Squirrel-RIFE is a GPU-accelerated video processing tool that uses a neural network to generate intermediate frames between existing video frames, enabling smooth slow-motion effects and frame rate conversion. It is built around the RIFE (Real-Time Intermediate Flow Estimation) model, which analyzes motion between consecutive frames to predict and insert new frames, and leverages NVIDIA CUDA for parallel processing to achieve high-speed inference.
The tool distinguishes itself by combining neural frame interpolation with practical video preprocessing features, including pixel-level duplicate frame detection and removal to eliminate stuttering in animated content, and a scene transition detector that identifies cuts with high accuracy to avoid generating interpolated frames across scene changes. It integrates FFmpeg as its video I/O layer for decoding source files and encoding output, and includes an arbitrary frame rate calculator that computes the exact number of intermediate frames needed for conversion between any input and output frame rates without rounding errors.
Squirrel-RIFE processes video frames in parallel batches to maximize GPU utilization, and its capabilities extend to generating smooth slow-motion video from standard-speed footage. The tool is available as a Python application with documentation covering installation and usage.
