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Did this one on hard mode. two different camera systems intercut in the same 30 seconds, normal third-person following her, and the enemy's surveillance feed watching her. Most models just flatten that into one look. this kept them telling apart, which is the only reason i'm posting it. Rain...

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Kaitee

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16,725 Aufrufe • vor 17 Tagen •via X (Twitter)

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Made with seedance 2.5 Prompt: Create a highly cinematic, realistic action sequence inside a crowded traditional Asian wet market during heavy rain and flooding. A young Asian woman with long dark wet hair, wearing a pink waterproof rain suit and black rubber boots, runs rapidly through the narrow market aisles while trying to escape from a massive rushing wave of water behind her. The market is packed with seafood and vegetable stalls, plastic crates, fish tanks, metal counters, hanging tarps, fluorescent ceiling lights, vendors and crowds. The floor is completely flooded with ankle-to-knee-deep dirty rainwater, creating strong reflections and splashes everywhere. Water violently rushes through the market, knocking over crates and flooding the stalls. Start with a close-up tracking shot of the frightened woman looking back over her shoulder while running. Follow her with a fast handheld camera as she runs through the narrow aisle. Use dynamic low-angle shots close to the water, capturing her boots hitting the flooded floor and creating dramatic splashes. Show water crashing through the market behind her, people running in panic, overturned crates floating in the water, and objects being swept away. Use realistic physics, natural human movement, detailed wet clothing, wet hair sticking to her face, realistic water droplets, splashes, reflections and motion blur. The camera should move dynamically with fast tracking shots, low-angle shots, side tracking shots and occasional wide shots revealing the scale of the flooding. At one point, show the woman jumping over obstacles and running across a market counter/raised surface while the floodwater continues rushing behind her. Keep her appearance, hairstyle, pink outfit and facial features consistent throughout the entire sequence. Dark cinematic atmosphere, overcast rainy lighting, cool blue-gray tones mixed with warm fluorescent market lights, dramatic contrast, realistic skin texture, photorealistic environment, volumetric lighting, atmospheric mist, cinematic depth of field, subtle film grain, high-detail textures, realistic reflections and physically accurate water simulation. The sequence should feel like a high-budget survival/action movie, extremely immersive and intense, with realistic camera shake and fast-paced movement. Add large cinematic white brush-stroke typography reading “RUN” briefly across the center of the screen during the action sequence. Photorealistic, ultra-detailed, cinematic Hollywood-style action scene, realistic physics, natural motion, 4K film quality, anamorphic lens look, dynamic composition, dramatic pacing, no cartoon look, no CGI appearance, no distorted anatomy, no extra fingers, no duplicated people, no face changes.
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Made with seedance 2.5 Prompt: Create a highly cinematic, realistic action sequence inside a crowded traditional Asian wet market during heavy rain and flooding. A young Asian woman with long dark wet hair, wearing a pink waterproof rain suit and black rubber boots, runs rapidly through the narrow market aisles while trying to escape from a massive rushing wave of water behind her. The market is packed with seafood and vegetable stalls, plastic crates, fish tanks, metal counters, hanging tarps, fluorescent ceiling lights, vendors and crowds. The floor is completely flooded with ankle-to-knee-deep dirty rainwater, creating strong reflections and splashes everywhere. Water violently rushes through the market, knocking over crates and flooding the stalls. Start with a close-up tracking shot of the frightened woman looking back over her shoulder while running. Follow her with a fast handheld camera as she runs through the narrow aisle. Use dynamic low-angle shots close to the water, capturing her boots hitting the flooded floor and creating dramatic splashes. Show water crashing through the market behind her, people running in panic, overturned crates floating in the water, and objects being swept away. Use realistic physics, natural human movement, detailed wet clothing, wet hair sticking to her face, realistic water droplets, splashes, reflections and motion blur. The camera should move dynamically with fast tracking shots, low-angle shots, side tracking shots and occasional wide shots revealing the scale of the flooding. At one point, show the woman jumping over obstacles and running across a market counter/raised surface while the floodwater continues rushing behind her. Keep her appearance, hairstyle, pink outfit and facial features consistent throughout the entire sequence. Dark cinematic atmosphere, overcast rainy lighting, cool blue-gray tones mixed with warm fluorescent market lights, dramatic contrast, realistic skin texture, photorealistic environment, volumetric lighting, atmospheric mist, cinematic depth of field, subtle film grain, high-detail textures, realistic reflections and physically accurate water simulation. The sequence should feel like a high-budget survival/action movie, extremely immersive and intense, with realistic camera shake and fast-paced movement. Add large cinematic white brush-stroke typography reading “RUN” briefly across the center of the screen during the action sequence. Photorealistic, ultra-detailed, cinematic Hollywood-style action scene, realistic physics, natural motion, 4K film quality, anamorphic lens look, dynamic composition, dramatic pacing, no cartoon look, no CGI appearance, no distorted anatomy, no extra fingers, no duplicated people, no face changes.

Elisia

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RUN BEFORE THE FLOOD TAKES EVERYTHING One Woman. One Cow. One Chance to Escape. Made with seedance 2.5 on NadouPro Prompt: Create a photorealistic, high-budget cinematic action scene in a crowded traditional Asian wet market during heavy rain and severe flooding. A young Asian woman with long wet dark hair, wearing a pink waterproof rain suit and black rubber boots, runs through flooded market aisles while a massive wave of water rushes behind her. Show seafood and vegetable stalls, floating crates, overturned objects, panicked crowds, rushing dirty water, reflections, splashes and realistic wet details. Use fast handheld tracking, close-ups, low-angle water shots, side tracking and wide shots, with realistic physics, motion blur and dynamic camera shake. She jumps over obstacles and runs across raised market surfaces. Near the end, she reaches a raised area where a frightened cow is trapped by the flood. She looks at it and urgently says: “Come on, girl! Move!” She guides the cow toward safety. Keep her face, hairstyle and pink outfit consistent. Dark rainy atmosphere, cool blue-gray tones mixed with warm fluorescent lights, cinematic depth of field, volumetric lighting, realistic skin, water and reflections, subtle film grain, 4K anamorphic Hollywood action style. Add large white brush-stroke typography “RUN” briefly across the center. No cartoon look, CGI appearance, distorted anatomy, extra fingers, duplicated people or face changes.
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RUN BEFORE THE FLOOD TAKES EVERYTHING One Woman. One Cow. One Chance to Escape. Made with seedance 2.5 on NadouPro Prompt: Create a photorealistic, high-budget cinematic action scene in a crowded traditional Asian wet market during heavy rain and severe flooding. A young Asian woman with long wet dark hair, wearing a pink waterproof rain suit and black rubber boots, runs through flooded market aisles while a massive wave of water rushes behind her. Show seafood and vegetable stalls, floating crates, overturned objects, panicked crowds, rushing dirty water, reflections, splashes and realistic wet details. Use fast handheld tracking, close-ups, low-angle water shots, side tracking and wide shots, with realistic physics, motion blur and dynamic camera shake. She jumps over obstacles and runs across raised market surfaces. Near the end, she reaches a raised area where a frightened cow is trapped by the flood. She looks at it and urgently says: “Come on, girl! Move!” She guides the cow toward safety. Keep her face, hairstyle and pink outfit consistent. Dark rainy atmosphere, cool blue-gray tones mixed with warm fluorescent lights, cinematic depth of field, volumetric lighting, realistic skin, water and reflections, subtle film grain, 4K anamorphic Hollywood action style. Add large white brush-stroke typography “RUN” briefly across the center. No cartoon look, CGI appearance, distorted anatomy, extra fingers, duplicated people or face changes.

