GitHub - nihui rife-ncnn-vulkan: RIFE, Real-Time Intermediate Flow . . . ncnn implementation of RIFE, Real-Time Intermediate Flow Estimation for Video Frame Interpolation rife-ncnn-vulkan uses ncnn project as the universal neural network inference framework Download Windows Linux MacOS Executable for Intel AMD Nvidia GPU https: github com nihui rife-ncnn-vulkan releases
GitHub - hzwer ECCV2022-RIFE: ECCV2022 - Real-Time Intermediate Flow . . . If you are a developer, welcome to follow Practical-RIFE, which aims to make RIFE more practical for users by adding various features and design new models with faster speed You may check this pull request for supporting macOS
rife47. pth · jasonot mycomfyui at main - Hugging Face Upload rife47 pth 84902d7 verified about 1 year ago download Copy download link history blame contribute delete Safe pickle Detected Pickle imports (3) "torch FloatStorage", "collections OrderedDict", "torch _utils _rebuild_tensor_v2" What is a pickle import? 21 3 MB
rife-ncnn-vulkan-python · PyPI rife-ncnn-vulkan is nihui's ncnn implementation of Real-Time Intermediate Flow Estimation for Video Frame Interpolation rife-ncnn-vulkan-python wraps rife-ncnn-vulkan project by SWIG to make it easier to integrate rife-ncnn-vulkan with existing python projects Linux Windos Mac X86_64 binary build releases are available now
RIFE AI interpolation - SmoothVideo Project (SVP) - frame doubling . . . RIFE is a Real-time Intermediate Flow Estimation algorithm based on a neural network named IFNet, that can directly estimate the intermediate flows from images SVP can use RIFE engine in both transcoding and real-time playback modes
styler00dollar VapourSynth-RIFE-ncnn-Vulkan - GitHub Real-Time Intermediate Flow Estimation for Video Frame Interpolation, based on rife-ncnn-vulkan clip: Clip to process Only RGB format with float sample type of 32 bit depth is supported The models folder needs to be in the same folder as the compiled binary By default models are exported with ensemble=False and Fast=True model: Model to use