only big improvement was on the start-up time when the TensorRT is enabled. Previously it was necessary to wait till 40min before the encoding could start and was generated a cache file with name like: "TensorrtExecutionProvider_TRTKernel_graph_torch-jit-export_18011103394555784438_1_0_fp16.engine".
Now the start-up with TensorRT is less than 1min and are not generated the cache files (the cache is in memory ?).
It seems that this improvement in using TensorRT has impacted on the encoding speed. Now the encoding using "x4plus_anime_6B" (old name) is 15% slower and the encoding using animevideo_v3 is 27% slower respect to animevideo_v2 with no observable difference in quality.
I don't know if this decrease in speed is due to the fact that the version 4.0.1 dropped the support to ONNX, there is a way to enable it ? i.e. convert the "pth" models in "onnx" ?
I noted also that you included RealCUGAN. I tested all the 3 models, but on my sample only the "se" model was able to provide a good quality, comparable with RealESRGAN animevideo.
It seems that it is missing the support for TensorRT in RealCUGAN and its encoding speed is slower respect to RealESRGAN animevideo when TensorRT is enabled (4.06fps vs 13.58fps).
I Thank you very much for the support.
Dan
I downloaded your dev version, the torch addons, and now RealESRGAN in Hybrid is working as expected.
I done some tests and despite the jump in version (from 3.0.0 to 4.0.1) I was unable to observe significant improvement in quality for RealESRGAN.
The only big improvement was on the start-up time when the TensorRT is enabled. Previously it was necessary to wait till 40min before the encoding could start and was generated a cache file with name like: "TensorrtExecutionProvider_TRTKernel_graph_torch-jit-export_18011103394555784438_1_0_fp16.engine".
Now the start-up with TensorRT is less than 1min and are not generated the cache files (the cache is in memory ?).
It seems that this improvement in using TensorRT has impacted on the encoding speed. Now the encoding using "x4plus_anime_6B" (old name) is 15% slower and the encoding using animevideo_v3 is 27% slower respect to animevideo_v2 with no observable difference in quality.
I don't know if this decrease in speed is due to the fact that the version 4.0.1 dropped the support to ONNX, there is a way to enable it ? i.e. convert the "pth" models in "onnx" ?
I noted also that you included RealCUGAN. I tested all the 3 models, but on my sample only the "se" model was able to provide a good quality, comparable with RealESRGAN animevideo.
It seems that it is missing the support for TensorRT in RealCUGAN and its encoding speed is slower respect to RealESRGAN animevideo when TensorRT is enabled (4.06fps vs 13.58fps).
I Thank you very much for the support.
Dan