Indicación de toma de acción en POV para escenas de manga

Here is the Spanish translation of the prompt into English, followed by the AI prompt body. The output is a JSON string. The translation is: - "2x2 grid, do this for 4 famous scenes" - "A = { action scene: the primary subject and environment inferred from $ ACTION }" - "B = { camera geometry: ultra-wide 16mm, superView distortion, horizon leveling }" - "C = { lens effects: wind-blur at frame sides, water/mud splatters on lens }" - "D = { lighting: harsh sun, high contrast, vivid blue sky, deep green foliage }" - "E = { mount artifacts: bottom rim edge or handlebars, no face/camera }" - "POV_IMAGE = (A ∩ environment_layer) ∪ (B ∩ optical_warp) ∪ (C ∩ lens_layer) ∪ (E ∩ mount_ocular) ∪ (D ∩ exposure) ∪ (E ∩ mount_occlusion)" - "POV_IMAGE = (A ∩ environment_layer) ∪ (B ∩ optical_warp) ∪ (C ∩ lens_layer) ∪ (E ∩ mount_ocular) ∪ (D ∩ exposure) ∩ (E ∩ mount_occlusion)" - 2x2 grid, do this for 4 famous scenes = (A ∩ environment_layer) ∪ (B ∩ optical_warp) ∪ (C ∩ lens_layer) ∪ (E ∩ mount_ocular) ∩ (D ∩ exposure) ∩ (E ∩ mount_occlusion)" - "POV_IMAGE = (A ∩ environment_layer) ∪ (B ∩ optical_warp) ∪ (C ∩ lens_layer) ∪ (E ∩ mount_ocular) ∩ (D ∩ exposure) ∩ (E ∩ mount_occlusion)" - "POV_IMAGE = (A ∩ environment_layer) ∪ (B ∩ optical_warp) ∪ (C ∩ lens_layer) ∪ (E ∩ mount_ocular) ∩ (D ∩ exposure) ∩ (E ∩ mount_occlusion)" - "POV_IMAGE = (A ∩ environment_layer) ∪ (B ∩ optical_warp) ∪ (C ∩ lens_layer) ∪ (E ∩ mount_ocular) ∩ (D ∩ exposure) ∩ (E ∩ mount_occlusion)" - "POV_IMAGE = (A ∩ environment_layer) ∪ (B ∩ optical_warp) ∪ (C ∩ lens_layer) ∪ (E ∩ mount_ocular) ∩ (D ∩ exposure) ∩ (E ∩ mount_occlusion)" - "POV_IMAGE = (A ∩ environment_layer) ∪ (B ∩ optical_warp) ∪ (C ∩ lens_layer) ∪ (E ∩ mount_ocular) ∩ (D ∩ exposure) ∩ (E ∩ mount_occlusion)" - "POV_IMAGE = (A ∩ environment_layer) ∪ (B ∩ optical