Un collage de fotos vertical con calidad de teléfono móvil que muestra tres paneles: una toma panorámica en la parte superior, un retrato en el medio y un detalle macro en la parte inferior. Las imágenes siguen una estética de 'photo dump' al estilo VSCO con una gradación de color vibrante y cálida propia de un concierto, capturadas con una simulación de iPhone 17ProMax utilizando lentes variadas (ultra gran angular, gran angular, teleobjetivo) con una apertura de f/1.8. La iluminación proviene de fuentes dinámicas de concierto, incluyendo luces estroboscópicas y el brillo de los teléfonos, creando reflejos brillantes sobre la piel y sombras profundas de alto contraste. La escena se desarrolla en un enorme estadio de música por la noche con acceso a la pista y vista al escenario, incluyendo una pantalla de video y siluetas de manos del público. La protagonista es una influencer nórdica atlética de 21 años con cabello rubio y ojos azules, vistiendo un Wonderbra negro y tanga en V con tacones altos negros. Su piel tiene un brillo bronceado con dispersión subsuperficial visible debido al calor del escenario, y presenta detalles biológicos realistas como vello fino en las mejillas y detalles visibles en el iris. El panel central la muestra guiñando un ojo con una señal de paz sobre él, mientras que el panel inferior la captura caminando con tacones. La composición utiliza una perspectiva en primera persona con la regla de los tercios en cada panel y un equilibrio asimétrico. El color está realzado selectivamente en el confeti con toques de magenta y cian. El efecto general debe sentirse como una noche auténtica en un concierto, evitando la iluminación de estudio, el grano de película vintage o aspectos demasiado pulidos.
Publicación en redes sociales - Collage de 'Photo Dump' de concierto con iPhone
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Un prompt JSON extremadamente detallado para Nano Banana Pro con el fin de generar un collage vertical de varios paneles que simule un 'Photo Dump al estilo VSCO' de un concierto, completo con ajustes de cámara específicos (simulación de iPhone 17 Pro Max), efectos de iluminación (luces estroboscópicas, destellos de lente) y descripciones detalladas de la anatomía y el maquillaje del sujeto.
A highly specific prompt designed to generate an ultra-photorealistic image of Madelyn Cline hydrating after a tennis match. It focuses on post-workout realism, including perspiration, damp clothing clinging to the body, golden hour lighting, and a candid, confident pose, shot on an iPhone 15 Pro Max in a vertical 9:16 format.
A complex JSON prompt designed to generate a 2x2 grid collage of ultra-wide angle selfies in the style of a Gen Z candid social media dump, featuring a subject resembling Sydney Sweeney. The prompt meticulously details the image structure, global style settings (0.5x lens, high-angle distortion, chaotic fairy aesthetic), subject details (outfit, makeup, accessories), and specific expressions and poses for each of the four panels (tongue out, duck face, winking).
A highly detailed JSON prompt for Nano Banana Pro to generate a 2x2 grid collage of Sydney Sweeney selfies using an ultra-wide angle lens (0.5x / fisheye effect), capturing a Gen Z candid social media dump aesthetic with specific expressions and a lime green sequin dress.
A highly technical prompt for Gemini Nano Banana Pro designed to simulate a raw, high-contrast gym mirror selfie taken with an ultra-wide-angle iPhone 17 Pro lens. It mandates extreme bio-fidelity, sharp focus across all planes (no bokeh), aggressive anatomical tapering, and realistic textural details on clothing and skin, aiming for an unedited social media dump aesthetic.
A highly detailed image generation prompt designed to create an extremely realistic, raw, high-contrast mirror selfie. It specifies strict identity locking, bio-fidelity for skin textures (TrueLens physics), precise outfit material realism (vacuum-tight jersey knit), and environmental details like realistic mirror imperfections and a sharp background, aiming for an unedited social media dump aesthetic.
Generate a 9-image grid ‘photo dump’ of a person’s weekend including mirror selfie, café, friends at dinner, party, walking, work shot, pet, sunset, and candid laughing moments.
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Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Non-precise location data, Precise location data
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Browsing and interaction data, Non-precise location data, Precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, User-provided data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Precise location data
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
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