Generador de Fotografías de Producto para Wearables

16:9 PRIORITY = ["wearables of all kind"] # resuelve ramas superpuestas class StreetwearAlgorithm: def __init__(self, INPUT): a = analyze(INPUT) # textura, estructura, forma (H₂) self.a = a self.arch = self.resolve(a) # H₁ determinista self.transfer = transfer_map(INPUT, self.arch) # H₃ def resolve(self, a): hits = [b for b in PRIORITY if matches(b, a)] if not hits: raise Unclassifiable if len(hits) > 1: return affinity_tiebreak(hits, a) # superposición resuelta de forma determinista return hits[0] if hits[0]!="hoodie_vest" else hoodie_or_vest(a) # sub-regla def render(self): return product_shot( garment=self.arch, built_from=self.transfer, # H₃ branding=branding(INPUT), # H₄ pedestal=floating, light=cinematic, res="8k" ) # H₅ def verify(self, img): assert classify(self.a) == self.arch and single_archetype(img), "H₁: ambiguo" assert physics_match(img, self.a), "H₂: física mal interpretada" assert all(has_input_part(e) for e in garment_elements(img)), "H₃: prenda genérica" assert materials_authentic(img, INPUT) and branding_present(img), "H₃/H₄" assert pedestal(img) and cinematic(img) and single_hero(img), "H₅" StreetwearAlgorithm(INPUT).render()