Noor

17,446 Aufrufe • vor 18 Tagen

A FITNESS INSTRUCTOR FROM DUBAI NAMED KIRA FILLS A 200-PERSON CLASS EVERY NIGHT AT $45 A HEAD BY MAKING HER WORKOUTS LOOK LIKE SOMETHING THAT WOULD GET BANNED ON EVERY OTHER PAGE. Thread. Here's the format that fitness influencers have been trying to crack for years and one girl in Dubai solved it by turning off the lights. A dark studio. Red and orange lighting. Neon workout sets. 200 women on orange mats doing hip thrusts in sync. The camera sits at floor level and drifts along the row. This is a workout class. It looks like the opening scene of a movie you'd watch with the door locked. Here's what Kira understood. Nobody shares a workout video because the exercise is effective. People share workout videos because of how the exercise looks. Hip thrusts are the single most effective glute exercise in strength training. They're also the single most suggestive movement a human body can make in a gym setting. She didn't invent the exercise. She invented the way you film it. Floor level, dark room, neon fabric, red light. Same exercise in a Planet Fitness under fluorescent bulbs gets 3,000 views. Same exercise in her studio gets 18 million. The neon is doing business nobody talks about. Hot pink, electric green, purple, white. Every color pops against the dark studio and the orange mats. The algorithm reads bright colors on dark backgrounds as high-contrast content and pushes it harder. But here's the real play: the neon colors are her merchandise. Every set you see in the video is available on her site. She doesn't tag the product, doesn't show a price, doesn't mention the store. The comments do it for her. "Where is the pink set from." "Link for the white leggings." Forty thousand free product inquiries per video and she never ran an ad. The class sells out 3 weeks in advance. Not because the programming is unique. The exercises are standard. Hip thrusts, bridges, glute kickbacks. You can find them in any trainer's plan. The class sells out because every person in the room knows they'll be in the video. 200 women pay $45 each to be background extras in a clip that will do 10 million views. They're not paying for the workout. They're paying for the content. They show up in neon, film themselves from their mat, post their own angle, tag the studio. 200 personal accounts all posting the same class on the same night. The reach multiplies by 200 every session and Kira doesn't post a single one of those. The camera angle is the moat. Any trainer can darken a room and buy colored lights. But the floor-level camera that drifts along a row of bodies mid-thrust is what makes this unflagable pornography for the fitness feed. It's a workout. Everyone is clothed. The exercise is in every textbook. But 200 women thrusting upward in neon under red light filmed from the floor doesn't read as fitness. It reads as something your brain has no clean category for. And content without a category gets watched longer because your brain is still trying to file it. She turned a gym into a nightclub, a nightclub into a content studio, and a content studio into a merch store. The class is the content. The content is the ad. The ad is the class. The loop never opens and the $45 is just the entry fee to a machine that prints views, sells leggings, and fills the next class with people who saw the last one. The lights are off but the business has never been more visible.
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A FITNESS INSTRUCTOR FROM DUBAI NAMED KIRA FILLS A 200-PERSON CLASS EVERY NIGHT AT $45 A HEAD BY MAKING HER WORKOUTS LOOK LIKE SOMETHING THAT WOULD GET BANNED ON EVERY OTHER PAGE. Thread. Here's the format that fitness influencers have been trying to crack for years and one girl in Dubai solved it by turning off the lights. A dark studio. Red and orange lighting. Neon workout sets. 200 women on orange mats doing hip thrusts in sync. The camera sits at floor level and drifts along the row. This is a workout class. It looks like the opening scene of a movie you'd watch with the door locked. Here's what Kira understood. Nobody shares a workout video because the exercise is effective. People share workout videos because of how the exercise looks. Hip thrusts are the single most effective glute exercise in strength training. They're also the single most suggestive movement a human body can make in a gym setting. She didn't invent the exercise. She invented the way you film it. Floor level, dark room, neon fabric, red light. Same exercise in a Planet Fitness under fluorescent bulbs gets 3,000 views. Same exercise in her studio gets 18 million. The neon is doing business nobody talks about. Hot pink, electric green, purple, white. Every color pops against the dark studio and the orange mats. The algorithm reads bright colors on dark backgrounds as high-contrast content and pushes it harder. But here's the real play: the neon colors are her merchandise. Every set you see in the video is available on her site. She doesn't tag the product, doesn't show a price, doesn't mention the store. The comments do it for her. "Where is the pink set from." "Link for the white leggings." Forty thousand free product inquiries per video and she never ran an ad. The class sells out 3 weeks in advance. Not because the programming is unique. The exercises are standard. Hip thrusts, bridges, glute kickbacks. You can find them in any trainer's plan. The class sells out because every person in the room knows they'll be in the video. 200 women pay $45 each to be background extras in a clip that will do 10 million views. They're not paying for the workout. They're paying for the content. They show up in neon, film themselves from their mat, post their own angle, tag the studio. 200 personal accounts all posting the same class on the same night. The reach multiplies by 200 every session and Kira doesn't post a single one of those. The camera angle is the moat. Any trainer can darken a room and buy colored lights. But the floor-level camera that drifts along a row of bodies mid-thrust is what makes this unflagable pornography for the fitness feed. It's a workout. Everyone is clothed. The exercise is in every textbook. But 200 women thrusting upward in neon under red light filmed from the floor doesn't read as fitness. It reads as something your brain has no clean category for. And content without a category gets watched longer because your brain is still trying to file it. She turned a gym into a nightclub, a nightclub into a content studio, and a content studio into a merch store. The class is the content. The content is the ad. The ad is the class. The loop never opens and the $45 is just the entry fee to a machine that prints views, sells leggings, and fills the next class with people who saw the last one. The lights are off but the business has never been more visible.

Promt Lab Dialy

870,515 Aufrufe • vor 10 Tagen

Made this cinematic sequence using Seedance 2.5 The realism, camera movements, water physics, explosions, and intense atmosphere are on another level. AI video generation is getting seriously cinematic. Prompt ⤵️ Create a 30-second ultra-realistic cinematic disaster sequence with a dark, intense, Hollywood-blockbuster atmosphere. Main character: A young woman with short, messy dark hair, wearing a soaked white T-shirt and light-colored shorts. Keep her appearance consistent throughout the entire video. Her face should remain realistic and expressive, showing fear, shock, exhaustion, and determination. Scene 1 — 0–5 seconds: Open with an extreme close-up of the woman running toward the camera through a dark industrial shipping yard at night. Heavy rain is falling, her hair and clothes are completely wet, and she is breathing heavily. Behind her, bright industrial lights glow through thick smoke and mist. The camera moves backward smoothly while maintaining focus on her face. Add realistic rain droplets on the camera lens, dramatic backlighting, atmospheric fog, and handheld cinematic movement. Scene 2 — 5–10 seconds: Cut to a wider shot as she runs through the flooded container yard. Large shipping containers surround her, emergency lights flash in the distance, and explosions/fire erupt behind her. She looks over her shoulder in panic while continuing to run. Water splashes dramatically around her legs with every step. Use realistic fire, smoke, debris, rain, and volumetric lighting. Scene 3 — 10–15 seconds: She suddenly loses her balance and falls into the flooded ground. Show the impact in slow motion for a moment, with water splashing around her. She quickly pushes herself back up while terrified people run in the background. A massive wave of smoke, debris, and water moves through the shipping yard behind them. Use a low-angle camera close to the ground for a powerful disaster-movie perspective. Scene 4 — 15–21 seconds: She gets back on her feet and starts sprinting toward safety. The camera tracks alongside her at high speed. Containers shake, debris flies through the air, vehicles and objects are pushed around by the powerful force behind her. Keep her face and body consistent. Alternate between close-ups of her frightened expression and wide shots showing the enormous scale of destruction. Scene 5 — 21–25 seconds: She reaches a large modern building filled with terrified people. The camera follows her inside as everyone rushes toward safety. People are falling, crawling, and helping each other while water and debris can be seen outside through the entrance. The lighting changes from cold blue-gray exterior lighting to dramatic warm interior lighting. Scene 6 — 25–30 seconds: Suddenly transition to a massive luxury yacht in the middle of a violent ocean. Huge dark waves surround the vessel under a stormy sky. The camera starts behind the yacht and slowly reveals an enormous shark-like sea creature emerging from the ocean directly behind it, creating a terrifying final reveal. The creature rises through the waves with water cascading from its body. End with a gigantic wave crashing toward the yacht. Visual style: photorealistic Hollywood disaster film, cinematic color grading, realistic skin texture, physically accurate water and rain, volumetric fog, dramatic practical lighting, realistic fire and smoke, detailed environments, natural motion blur, shallow depth of field, dynamic camera movement, high contrast, atmospheric storm clouds, extremely detailed CGI, 4K cinematic quality. Camera: mixture of handheld close-ups, smooth tracking shots, wide establishing shots, low-angle disaster shots, slow-motion impact moments, and dramatic aerial/wide shots. Sound design: heavy rainfall, thunder, distant explosions, sirens, screaming crowds, footsteps splashing through water, crashing metal, deep cinematic bass, roaring waves, and an intense rising orchestral score that builds toward the final creature reveal.
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Made this cinematic sequence using Seedance 2.5 The realism, camera movements, water physics, explosions, and intense atmosphere are on another level. AI video generation is getting seriously cinematic. Prompt ⤵️ Create a 30-second ultra-realistic cinematic disaster sequence with a dark, intense, Hollywood-blockbuster atmosphere. Main character: A young woman with short, messy dark hair, wearing a soaked white T-shirt and light-colored shorts. Keep her appearance consistent throughout the entire video. Her face should remain realistic and expressive, showing fear, shock, exhaustion, and determination. Scene 1 — 0–5 seconds: Open with an extreme close-up of the woman running toward the camera through a dark industrial shipping yard at night. Heavy rain is falling, her hair and clothes are completely wet, and she is breathing heavily. Behind her, bright industrial lights glow through thick smoke and mist. The camera moves backward smoothly while maintaining focus on her face. Add realistic rain droplets on the camera lens, dramatic backlighting, atmospheric fog, and handheld cinematic movement. Scene 2 — 5–10 seconds: Cut to a wider shot as she runs through the flooded container yard. Large shipping containers surround her, emergency lights flash in the distance, and explosions/fire erupt behind her. She looks over her shoulder in panic while continuing to run. Water splashes dramatically around her legs with every step. Use realistic fire, smoke, debris, rain, and volumetric lighting. Scene 3 — 10–15 seconds: She suddenly loses her balance and falls into the flooded ground. Show the impact in slow motion for a moment, with water splashing around her. She quickly pushes herself back up while terrified people run in the background. A massive wave of smoke, debris, and water moves through the shipping yard behind them. Use a low-angle camera close to the ground for a powerful disaster-movie perspective. Scene 4 — 15–21 seconds: She gets back on her feet and starts sprinting toward safety. The camera tracks alongside her at high speed. Containers shake, debris flies through the air, vehicles and objects are pushed around by the powerful force behind her. Keep her face and body consistent. Alternate between close-ups of her frightened expression and wide shots showing the enormous scale of destruction. Scene 5 — 21–25 seconds: She reaches a large modern building filled with terrified people. The camera follows her inside as everyone rushes toward safety. People are falling, crawling, and helping each other while water and debris can be seen outside through the entrance. The lighting changes from cold blue-gray exterior lighting to dramatic warm interior lighting. Scene 6 — 25–30 seconds: Suddenly transition to a massive luxury yacht in the middle of a violent ocean. Huge dark waves surround the vessel under a stormy sky. The camera starts behind the yacht and slowly reveals an enormous shark-like sea creature emerging from the ocean directly behind it, creating a terrifying final reveal. The creature rises through the waves with water cascading from its body. End with a gigantic wave crashing toward the yacht. Visual style: photorealistic Hollywood disaster film, cinematic color grading, realistic skin texture, physically accurate water and rain, volumetric fog, dramatic practical lighting, realistic fire and smoke, detailed environments, natural motion blur, shallow depth of field, dynamic camera movement, high contrast, atmospheric storm clouds, extremely detailed CGI, 4K cinematic quality. Camera: mixture of handheld close-ups, smooth tracking shots, wide establishing shots, low-angle disaster shots, slow-motion impact moments, and dramatic aerial/wide shots. Sound design: heavy rainfall, thunder, distant explosions, sirens, screaming crowds, footsteps splashing through water, crashing metal, deep cinematic bass, roaring waves, and an intense rising orchestral score that builds toward the final creature reveal.

