ALPHA 2.5: Frostbite Revival (Released 12/23/21)
Changelog:
[ UI ] Chained design. All steps link to one another! Use the master override toggles to skip processes.
[ Upscaling ] GFPGAN face-enhance toggle (embedded in Real-ESRGAN)
[ Interpolation ] Practical-RIFE implementation; 4.0 model
[ File mgmt ] Compatibility with padded filenames, File overwrite protection, verification of completion
[ Misc ] Forked essential dependencies for long-term backwards compatibility; if needed.
*This updates brings AnKit back to a functioning state. Upcoming updates will make use of recent prerequisite updates and coinciding AI advances. *
Your (eventual) all-in-one AI post-processing tool!
Early Alpha Google Colab Notebook
- AnimationKit Colab Notebook for Real-ESRGAN
.
Features:
- ✅ Real-ESRGAN video upscaling (Raise your resolution by up to 4x!)
- ✅ Practical-RIFE motion smoothing / video interpolation (Make choppy footage smooth)
- ✅ Chained design - No need to sort through multiple cells! Set your options and forget it.
- ✅ Google Colab (with basic UI) & Google Drive support
- ✅ Import either mp4 files or an individual frame folder
Real-ESRGAN video upscaling, RIFE interpolation/motion smoothing, and FFMPEG hevc_nvenc (h265) compression
Credits: Motion smoothing conceived from "Zoom animation processing and motion interpolation" added by https://twitter.com/unltd_dream_co. This part of the script uses RIFE real-time video interpolation to smooth out the resulting video.
Upscaling uses Real-ESRGAN (https://github.com/xinntao/Real-ESRGAN). A demo notebook for static images can be found here: https://colab.research.google.com/drive/1k2Zod6kSHEvraybHl50Lys0LerhyTMCo?usp=sharing. The demo was based on the following paper: ''Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data''.
Feature additions & bugfixes:
Feel free to report bugs and/or help with developments! See the "Issues" page for documentation and development notes-
#Prior Changelog (Incomplete)
##ALPHA 2: Released 9/4/21 Feature additions
- :🔻: Deflickering [Depcrecated]
- ✅ Upscaling from individual frames (P2)
- ✅ Target length (in seconds) for RIFE interpolation - Replaces old length_multiplier option
#Alpha 1 release: All major bugs have (hopefully) been patched. New functions will be released in the testing branch until debugged.
- ✅ Anime model for realesrgan
- ✅ 2x model
- ✅ target output path
- ✅ omission of outscaling (note, may need to check defaults in inference.py)
- ✅ target fps no longer causes duplicates prior to ffmpeg end-phase (prevents upscaler from wasting gpu cycles on duplicate frames; major speed increase)
- ✅ notebook set to high memory - necessary for RIFE