https://github.com/Snickrr/Auto-Target-Encoder
A sophisticated, GUI-based encoding tool designed for automated batch processing of your videos that do not require comprehensive fine-tuning. It leverages machine learning to create high-quality, efficient AV1 video encodes. This application automates the entire workflow for large batches of files: it learns from past encodes to predict optimal quality settings, intelligently analyzes each video's complexity, and displays the progress of all parallel jobs in a real-time dashboard.
This tool moves beyond single-file, trial-and-error encoding by building persistent knowledge. A RandomForest machine learning model predicts the exact CQ/CRF value needed to hit a target quality score (VMAF, SSIMULACRA2, BUTTERAUGLI), while other models provide highly accurate ETA predictions by learning your hardware's real-world performance across hundreds of encodes.
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Not tested nor created by me.