Noor 🌸

23,233 Aufrufe • vor 29 Tagen

Spiderwoman in your town Seedance 2.0 on FlovaAI prompt 45-Second Cinematic AI Video Prompt** 45 seconds, photorealistic, cinematic superhero film, ultra-detailed, 8K HDR, realistic physics, dynamic camera movement, fast-paced editing, dramatic lighting, natural facial expressions, high-end VFX, Japanese female lead, no text, no watermark. **Main Character:** A beautiful young **Japanese woman** in her early 20s with fair skin, soft natural makeup, expressive dark brown eyes, and shoulder-length black hair tied into a low ponytail. She wears an **oversized light blue knit sweater**, loose gray pants, and white sneakers throughout the story. Maintain identical facial identity, hairstyle, body proportions, and outfit consistency across every scene. ### Scene 1 (0–6s) – The Spider Bite Inside a cozy modern apartment during the afternoon. Extreme macro close-up as a glowing crystal-like translucent spider slowly crawls onto the back of the Japanese woman's neck. The spider sparkles with iridescent blue light before gently biting her. A glowing blue spider-shaped mark appears beneath her skin, sending shimmering energy across her neck. She gasps softly and turns in surprise. Cinematic macro lens, shallow depth of field, dramatic lighting. ### Scene 2 (6–12s) – Powers Awakening She walks through her apartment wearing her oversized **light blue sweater** and gray pants. Suddenly books, mugs, and small household objects begin floating around her. Confused, she raises her hands, and a metallic glowing spider web suddenly shoots from her wrist, sticking to a distant wall. Her eyes widen in shock before she smiles with excitement. Fast push-in camera, floating debris, cinematic energy effects. ### Scene 3 (12–21s) – First Leap She steps onto the balcony of a towering skyscraper overlooking a massive modern metropolis under bright daylight. Without hesitation she leaps into open air. The camera rotates as she freefalls upside down between towering glass skyscrapers. Just before reaching another building, she fires brilliant silver-blue web lines from both wrists and swings powerfully through the city. Dynamic drone shots, rapid FPV movement, realistic wind simulation, superhero movie energy. ### Scene 4 (21–31s) – Web Acrobatics An adrenaline-filled montage of spectacular web-swinging through narrow urban streets, soaring between skyscrapers, performing flips above busy intersections, landing gracefully on rooftops, vaulting across glass towers, and gliding over a luxurious rooftop infinity pool overlooking the skyline. The camera alternates between cinematic tracking shots, aerial drone views, slow-motion hero moments, and fast FPV chase sequences. Bright daylight, highly realistic reflections, cinematic action. ### Scene 5 (31–36s) – Sunset Break Golden-hour sunset. A peaceful wide cinematic shot shows her sitting comfortably on a high steel construction beam far above the city. She casually eats a sandwich while admiring the glowing skyline. Gentle breeze moves her ponytail and oversized **light blue sweater**. Warm orange sunlight creates a calm contrast to the previous action scenes. Emotional cinematic composition. ### Scene 6 (36–41s) – Neon Night Nighttime in a vibrant neon-lit alley filled with colorful reflections after light rain. She hangs upside down from a single web line, smiling warmly. A curious black cat sits calmly on a nearby windowsill staring back at her. Blue and pink neon lights reflect across her face and sweater while the city glows behind her. Slow cinematic camera orbit with soft depth of field. ### Scene 7 (41–45s) – Home Again She swings effortlessly back toward her apartment building, lands smoothly on her balcony, performs a stylish flip into the living room, and collapses onto the sofa laughing happily. She pulls out her phone, starts chatting excitedly, and smiles as the camera slowly pulls away through the apartment window while the city lights sparkle outside. End with a cinematic superhero-style closing shot. **Visual Style:** Hollywood superhero movie aesthetic, photorealistic, cinematic color grading, realistic cloth simulation, physically accurate web physics, dynamic lighting, volumetric sunlight, realistic facial animation, expressive emotions, smooth character consistency, high-speed action choreography, premium VFX, ultra-detailed environments, crisp reflections, motion blur, dramatic camera transitions, IMAX-quality visuals, 8K HDR.
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Aaliya

56,907 Aufrufe • vor 1 Monat

Seedance 2.5 frozen time + rewind effect prompt is below 👇 Photorealistic cinematic 1950s American diner, chrome stools, red vinyl, neon glow and checkerboard floor, shot with modern lived-in realism and soft natural window light. Subtle handheld texture, warm practicals, rich period detail, heavy film grain. 0-4s: [Medium Wide] A striking young woman in her early 20s sits alone at the counter, calm and slightly amused, slowly sipping a tall thick milkshake through a straw. Behind her a young waitress in classic uniform approaches with a tray of eggs and bacon in one hand and a full glass coffee pot in the other. An older lady starts rising from a nearby booth. 4-8s: [Dynamic Tracking] The older lady collides hard into the waitress. Tray, plate, eggs, bacon and coffee pot explode upward in chaotic slow motion. Coffee erupts into long liquid ribbons and perfect suspended droplets. Camera immediately begins a smooth continuous orbit around the impact. Time locks completely at the peak of the spill. Every face freezes in pure shock. Only the girl at the counter keeps moving, completely unfazed. 8-17s: [Slow 360° Orbital] Camera glides in a full elegant orbit through the frozen diner. Coffee hangs in mid-air as glassy ribbons and spheres with perfect volume and surface tension. Bacon strips, eggs and the spinning tray float weightlessly. Patrons and waitress remain locked in startled expressions. The girl at the counter takes one slow, deliberate sip, eyes half-lidded, almost bored, while the entire frozen world (except her) begins an elegant reverse: every droplet, every piece of food and every person rewinds smoothly back to the exact starting positions. 17-24s: [Medium Shot] Rewind lands perfectly. Waitress stands balanced again with tray and coffee pot. The girl lifts her eyes, raises two fingers in a small casual gesture and softly calls the waitress by name. The waitress turns toward her just before the older lady begins to stand, completely avoiding the collision. A tiny private smile crosses the girl’s face. 24-30s: [Extreme Close-Up] Hard cut to her face as she takes one last slow sip. Soft knowing smile, eyes almost closed in quiet satisfaction, like she has done this a hundred times. Shallow depth of field, creamy bokeh of the neon diner behind her. Photorealistic, ultra-detailed fluid physics, perfect motion blur only on moving elements, stable characters, cinematic lighting, heavy natural film grain, no artifacts, movie-level temporal coherence, high rewatch value. 30 seconds long is the new AI standard! hope you like it 🫡
0:30

Seedance 2.5 frozen time + rewind effect prompt is below 👇 Photorealistic cinematic 1950s American diner, chrome stools, red vinyl, neon glow and checkerboard floor, shot with modern lived-in realism and soft natural window light. Subtle handheld texture, warm practicals, rich period detail, heavy film grain. 0-4s: [Medium Wide] A striking young woman in her early 20s sits alone at the counter, calm and slightly amused, slowly sipping a tall thick milkshake through a straw. Behind her a young waitress in classic uniform approaches with a tray of eggs and bacon in one hand and a full glass coffee pot in the other. An older lady starts rising from a nearby booth. 4-8s: [Dynamic Tracking] The older lady collides hard into the waitress. Tray, plate, eggs, bacon and coffee pot explode upward in chaotic slow motion. Coffee erupts into long liquid ribbons and perfect suspended droplets. Camera immediately begins a smooth continuous orbit around the impact. Time locks completely at the peak of the spill. Every face freezes in pure shock. Only the girl at the counter keeps moving, completely unfazed. 8-17s: [Slow 360° Orbital] Camera glides in a full elegant orbit through the frozen diner. Coffee hangs in mid-air as glassy ribbons and spheres with perfect volume and surface tension. Bacon strips, eggs and the spinning tray float weightlessly. Patrons and waitress remain locked in startled expressions. The girl at the counter takes one slow, deliberate sip, eyes half-lidded, almost bored, while the entire frozen world (except her) begins an elegant reverse: every droplet, every piece of food and every person rewinds smoothly back to the exact starting positions. 17-24s: [Medium Shot] Rewind lands perfectly. Waitress stands balanced again with tray and coffee pot. The girl lifts her eyes, raises two fingers in a small casual gesture and softly calls the waitress by name. The waitress turns toward her just before the older lady begins to stand, completely avoiding the collision. A tiny private smile crosses the girl’s face. 24-30s: [Extreme Close-Up] Hard cut to her face as she takes one last slow sip. Soft knowing smile, eyes almost closed in quiet satisfaction, like she has done this a hundred times. Shallow depth of field, creamy bokeh of the neon diner behind her. Photorealistic, ultra-detailed fluid physics, perfect motion blur only on moving elements, stable characters, cinematic lighting, heavy natural film grain, no artifacts, movie-level temporal coherence, high rewatch value. 30 seconds long is the new AI standard! hope you like it 🫡

