Document radial overhead validation

README.md

@@ -90,7 +90,7 @@ ZhengPeng7/BiRefNet (transparent-cutout alpha only)
 
 SDXL Base is a 3B-parameter Open RAIL++ text-to-image model. Production generation intentionally runs without an LCM acceleration adapter: backgrounds use 30 denoising steps, sprites use 32, and classifier-free guidance is 8.0. This is slower than the earlier SSD-1B + LCM configuration, but it preserves the base model's full denoising process, makes negative prompts effective, and gives strict perspective and composition instructions substantially more influence. The weights run inside the Space's free ZeroGPU allocation, so the app does not consume Hugging Face Inference Provider credits and does not require a paid image API.
 
-Sprites and backgrounds are generated directly from their written prompts. No procedurally drawn sprite, palette, silhouette, camera guide, or background layout is passed into the production image generator. Strict top-down sprites use a native 1024×1024 canvas, an orthographic 90-degree overhead instruction at the front of the positive prompt, and an effective negative prompt that rejects front, oblique, three-quarter, eye-level, and side-elevation views. Other perspectives use camera-appropriate native SDXL aspect ratios. BiRefNet predicts only the alpha mask for transparent cutouts while preserving SDXL's generated RGB artwork. After neural transparency extraction, sprites with zero or multiple significant foreground components, retained scene-like alpha, implausible silhouettes, or inadequate scale are regenerated with a new seed up to `PRIMARY_SPRITE_ATTEMPTS` times. If every attempt fails, the deployed Space returns an explicit model-generation error rather than returning a character sheet, environment-contaminated cutout, or obvious upright portrait. Background negative prompts reject characters and generic particle overlays.
+Sprites and backgrounds are generated directly from their written prompts. No procedurally drawn sprite, palette, silhouette, camera guide, or background layout is passed into the production image generator. Strict top-down sprites use a native 1024×1024 canvas, an orthographic 90-degree overhead instruction at the front of the positive prompt, and an effective negative prompt that rejects front, oblique, three-quarter, eye-level, and side-elevation views. Other perspectives use camera-appropriate native SDXL aspect ratios. BiRefNet predicts only the alpha mask for transparent cutouts while preserving SDXL's generated RGB artwork. After neural transparency extraction, sprites with zero or multiple significant foreground components, retained scene-like alpha, implausible silhouettes, inadequate scale, or explicitly radial bodies without plausible rotational balance are regenerated with a new seed up to `PRIMARY_SPRITE_ATTEMPTS` times. If every attempt fails, the deployed Space returns an explicit model-generation error rather than returning a character sheet, environment-contaminated cutout, or obvious upright portrait. Background negative prompts reject characters and generic particle overlays.
 
 SDXL uses two fixed text encoders with limited prompt context. Production prompts therefore retain a conservative word budget, place the camera and single-subject contract first, and compact the free-form description. This prevents critical geometry constraints from being silently truncated behind verbose style text.