User insight: Florence2's vision encoder activations scale with input image
dimensions, not with the polygon complexity it outputs. Down-scaling the
source image BEFORE detection saves the bulk of Florence2-stage VRAM
(encoder is dominant over the decoder's KV cache for moderate sequence
lengths). Detection accuracy at 0.5 MP is essentially identical to full
resolution for face/region tasks because the polygon is coarse and gets
smoothed by GrowMask + feather + crop+paste-back downstream anyway.
Implementation in florence2_hires.run_florence2_step:
- Read step_config['florence2_input_mp'] (default 0.5; set 0 to disable)
- If source MP > target, common_upscale source down to target dims with
lanczos before passing to Florence2Run
- After detection, common_upscale the returned mask back up to source dims
with bilinear so the crop / grow / feather / inpaint / paste-back chain
operates at full source resolution as before
- Only down-scales — never up-scales (skip when source already smaller)
- Manifest entry records florence2_input_mp + florence2_detect_resized
for forensics
- Console log shows both src and detect dimensions per call
UI: new 'Florence2 Input MP' numeric field (range 0-4.0, step 0.25)
in BOTH the Builder UI's Florence2 sub-panel and the Dashboard's Upscale
Image modal Florence2 panel. Default 0.5. Tooltip explains the VRAM
tradeoff and that it only takes effect when source > this MP.
Mirrors createDefaultFlorence2Options() + render block in both
conf-builder-config-management.js (Builder) and logic_upscale_modal.js
(Dashboard), keeping the two UI surfaces in sync.
Jason Hoku
fb3530d4d4