TechHalla

225,404 Aufrufe • vor 1 Monat

The goal wasn’t to make something cinematic. Just make an ordinary day feel real. Made with Seedance 2.5. Prompt: Create a 30-second, 1080p ultra-realistic personal home-video of a young Korean woman confidently claiming she can sing, only to completely fall apart mid-song in a noraebang (karaoke room). No reference image. MAIN SUBJECT Young Korean woman in her early 20s, casual and confident energy, natural makeup that's slightly smudged from a night out, expressive face that goes from cocky to distressed in seconds. Long black hair in loose waves, a claw clip half-holding it up, small hoop earrings catching the disco light. Wearing an oversized denim jacket over a graphic tee, black mini skirt, ankle boots, holding a wireless karaoke mic like it's a real microphone. Maintain the same face, hairstyle, clothing, body proportions, and appearance throughout the entire video. SETTING A small, slightly worn private noraebang room late at night. Neon-colored wall lighting cycling through pink, blue, and purple, a low vinyl couch, a coffee table with empty snack bags and soju/beer cans, a big screen playing a lyrics video with over-the-top visuals, a disco ball casting light spots, a tambourine on the table, a song-selection remote, and mirrored wall panels reflecting the room. Slightly tacky, glowing, chaotic in the best way. CAMERA / VISUAL AESTHETIC Raw personal footage filmed by her friend on a phone, strong handheld vlog shake throughout. Lighting shifts constantly with the neon cycle, causing exposure and color shifts across her face. Autofocus hunts between her face and the flashing screen behind her. Camera swings and dips with the friend's own laughter, mild motion blur during her more dramatic mic-swinging moments, visible digital noise in the dim room, colors slightly oversaturated from the neon wash. No stabilization, no cinematic polish — it should feel like real footage that'll end up in a group chat. 00:00–00:05 — THE CONFIDENT INTRO She grabs the mic with both hands, striking a mock-serious pop-star pose as the intro music starts. She looks dead into the camera, completely deadpan and confident. "Okay watch this. I'm actually good." 00:05–00:10 — STRONG START The first line of the song hits and she nails it — eyes closed, hand on chest, fully committed to the performance. The camera pushes in slightly, genuinely impressed, catching her hitting the note clean. Her friend's voice off-camera: "Okay wait—?!" 00:10–00:15 — THE CRACK The song hits a higher note and her voice visibly strains, cracking halfway through. Her eyes snap open in panic mid-note. She tries to recover by belting harder, which makes it worse. The camera shakes as the friend starts laughing, frame briefly clipping the ceiling. 00:15–00:20 — FULL COLLAPSE She completely loses the melody, mumbling half the lyrics she doesn't know, gesturing wildly with the mic to compensate. She turns away from the camera in embarrassment mid-line, then spins back in for a dramatic (bad) finish, hair flying. The frame overshoots trying to follow her spin, briefly blurring. 00:20–00:25 — GIVING UP She drops onto the couch mid-song, still holding the mic up weakly, mumbling the last few lines into the cushion instead of singing them. The score screen pops up on the TV behind her with a visibly low number. She peeks at the score, winces hard, and covers her face with a couch pillow. 00:25–00:30 — FINAL MOMENT She lowers the pillow slowly, mic still limp in her other hand, and stares into the camera in mock devastation. "...We're never speaking about this again." Her friend, still laughing off-camera, zooms in too close on her defeated face — she weakly swats the lens away — and the footage cuts abruptly to black. AUDIO Natural location sound only: Karaoke backing track playing from the room's speaker (muffled, roomy), her actual singing — strong at first, then cracking and falling apart — her friend's genuine off-camera laughter throughout, mic feedback crackle, couch cushion thud, tambourine jingling faintly when knocked, and handheld camera noise. No added music. No narration. No artificial sound effects. Spoken lines: "Okay watch this. I'm actually good." / "Okay wait—?!" (friend, off-camera) / "...We're never speaking about this again." FINAL FEEL Chaotic, glowing, late-night noraebang energy — the universal experience of confidently starting a karaoke song and immediately regretting every choice that led to that moment. Funny, cringe-in-a-good-way, genuinely unscripted. No polished performance. No actual singing talent required — the comedy comes from the real vocal crack, real panic, and the gap between her confidence and her execution.
0:30

The goal wasn’t to make something cinematic. Just make an ordinary day feel real. Made with Seedance 2.5. Prompt: Create a 30-second, 1080p ultra-realistic personal home-video of a young Korean woman confidently claiming she can sing, only to completely fall apart mid-song in a noraebang (karaoke room). No reference image. MAIN SUBJECT Young Korean woman in her early 20s, casual and confident energy, natural makeup that's slightly smudged from a night out, expressive face that goes from cocky to distressed in seconds. Long black hair in loose waves, a claw clip half-holding it up, small hoop earrings catching the disco light. Wearing an oversized denim jacket over a graphic tee, black mini skirt, ankle boots, holding a wireless karaoke mic like it's a real microphone. Maintain the same face, hairstyle, clothing, body proportions, and appearance throughout the entire video. SETTING A small, slightly worn private noraebang room late at night. Neon-colored wall lighting cycling through pink, blue, and purple, a low vinyl couch, a coffee table with empty snack bags and soju/beer cans, a big screen playing a lyrics video with over-the-top visuals, a disco ball casting light spots, a tambourine on the table, a song-selection remote, and mirrored wall panels reflecting the room. Slightly tacky, glowing, chaotic in the best way. CAMERA / VISUAL AESTHETIC Raw personal footage filmed by her friend on a phone, strong handheld vlog shake throughout. Lighting shifts constantly with the neon cycle, causing exposure and color shifts across her face. Autofocus hunts between her face and the flashing screen behind her. Camera swings and dips with the friend's own laughter, mild motion blur during her more dramatic mic-swinging moments, visible digital noise in the dim room, colors slightly oversaturated from the neon wash. No stabilization, no cinematic polish — it should feel like real footage that'll end up in a group chat. 00:00–00:05 — THE CONFIDENT INTRO She grabs the mic with both hands, striking a mock-serious pop-star pose as the intro music starts. She looks dead into the camera, completely deadpan and confident. "Okay watch this. I'm actually good." 00:05–00:10 — STRONG START The first line of the song hits and she nails it — eyes closed, hand on chest, fully committed to the performance. The camera pushes in slightly, genuinely impressed, catching her hitting the note clean. Her friend's voice off-camera: "Okay wait—?!" 00:10–00:15 — THE CRACK The song hits a higher note and her voice visibly strains, cracking halfway through. Her eyes snap open in panic mid-note. She tries to recover by belting harder, which makes it worse. The camera shakes as the friend starts laughing, frame briefly clipping the ceiling. 00:15–00:20 — FULL COLLAPSE She completely loses the melody, mumbling half the lyrics she doesn't know, gesturing wildly with the mic to compensate. She turns away from the camera in embarrassment mid-line, then spins back in for a dramatic (bad) finish, hair flying. The frame overshoots trying to follow her spin, briefly blurring. 00:20–00:25 — GIVING UP She drops onto the couch mid-song, still holding the mic up weakly, mumbling the last few lines into the cushion instead of singing them. The score screen pops up on the TV behind her with a visibly low number. She peeks at the score, winces hard, and covers her face with a couch pillow. 00:25–00:30 — FINAL MOMENT She lowers the pillow slowly, mic still limp in her other hand, and stares into the camera in mock devastation. "...We're never speaking about this again." Her friend, still laughing off-camera, zooms in too close on her defeated face — she weakly swats the lens away — and the footage cuts abruptly to black. AUDIO Natural location sound only: Karaoke backing track playing from the room's speaker (muffled, roomy), her actual singing — strong at first, then cracking and falling apart — her friend's genuine off-camera laughter throughout, mic feedback crackle, couch cushion thud, tambourine jingling faintly when knocked, and handheld camera noise. No added music. No narration. No artificial sound effects. Spoken lines: "Okay watch this. I'm actually good." / "Okay wait—?!" (friend, off-camera) / "...We're never speaking about this again." FINAL FEEL Chaotic, glowing, late-night noraebang energy — the universal experience of confidently starting a karaoke song and immediately regretting every choice that led to that moment. Funny, cringe-in-a-good-way, genuinely unscripted. No polished performance. No actual singing talent required — the comedy comes from the real vocal crack, real panic, and the gap between her confidence and her execution.

