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Victor Kuznetsov
9bd2c17cc4
Add `auto_config.plan(image_path) -> AutoConfig`, the first step of the invisible/all pipeline: it inspects the input image (before the diffusion model loads) and picks the quality modes so the run adapts to content. Quality-priority routing -- ControlNet (text/face-structure preservation) is the default, skipped for plain SDXL only on a clearly structure-less image; GFPGAN face restore when a face is present; a mild sharpen + grain polish when a smoothing pass ran. Exposed as `--auto` on `all`/`invisible` (`_apply_auto`; explicit flags override via click's parameter source). Not wired into batch (its engine is cached per-mode). Detection is cv2-only and torch-free (~100 MB peak RSS, a few ms): OpenCV YuNet (`cv2.FaceDetectorYN`, MIT, 232 KB model bundled in assets/) for faces, a Canny edge-density + MSER heuristic for text/structure (a rough Phase-1 placeholder; DBNet via cv2.dnn is the planned upgrade). ZERO new pip deps. Designed to run wherever the pipeline runs -- the raiw.cc Modal GPU worker -- never on the 512 MB web host. Real-ESRGAN-via-Spandrel upscaling (a new `esrgan` extra) and an adaptive Laplacian-variance polish are deferred to later phases. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>