Implement advanced AI enhancements UI tracking, styling, requirements, and documentation modal

2026-06-24 13:45:34 -04:00
parent 212291ea94
commit 7b7cb2866a
7 changed files with 236 additions and 16 deletions
@@ -56,3 +56,9 @@ A typical upscale job follows these sequential steps:
 - **Self-Sufficiency**: Running `python3 start.py` automatically checks for a local virtual environment (`venv/` or `.venv/`).
 - **Auto-Provisioning**: If no virtual environment is found, `start.py` will initialize one in `venv/`, upgrade `pip`, install all dependencies listed in `requirements.txt`, mark the Real-ESRGAN binary as executable (`chmod +x`), and create necessary folders (`uploads/`, `outputs/`, `temp/`).
 - **Seamless Launch**: It then automatically launches the server process using the newly created environment interpreter.
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+### 4. Advanced AI Enhancements
+- **AI Face Restoration (GFPGAN)**: Runs as a python subprocess invoking `gfpgan.inference_gfpgan` to restore and clear up human faces in low-resolution video frames. Results are copied directly back into the frame output folder before motion interpolation and final video assembly.
+- **AI Frame Interpolation (RIFE)**: Runs using the `rife-ncnn-vulkan` binary (expected in `rife-bin/`). Smooths motion by generating and inserting intermediate frames, doubling the framerate. Falls back to FFmpeg's `minterpolate` optical flow filter if the Vulkan binary is not present.
+- **AI Audio Denoising (RNNoise)**: Transports and filters audio using the deep-learning-based `arnnoise` FFmpeg filter, eliminating background noise from output tracks during assembly.
+