Oogie

27,923 Aufrufe • vor 12 Tagen

Meme Vlog using Seedance 2.5 Prompt: Vertical 9:16 smartphone vlog, shot on iPhone 17 Pro. ONE SINGLE UNINTERRUPTED HANDHELD TAKE, ~30 seconds, no cuts, no editing — every transition happens only through the vlogger panning, tilting, zooming or walking. Brisk, snappy pacing: quick whip pans, each beat lands in a few seconds, the camera never lingers. Sunny daytime New York City street >> — brick facades, fire escapes, a sidewalk café, parked cars. The filming style is the core of the video: natural hand micro-shake and walking bounce, slightly floaty digital stabilization, deep focus with everything sharp — no cinematic bokeh, no film look, no color grading. Natural HDR daylight, sky highlights slightly clipped, auto exposure and white balance visibly re-adjusting on every pan between shade and sun, quick autofocus hunting on fast pans, digital zoom bringing a slight quality drop and extra shake. Audio: raw street ambience only — traffic, distant horns, footsteps, chatter, wind brushing the mic, plus the live sounds written into the scenes. No music track, no captions, no watermark. The vlogger's phone IS the camera — it never appears on screen, and she never holds a second phone or any other device. Spontaneous amateur vlog energy. 0:00–0:05 — Front camera, selfie mode: the vlogger >> films herself at arm's length while walking down the sidewalk, her face a touch overexposed by daylight. She starts excitedly: "Guys! I just—" — behind her shoulder, a couple >>walking the opposite way passes right beside her; a beat later the guy stops and turns back, head over his shoulder, staring straight at her — the exact reference pose — while his girlfriend , gripping his hand, glares at him in outraged disbelief, mouth open. They hold the exact reference tableau; his stare reads odd and unreadable, not flirty. She catches them in her own selfie frame, cuts off mid-word and reacts instantly, without breaking stride: "...What was that?" — and keeps walking. 0:05–0:09 — Same take, no cut: she flips the phone to the rear camera and whips it to the RIGHT — a sidewalk café. By the entrance, a guy >> stands at a microphone on a stand, a small speaker beside it looping a soft instrumental backing. He leans in, takes a breath to sing the first line — and bursts out laughing instead, turning away and covering his mouth, then waves it off and resets toward the mic. The vlogger laughs quietly behind the camera. 0:09–0:13 — Without cutting, the camera slides and zooms further RIGHT along the same café terrace: at one table a woman >> is mid-meltdown — crying, shouting, jabbing an accusing finger across the terrace — while her friend >> leans in, holding her back. Quick punch-in digital zoom to the opposite table: the cat >> sits upright behind a plate of salad, perfectly calm and unimpressed. Autofocus hunts for a split second on the zoom. 0:13–0:17 — Without cutting, the camera TILTS UP the facade directly above the café awning: a second-floor open window of the same brick building, a fire escape beside it. Quick digital zoom in — the image gets slightly softer and shakier — the dog >> sits in the window with its eyes closed, chin lifted, blissfully soaking up the warm golden sunlight hitting the facade. She melts behind the camera: "Awww, look at him..." 0:17–0:21 — The camera drops back down and swings FORWARD — a few steps ahead of her on the same sidewalk stands a couple in office attire, mid-argument. The guy >> leans in toward the woman, talking heatedly, both hands raised mid-gesture; the woman >> doesn't even glance at him — she smiles down at the phone in her hand, her other arm extended toward his face, flat palm raised in a firm "stop, talk to the hand" gesture, exactly matching the reference poses. The vlogger steps around them, the camera holding on the pair as she half-laughs: "What is going on?" 0:21–0:25 — Same take: she whips the camera to the LEFT, across the two-lane road — a sedan parked at the opposite curb. Shaky digital zoom onto the driver's window: a man >> sits behind the wheel, one hand draped over the top of the steering wheel, staring straight into the lens with a heavy, unblinking suspicious look, his eyes slowly tracking her as she passes. She says flatly: "...What is his problem?" 0:25–0:30 — The camera swings back forward: ahead at the corner of the block, a guy >> stands in profile by a red brick wall, heatedly arguing with the wall itself — both hands gesturing, leaning in, making his case to the bricks like a real debate. Quick shaky digital zoom toward him as she approaches, his agitated voice rising under the street noise. She flips to the front camera — her speechless, wide-eyed face fills the frame — then flips back to the rear camera: he's still going at it. The take ends mid-argument, no cut.
0:30

Meme Vlog using Seedance 2.5 Prompt: Vertical 9:16 smartphone vlog, shot on iPhone 17 Pro. ONE SINGLE UNINTERRUPTED HANDHELD TAKE, ~30 seconds, no cuts, no editing — every transition happens only through the vlogger panning, tilting, zooming or walking. Brisk, snappy pacing: quick whip pans, each beat lands in a few seconds, the camera never lingers. Sunny daytime New York City street >> — brick facades, fire escapes, a sidewalk café, parked cars. The filming style is the core of the video: natural hand micro-shake and walking bounce, slightly floaty digital stabilization, deep focus with everything sharp — no cinematic bokeh, no film look, no color grading. Natural HDR daylight, sky highlights slightly clipped, auto exposure and white balance visibly re-adjusting on every pan between shade and sun, quick autofocus hunting on fast pans, digital zoom bringing a slight quality drop and extra shake. Audio: raw street ambience only — traffic, distant horns, footsteps, chatter, wind brushing the mic, plus the live sounds written into the scenes. No music track, no captions, no watermark. The vlogger's phone IS the camera — it never appears on screen, and she never holds a second phone or any other device. Spontaneous amateur vlog energy. 0:00–0:05 — Front camera, selfie mode: the vlogger >> films herself at arm's length while walking down the sidewalk, her face a touch overexposed by daylight. She starts excitedly: "Guys! I just—" — behind her shoulder, a couple >>walking the opposite way passes right beside her; a beat later the guy stops and turns back, head over his shoulder, staring straight at her — the exact reference pose — while his girlfriend , gripping his hand, glares at him in outraged disbelief, mouth open. They hold the exact reference tableau; his stare reads odd and unreadable, not flirty. She catches them in her own selfie frame, cuts off mid-word and reacts instantly, without breaking stride: "...What was that?" — and keeps walking. 0:05–0:09 — Same take, no cut: she flips the phone to the rear camera and whips it to the RIGHT — a sidewalk café. By the entrance, a guy >> stands at a microphone on a stand, a small speaker beside it looping a soft instrumental backing. He leans in, takes a breath to sing the first line — and bursts out laughing instead, turning away and covering his mouth, then waves it off and resets toward the mic. The vlogger laughs quietly behind the camera. 0:09–0:13 — Without cutting, the camera slides and zooms further RIGHT along the same café terrace: at one table a woman >> is mid-meltdown — crying, shouting, jabbing an accusing finger across the terrace — while her friend >> leans in, holding her back. Quick punch-in digital zoom to the opposite table: the cat >> sits upright behind a plate of salad, perfectly calm and unimpressed. Autofocus hunts for a split second on the zoom. 0:13–0:17 — Without cutting, the camera TILTS UP the facade directly above the café awning: a second-floor open window of the same brick building, a fire escape beside it. Quick digital zoom in — the image gets slightly softer and shakier — the dog >> sits in the window with its eyes closed, chin lifted, blissfully soaking up the warm golden sunlight hitting the facade. She melts behind the camera: "Awww, look at him..." 0:17–0:21 — The camera drops back down and swings FORWARD — a few steps ahead of her on the same sidewalk stands a couple in office attire, mid-argument. The guy >> leans in toward the woman, talking heatedly, both hands raised mid-gesture; the woman >> doesn't even glance at him — she smiles down at the phone in her hand, her other arm extended toward his face, flat palm raised in a firm "stop, talk to the hand" gesture, exactly matching the reference poses. The vlogger steps around them, the camera holding on the pair as she half-laughs: "What is going on?" 0:21–0:25 — Same take: she whips the camera to the LEFT, across the two-lane road — a sedan parked at the opposite curb. Shaky digital zoom onto the driver's window: a man >> sits behind the wheel, one hand draped over the top of the steering wheel, staring straight into the lens with a heavy, unblinking suspicious look, his eyes slowly tracking her as she passes. She says flatly: "...What is his problem?" 0:25–0:30 — The camera swings back forward: ahead at the corner of the block, a guy >> stands in profile by a red brick wall, heatedly arguing with the wall itself — both hands gesturing, leaning in, making his case to the bricks like a real debate. Quick shaky digital zoom toward him as she approaches, his agitated voice rising under the street noise. She flips to the front camera — her speechless, wide-eyed face fills the frame — then flips back to the rear camera: he's still going at it. The take ends mid-argument, no cut.

