Releases: HolyWu/vs-rife
Releases · HolyWu/vs-rife
v3.1.0
v3.0.0
- Add
model
paramter to support v4.0~v4.6 models. - Add
ensemble
parameter to smooth predictions in areas where the estimation is uncertain. - Fix corruption with FP16 mode on 4K video.
- Replace
multi
parameter withfactor_num
,factor_den
,fps_num
andfps_den
for rational frame rate change. - Add
sc
andsc_threshold
parameters for scene change detection. - Add
cuda_graphs
parameter to use CUDA Graphs. - Add
fusion
parameter to enable fusion through nvFuser. - Remove
device_type
parameter. No one bothers to run deep learning inference on CPU anyway. - Add
num_streams
parameter for parallel execution. - Remove
fp16
parameter and now it's controlled by the format of the clip.RGBH
format uses FP16 mode andRGBS
format uses FP32 mode. - Add
trt
,trt_max_workspace_size
, andtrt_cache_path
parameters for TensorRT support.
With the usage of TensorRT, it should run at least 40~50% faster than previous version or RIFE-ncnn-Vulkan implementation using FP16 mode on GPUs with Tensor Cores. For ease of installation on Windows, you can download the CUDA 7z file which contains required runtime libraries and Python wheel file. Either add the unzipped directory to your system PATH
or copy the DLL files to a directory which is already in your system PATH
. Finally pip install
the Python wheel file.