Oogie

45,086 Aufrufe • vor 13 Tagen

Seedance 2.5 vs WAN 3.0 - same viral video One of them is dead in the water - You judge Prompt: Handheld digital camcorder aesthetic, landscape framing. A gorgeous fitness and food influencer films herself by hand in selfie-cam and first-person style while cooking a late-night high-protein meal after training and a shower. Keep realistic hand shake, slightly crooked framing, autofocus briefly hunting between her face and the food, awkward zoom-ins onto the pan, occasional motion blur, brief lens steam-up over the hot pan that clears naturally, and small framing mistakes where her face or the pan edge slips out of frame. Mix handheld selfie footage with a few fixed external shots. Important: never show her placing, adjusting, or setting up a camera. When switching from handheld footage to a fixed external angle, use a clean jump cut as if the camera had already been positioned before the shot began. The camera itself must never appear on screen or in the window reflection. LOOK: Warm late-night kitchen light. A single warm pendant over the counter, cool blue night visible through the window behind her, under-cabinet strip light glowing on the backsplash. Slight camcorder softness, faint noise in the shadows, mild bloom on the pendant. Food realism is the core of the look: real sizzle with fine oil spatter, steam rising and curling from the pan, honest food textures with sear marks and glistening surfaces, knife cuts that separate cleanly, droplets on rinsed vegetables. Realistic skin texture, fresh-from-the-shower glow, clean dewy skin, realistic skin tones. STYLE: A realistic late-night what-I-eat-after-training vlog. The tone is relaxed, hungry, funny, quietly confident, and natural, talking to the lens like a friend while her hands keep working. She is clearly attractive and charismatic, but the video must feel like a believable self-recorded kitchen vlog, not a food commercial. Fast clean jump cuts, strong continuity, natural body language, real kitchen sounds, sizzle, chopping, no awkward dead moments. CHARACTER: The woman in the reference image. Her face, features, skin tone, body, and clothing must match the reference image exactly in every shot — she wears exactly what she is wearing in the reference image. Do not restyle, beautify, or alter her in any way beyond the reference. The one addition: a soft white towel wrapped around her head like a turban, as if she just stepped out of the shower. The towel stays neatly wrapped for the whole video. A few small damp strands of hair may peek out at the hairline and neck. Minimal or no makeup, fresh clean post-shower look. A small kitchen towel over one shoulder for most of the video. SETTING: A small warm real apartment kitchen at night. Wooden counter with knife marks, a gas hob with one cast-iron pan, a cutting board with chicken breast and vegetables, a bowl of cooked rice, a bottle of olive oil, salt in a small dish, a fridge with magnets and photos, dishes drying on a rack, dark window over the sink reflecting the warm kitchen. Lived-in and slightly cluttered. No other people, no pets. IMPORTANT CONTINUITY RULES: The same woman from the reference image must remain fully consistent in every shot. No face changes, no outfit changes, no body changes. The head towel stays wrapped in the same position in every shot — it never unwraps, falls, changes color, or disappears. The meal progresses in one direction only: raw ingredients, then chopping, then searing, then plating, then eating, and never reverses or regenerates. Food already cooked never becomes raw again. Hands and knife are the top priority: five fingers always, correct knife grip with curled guiding fingers, clean cuts, the knife never bends and never passes through her hand. The pan, board, oil bottle and rice bowl stay in the same positions. Steam and sizzle must behave with real physics. No extra people, including in the dark window reflection, and the reflection never shows a camera. No duplicated limbs. No camera visible. No camera setup shown. Keep her matching the reference image, warm, and photogenic in every shot. STORYBOARD: 30 seconds total, 10 cuts. (~3s, arm's-length selfie) She leans on the counter, towel wrapped on her head, clearly fresh from the shower after training, and grins tiredly at the lens. Dialogue: "Trained late. Showered. Starving. Let's cook." (~3s, handheld pan across the counter and back to her) The camera drifts across the board with raw chicken and vegetables, the pan, the rice bowl, then back up to her face. Dialogue: "Ten minute meal. Watch." (~3s, fixed external medium shot from across the counter) Jump cut. She is already chopping a red pepper with quick confident cuts, guiding fingers curled, pieces falling evenly. No camera setup shown. No dialogue, just the knife on the board. (~3s, same fixed shot) She slices the chicken breast into strips, seasons it from the salt dish with a high pinch, and rubs it in with her fingertips. Dialogue: "Protein first. Always." (~3s, tight handheld first-person shot over the pan) Oil shimmering, she lays the chicken strips in one by one and they hit with a loud real sizzle, fine spatter, steam rising into the lens which fogs for a beat and clears. No dialogue, just the sizzle. (~3s, handheld selfie while the pan sizzles behind her) She turns the camera on herself, fanning steam away from her face, laughing, one hand briefly steadying the head towel. Dialogue: "The smell. You have no idea." (~3s, tight handheld close-up of the pan) She flips the strips with tongs, showing deep golden sear marks, tosses in the peppers, and shakes the pan once so everything jumps and resettles. Dialogue: "That colour? That's the whole point." (~3s, fixed external shot) Jump cut. She plates it: rice pressed from the bowl, chicken and peppers over the top, a last drizzle of olive oil in a thin ribbon, and she wipes the plate rim with the towel like a chef, then smirks at her own seriousness. Dialogue: "Yes, I wiped the rim. Let me live." (~3s, tight handheld close-up) First fork bite, steam still coming off it, she chews, closes her eyes for a beat and nods slowly. Dialogue: "Ten minutes. That's it. Ridiculous." (~3s, arm's-length selfie ending) Plate in one hand, camera in the other, she backs out of the kitchen toward the sofa, flicking the kitchen light off with her elbow. Dialogue: "Okay. Eating. Good night." FINAL INSTRUCTION: The result must feel like a real self-recorded late-night cooking vlog by an athlete who actually cooks, filmed right after her shower. The highest priorities are matching the reference image exactly, correct hands and knife work at close range, one-directional cooking progression that never reverses, real sizzle, steam and food texture, the head towel staying consistently wrapped, honest warm kitchen light against the dark window, and subtle imperfection. Keep it warm, hungry, and real. Not a food commercial, not overhead recipe content, not stiff.
0:30

Seedance 2.5 vs WAN 3.0 - same viral video One of them is dead in the water - You judge Prompt: Handheld digital camcorder aesthetic, landscape framing. A gorgeous fitness and food influencer films herself by hand in selfie-cam and first-person style while cooking a late-night high-protein meal after training and a shower. Keep realistic hand shake, slightly crooked framing, autofocus briefly hunting between her face and the food, awkward zoom-ins onto the pan, occasional motion blur, brief lens steam-up over the hot pan that clears naturally, and small framing mistakes where her face or the pan edge slips out of frame. Mix handheld selfie footage with a few fixed external shots. Important: never show her placing, adjusting, or setting up a camera. When switching from handheld footage to a fixed external angle, use a clean jump cut as if the camera had already been positioned before the shot began. The camera itself must never appear on screen or in the window reflection. LOOK: Warm late-night kitchen light. A single warm pendant over the counter, cool blue night visible through the window behind her, under-cabinet strip light glowing on the backsplash. Slight camcorder softness, faint noise in the shadows, mild bloom on the pendant. Food realism is the core of the look: real sizzle with fine oil spatter, steam rising and curling from the pan, honest food textures with sear marks and glistening surfaces, knife cuts that separate cleanly, droplets on rinsed vegetables. Realistic skin texture, fresh-from-the-shower glow, clean dewy skin, realistic skin tones. STYLE: A realistic late-night what-I-eat-after-training vlog. The tone is relaxed, hungry, funny, quietly confident, and natural, talking to the lens like a friend while her hands keep working. She is clearly attractive and charismatic, but the video must feel like a believable self-recorded kitchen vlog, not a food commercial. Fast clean jump cuts, strong continuity, natural body language, real kitchen sounds, sizzle, chopping, no awkward dead moments. CHARACTER: The woman in the reference image. Her face, features, skin tone, body, and clothing must match the reference image exactly in every shot — she wears exactly what she is wearing in the reference image. Do not restyle, beautify, or alter her in any way beyond the reference. The one addition: a soft white towel wrapped around her head like a turban, as if she just stepped out of the shower. The towel stays neatly wrapped for the whole video. A few small damp strands of hair may peek out at the hairline and neck. Minimal or no makeup, fresh clean post-shower look. A small kitchen towel over one shoulder for most of the video. SETTING: A small warm real apartment kitchen at night. Wooden counter with knife marks, a gas hob with one cast-iron pan, a cutting board with chicken breast and vegetables, a bowl of cooked rice, a bottle of olive oil, salt in a small dish, a fridge with magnets and photos, dishes drying on a rack, dark window over the sink reflecting the warm kitchen. Lived-in and slightly cluttered. No other people, no pets. IMPORTANT CONTINUITY RULES: The same woman from the reference image must remain fully consistent in every shot. No face changes, no outfit changes, no body changes. The head towel stays wrapped in the same position in every shot — it never unwraps, falls, changes color, or disappears. The meal progresses in one direction only: raw ingredients, then chopping, then searing, then plating, then eating, and never reverses or regenerates. Food already cooked never becomes raw again. Hands and knife are the top priority: five fingers always, correct knife grip with curled guiding fingers, clean cuts, the knife never bends and never passes through her hand. The pan, board, oil bottle and rice bowl stay in the same positions. Steam and sizzle must behave with real physics. No extra people, including in the dark window reflection, and the reflection never shows a camera. No duplicated limbs. No camera visible. No camera setup shown. Keep her matching the reference image, warm, and photogenic in every shot. STORYBOARD: 30 seconds total, 10 cuts. (~3s, arm's-length selfie) She leans on the counter, towel wrapped on her head, clearly fresh from the shower after training, and grins tiredly at the lens. Dialogue: "Trained late. Showered. Starving. Let's cook." (~3s, handheld pan across the counter and back to her) The camera drifts across the board with raw chicken and vegetables, the pan, the rice bowl, then back up to her face. Dialogue: "Ten minute meal. Watch." (~3s, fixed external medium shot from across the counter) Jump cut. She is already chopping a red pepper with quick confident cuts, guiding fingers curled, pieces falling evenly. No camera setup shown. No dialogue, just the knife on the board. (~3s, same fixed shot) She slices the chicken breast into strips, seasons it from the salt dish with a high pinch, and rubs it in with her fingertips. Dialogue: "Protein first. Always." (~3s, tight handheld first-person shot over the pan) Oil shimmering, she lays the chicken strips in one by one and they hit with a loud real sizzle, fine spatter, steam rising into the lens which fogs for a beat and clears. No dialogue, just the sizzle. (~3s, handheld selfie while the pan sizzles behind her) She turns the camera on herself, fanning steam away from her face, laughing, one hand briefly steadying the head towel. Dialogue: "The smell. You have no idea." (~3s, tight handheld close-up of the pan) She flips the strips with tongs, showing deep golden sear marks, tosses in the peppers, and shakes the pan once so everything jumps and resettles. Dialogue: "That colour? That's the whole point." (~3s, fixed external shot) Jump cut. She plates it: rice pressed from the bowl, chicken and peppers over the top, a last drizzle of olive oil in a thin ribbon, and she wipes the plate rim with the towel like a chef, then smirks at her own seriousness. Dialogue: "Yes, I wiped the rim. Let me live." (~3s, tight handheld close-up) First fork bite, steam still coming off it, she chews, closes her eyes for a beat and nods slowly. Dialogue: "Ten minutes. That's it. Ridiculous." (~3s, arm's-length selfie ending) Plate in one hand, camera in the other, she backs out of the kitchen toward the sofa, flicking the kitchen light off with her elbow. Dialogue: "Okay. Eating. Good night." FINAL INSTRUCTION: The result must feel like a real self-recorded late-night cooking vlog by an athlete who actually cooks, filmed right after her shower. The highest priorities are matching the reference image exactly, correct hands and knife work at close range, one-directional cooking progression that never reverses, real sizzle, steam and food texture, the head towel staying consistently wrapped, honest warm kitchen light against the dark window, and subtle imperfection. Keep it warm, hungry, and real. Not a food commercial, not overhead recipe content, not stiff.

Stav Zilbershtein

29,730 Aufrufe • vor 16 Tagen

Tried Seedance 2.5 on VideoDuck AI for this short action film. Door's locked? Not for long. One exhausted man, a building full of cartel muscle, and a boss in white waiting at the top. He's not leaving till it's empty. PROMPT: Hero = a rugged battle-hardened man around 35, weathered face, dark stubble, a brow cut, a dirty white tank-top vest, worn dark trousers and boots, dirt and grime. Fierce, exhausted, unbroken. Appearance only. Gang1 = a squad of rugged cartel henchmen in dirty casual clothes, unshaven and mean, armed with machetes. Appearance only. Gang2 = cartel enforcers in dark tailored suits, disciplined and armed with blades. Appearance only. Boss = a cartel boss around 45, sharp cold face, slicked-back greying hair, a trimmed beard, an immaculate white suit with a dark shirt. Powerful and menacing. Appearance only. Building = a rundown abandoned cartel hideout at dusk — a grimy derelict concrete building, a battered entrance door, a dim gritty ground floor with peeling walls, bare bulbs, debris and a staircase at the back, and a moody upper floor with tall grimy windows and shafts of dim light. Desaturated gritty grey-brown palette. Environment only. SCENE: a gritty one-man-army action sequence. A rugged exhausted man in a dirty white vest kicks in the door of an abandoned cartel hideout and fights his way through a machete-armed gang on the ground floor, then climbs to the upper floor where suited enforcers and their white-suited boss wait. He takes down the enforcers and defeats the boss in a final duel, standing victorious. Intense, raw, cinematic martial-arts action. TECHNICAL: 16:9, cinematic gritty desaturated grey action grade, dynamic handheld fight camera, low moody light, dust and haze, fine film grain, photorealistic raw action quality. CUTS: CUT 1 (0-5s): The man walks up to the grimy building at dusk, shouts "Come out!", and kicks the door in — storming into the dim ground floor where machete-armed henchmen ready their weapons. CUT 2 (5-12s): The fight erupts — brutal fast hand-to-hand combat, he dodges machete swings, disarms and takes down the whole squad one by one across the gritty room, using pillars and furniture. Dynamic changing angles. CUT 3 (12-17s): The room cleared, he strides to the staircase and climbs to the upper floor — where a squad of suited enforcers and the white-suited boss behind them are waiting. A tense standoff. CUT 4 (17-24s): The enforcers attack; he fights them down in fast fierce combat until only the boss remains. The two face off across the light-shafted room, breathing hard. CUT 5 (24-30s): The final duel — hero and boss clash in an intense one-on-one, trading heavy blows, until the hero lands a decisive final blow and the boss drops to the floor, beaten. The hero stands over him, victorious, in a shaft of dim light. Epic final hero frame. END. RULES: References are appearance only, do not recreate. Keep the hero's face and white vest, and the boss's white suit, consistent across every cut. Action is intense but NOT gory — enemies are beaten and drop, no blood, no graphic killing, impacts sold through motion and body mechanics. Gritty desaturated grade throughout. Sound design: the door bursting, brutal impact hits, grunts, a tense standoff beat, a driving action score peaking at the final blow, gritty ambience. Final hero frame stable and clean.
0:30

Tried Seedance 2.5 on VideoDuck AI for this short action film. Door's locked? Not for long. One exhausted man, a building full of cartel muscle, and a boss in white waiting at the top. He's not leaving till it's empty. PROMPT: Hero = a rugged battle-hardened man around 35, weathered face, dark stubble, a brow cut, a dirty white tank-top vest, worn dark trousers and boots, dirt and grime. Fierce, exhausted, unbroken. Appearance only. Gang1 = a squad of rugged cartel henchmen in dirty casual clothes, unshaven and mean, armed with machetes. Appearance only. Gang2 = cartel enforcers in dark tailored suits, disciplined and armed with blades. Appearance only. Boss = a cartel boss around 45, sharp cold face, slicked-back greying hair, a trimmed beard, an immaculate white suit with a dark shirt. Powerful and menacing. Appearance only. Building = a rundown abandoned cartel hideout at dusk — a grimy derelict concrete building, a battered entrance door, a dim gritty ground floor with peeling walls, bare bulbs, debris and a staircase at the back, and a moody upper floor with tall grimy windows and shafts of dim light. Desaturated gritty grey-brown palette. Environment only. SCENE: a gritty one-man-army action sequence. A rugged exhausted man in a dirty white vest kicks in the door of an abandoned cartel hideout and fights his way through a machete-armed gang on the ground floor, then climbs to the upper floor where suited enforcers and their white-suited boss wait. He takes down the enforcers and defeats the boss in a final duel, standing victorious. Intense, raw, cinematic martial-arts action. TECHNICAL: 16:9, cinematic gritty desaturated grey action grade, dynamic handheld fight camera, low moody light, dust and haze, fine film grain, photorealistic raw action quality. CUTS: CUT 1 (0-5s): The man walks up to the grimy building at dusk, shouts "Come out!", and kicks the door in — storming into the dim ground floor where machete-armed henchmen ready their weapons. CUT 2 (5-12s): The fight erupts — brutal fast hand-to-hand combat, he dodges machete swings, disarms and takes down the whole squad one by one across the gritty room, using pillars and furniture. Dynamic changing angles. CUT 3 (12-17s): The room cleared, he strides to the staircase and climbs to the upper floor — where a squad of suited enforcers and the white-suited boss behind them are waiting. A tense standoff. CUT 4 (17-24s): The enforcers attack; he fights them down in fast fierce combat until only the boss remains. The two face off across the light-shafted room, breathing hard. CUT 5 (24-30s): The final duel — hero and boss clash in an intense one-on-one, trading heavy blows, until the hero lands a decisive final blow and the boss drops to the floor, beaten. The hero stands over him, victorious, in a shaft of dim light. Epic final hero frame. END. RULES: References are appearance only, do not recreate. Keep the hero's face and white vest, and the boss's white suit, consistent across every cut. Action is intense but NOT gory — enemies are beaten and drop, no blood, no graphic killing, impacts sold through motion and body mechanics. Gritty desaturated grade throughout. Sound design: the door bursting, brutal impact hits, grunts, a tense standoff beat, a driving action score peaking at the final blow, gritty ambience. Final hero frame stable and clean.

Aaliyah | AI

59,962 Aufrufe • vor 9 Tagen

🚨 BERLIN JUST SPENT €3.9 MILLION ON AI CAMERAS THAT SCAN HOW YOU MOVE. AN ARTIST BUILT AN $88 SHIRT THAT MAKES THE SOFTWARE STOP SEEING A PERSON. About 30 cameras went up at Kottbusser Tor this month, the first permanent AI surveillance of public space in Berlin outside the subway. Third German city to do it, after Mannheim and Hamburg. It isn't face recognition, which is the part everyone gets wrong. The software turns every person in frame into a skeleton, a bundle of moving vectors, then scans those vectors for movements the police defined in advance as suspicious. Lying down. Falling. Staggering. Kicking. Hitting. Cross the threshold and it alarms a human operator, who pulls up the real video and decides whether to send anyone. Officials sold this as privacy-friendly on the grounds that you're only ever a stick figure to it. Police say the software comes from a firm called Adesso. Simon Weckert, a Berlin artist, read all that and made a shirt. It's loud, covered in pink and orange and green blobs, the kind of thing your uncle wears to a barbecue thinking he looks great. Point a detector at Weckert in normal clothes and it draws a green box around him labeled "person." He holds the shirt up to his chest and the box vanishes. Object detection never learned what a human is. It learned what humans statistically look like across millions of labeled photos: sharp edges, contrast, the head-and-shoulders silhouette, limbs in the right proportion to a torso, an outline that stays continuous against whatever's behind it. Weckert's pattern floods those early layers with saturated noise and shatters the outline into pieces, and the model's confidence that anyone is standing there drops below the threshold where it bothers drawing a box. He found the pattern by running a generative model in a loop against the detector until it surfaced the blind spot. The AI taught the shirt how to hide from AI. The print runs unbroken across the buttons and seams, so a fold or a turn doesn't kill it. That was the flaw in earlier adversarial patches, which stopped working the second the fabric bunched. Then there's the law, which is where this gets strange. Germany bans covering your face at public gatherings. This shirt covers nothing. Your face is fully visible to any officer standing in front of you, and to anyone reviewing the footage later. The statute governs what people can see. It says nothing about what a neural network can. The technology also has a record. Hamburg tested the same class of behavior scanner and the police report showed roughly 1,400 alerts in two months, of which eleven were police-relevant. An earlier three-month run threw over a thousand alarms, about one every hour. One percent mattered to police. 0.1 percent mattered to a criminal case. Weckert doesn't oversell it. He's said plainly that no pattern beats every camera and that this isn't a tool for evading police. A system nobody outside the police can independently test is now reading a public square 24 hours a day, and $88 of printed polyester turns it off.
0:55

🚨 BERLIN JUST SPENT €3.9 MILLION ON AI CAMERAS THAT SCAN HOW YOU MOVE. AN ARTIST BUILT AN $88 SHIRT THAT MAKES THE SOFTWARE STOP SEEING A PERSON. About 30 cameras went up at Kottbusser Tor this month, the first permanent AI surveillance of public space in Berlin outside the subway. Third German city to do it, after Mannheim and Hamburg. It isn't face recognition, which is the part everyone gets wrong. The software turns every person in frame into a skeleton, a bundle of moving vectors, then scans those vectors for movements the police defined in advance as suspicious. Lying down. Falling. Staggering. Kicking. Hitting. Cross the threshold and it alarms a human operator, who pulls up the real video and decides whether to send anyone. Officials sold this as privacy-friendly on the grounds that you're only ever a stick figure to it. Police say the software comes from a firm called Adesso. Simon Weckert, a Berlin artist, read all that and made a shirt. It's loud, covered in pink and orange and green blobs, the kind of thing your uncle wears to a barbecue thinking he looks great. Point a detector at Weckert in normal clothes and it draws a green box around him labeled "person." He holds the shirt up to his chest and the box vanishes. Object detection never learned what a human is. It learned what humans statistically look like across millions of labeled photos: sharp edges, contrast, the head-and-shoulders silhouette, limbs in the right proportion to a torso, an outline that stays continuous against whatever's behind it. Weckert's pattern floods those early layers with saturated noise and shatters the outline into pieces, and the model's confidence that anyone is standing there drops below the threshold where it bothers drawing a box. He found the pattern by running a generative model in a loop against the detector until it surfaced the blind spot. The AI taught the shirt how to hide from AI. The print runs unbroken across the buttons and seams, so a fold or a turn doesn't kill it. That was the flaw in earlier adversarial patches, which stopped working the second the fabric bunched. Then there's the law, which is where this gets strange. Germany bans covering your face at public gatherings. This shirt covers nothing. Your face is fully visible to any officer standing in front of you, and to anyone reviewing the footage later. The statute governs what people can see. It says nothing about what a neural network can. The technology also has a record. Hamburg tested the same class of behavior scanner and the police report showed roughly 1,400 alerts in two months, of which eleven were police-relevant. An earlier three-month run threw over a thousand alarms, about one every hour. One percent mattered to police. 0.1 percent mattered to a criminal case. Weckert doesn't oversell it. He's said plainly that no pattern beats every camera and that this isn't a tool for evading police. A system nobody outside the police can independently test is now reading a public square 24 hours a day, and $88 of printed polyester turns it off.

Evan Luthra

35,968 Aufrufe • vor 12 Tagen

Catch Me If You Can, A journey that never stops. Created with Seedance 2.5. Prompt: Create a 30-second, 9:16 photoreal cinematic travel-fashion film, 24fps, following the exact same woman from the supplied character reference. Preserve her face, freckles, dark hair, skin tone, body proportions and natural beauty perfectly throughout. She must look like a real person filmed on location—real skin pores, individual hair strands, natural expressions and realistic anatomy. She always wears white wired earphones. No dialogue. STORY — “CATCH ME IF YOU CAN” 0–4s — CITY HOOK Rain-wet city street, cool cinematic daylight. 24mm intimate close-up. She stands inches from camera, gives a playful knowing smile, then suddenly turns and runs. Camera immediately chases her handheld. A red city bus crosses extremely close and completely covers frame → perfect practical wipe transition. 4–8s — OLD MARKET Same running stride continues seamlessly into a beautiful atmospheric old-town market. Cream jacket, olive loose trousers. Real pedestrians, bicycles, textured stone, warm shops. She looks back laughing while running, then jumps across a puddle. Camera dives toward the splash → water fills frame. 8–12s — MOUNTAIN REVEAL Splash match-cuts into the reflective floor of a glass elevator. She enters; doors close, then immediately reopen onto a breathtaking enormous mountain valley above clouds. She smiles back at camera and runs outside. Cool mist, huge atmospheric depth, realistic wind. 12–16s — COAST Match her exact running stride onto a spectacular golden-hour coastal road. Deep-red track jacket, denim, ocean and cliffside architecture behind. Camera tracks beside her. She spins naturally, laughs, removes her red jacket while moving and throws it directly into lens → red fabric completely covers frame. 16–20s — NEON NIGHT Fabric clears into a rain-soaked neon city at night. Black leather jacket. Deep cinematic blacks, cyan reflections, controlled red practical lights, steam and natural crowds. She confidently walks toward camera. A passing tram completely blocks frame → occlusion transition. 20–23s — ABOVE THE CLOUDS Tram windows match-cut into a mountain cable-car window. Navy jacket. She stands against the glass overlooking gigantic mist-covered peaks. Music briefly becomes quiet. Her reflection overlays the landscape. She notices camera in the reflection, smiles mischievously, then suddenly exits frame. Camera whip-pans after her. 23–26s — WE LOSE HER Whip resolves into a huge lively blue-hour plaza. Camera urgently searches through real moving crowds. She appears for a moment, disappears behind pedestrians, then vanishes completely. Music drops almost to silence. Suddenly someone taps the camera from behind. Fast whip around—she is standing behind us with her female friend, both laughing. Beat drops hard and they run away together. 26–30s — HERO ENDING Camera chases both girls across the spectacular plaza. They hold hands, run, spin and laugh naturally. A flock of pigeons lifts ahead of them. Camera catches up as they turn back and throw their arms up. At 27.8s introduce huge premium warm-ivory condensed typography: CATCH ME then: IF YOU CAN. Characters naturally overlap parts of the letters for realistic depth. No glow, gradients or cheap animation—clean theatrical movie-title design. Lead runs directly toward camera, laughing, then covers the lens with her hand. Hard cut to black exactly on the final beat. CINEMATIC LOOK Feature-film-level cinematography: 24mm chase shots, 35mm movement, 50mm portraits, natural handheld micro-movement, 180° shutter and realistic motion blur. Fine 35mm film grain, subtle highlight halation, soft cinematic bloom and expensive highlight roll-off. Color progression: cool rainy city → warm earthy market → cyan misty mountains → golden coast → deep cyan/red neon → cool mountain atmosphere → rich cinematic blue-hour finale. Keep natural warm skin throughout. TRANSITION RULE Every transition must be physically motivated: bus wipe → water splash → elevator doors → jacket wipe → tram wipe → reflection/whip → crowd reveal → hand-to-lens ending. Never visibly morph locations. No portals, liquid AI transformations, speed ramps, floating cameras or impossible movements. Cuts should be so clean viewers replay them to understand how they happened. REALISM LOCK Same exact lead identity throughout. Real skin texture, correct hands, natural running, realistic footsteps, weighted hair and clothing, earphone cable bouncing with movement, physically correct reflections and splashes. Background people move independently and never freeze or duplicate. No warped architecture, plastic skin, beauty-filter face or AI look. MUSIC / SOUND Original 120 BPM premium cinematic-electronic travel track synchronized tightly to every transition. Start with minimal bass and crisp percussion, build through the chase, open into an uplifting melodic hook at the coast, become deeper at neon night, strip down during the cable-car/crowd search, then massive satisfying beat drop at the friend reveal and strongest musical section for the final run. Layer realistic footsteps, traffic, splash, elevator ding, wind, tram rumble, cable-car hum, crowd ambience, fabric movement, pigeon wings and genuine laughter. No dialogue. No voiceover. No lyrics.
0:30

Catch Me If You Can, A journey that never stops. Created with Seedance 2.5. Prompt: Create a 30-second, 9:16 photoreal cinematic travel-fashion film, 24fps, following the exact same woman from the supplied character reference. Preserve her face, freckles, dark hair, skin tone, body proportions and natural beauty perfectly throughout. She must look like a real person filmed on location—real skin pores, individual hair strands, natural expressions and realistic anatomy. She always wears white wired earphones. No dialogue. STORY — “CATCH ME IF YOU CAN” 0–4s — CITY HOOK Rain-wet city street, cool cinematic daylight. 24mm intimate close-up. She stands inches from camera, gives a playful knowing smile, then suddenly turns and runs. Camera immediately chases her handheld. A red city bus crosses extremely close and completely covers frame → perfect practical wipe transition. 4–8s — OLD MARKET Same running stride continues seamlessly into a beautiful atmospheric old-town market. Cream jacket, olive loose trousers. Real pedestrians, bicycles, textured stone, warm shops. She looks back laughing while running, then jumps across a puddle. Camera dives toward the splash → water fills frame. 8–12s — MOUNTAIN REVEAL Splash match-cuts into the reflective floor of a glass elevator. She enters; doors close, then immediately reopen onto a breathtaking enormous mountain valley above clouds. She smiles back at camera and runs outside. Cool mist, huge atmospheric depth, realistic wind. 12–16s — COAST Match her exact running stride onto a spectacular golden-hour coastal road. Deep-red track jacket, denim, ocean and cliffside architecture behind. Camera tracks beside her. She spins naturally, laughs, removes her red jacket while moving and throws it directly into lens → red fabric completely covers frame. 16–20s — NEON NIGHT Fabric clears into a rain-soaked neon city at night. Black leather jacket. Deep cinematic blacks, cyan reflections, controlled red practical lights, steam and natural crowds. She confidently walks toward camera. A passing tram completely blocks frame → occlusion transition. 20–23s — ABOVE THE CLOUDS Tram windows match-cut into a mountain cable-car window. Navy jacket. She stands against the glass overlooking gigantic mist-covered peaks. Music briefly becomes quiet. Her reflection overlays the landscape. She notices camera in the reflection, smiles mischievously, then suddenly exits frame. Camera whip-pans after her. 23–26s — WE LOSE HER Whip resolves into a huge lively blue-hour plaza. Camera urgently searches through real moving crowds. She appears for a moment, disappears behind pedestrians, then vanishes completely. Music drops almost to silence. Suddenly someone taps the camera from behind. Fast whip around—she is standing behind us with her female friend, both laughing. Beat drops hard and they run away together. 26–30s — HERO ENDING Camera chases both girls across the spectacular plaza. They hold hands, run, spin and laugh naturally. A flock of pigeons lifts ahead of them. Camera catches up as they turn back and throw their arms up. At 27.8s introduce huge premium warm-ivory condensed typography: CATCH ME then: IF YOU CAN. Characters naturally overlap parts of the letters for realistic depth. No glow, gradients or cheap animation—clean theatrical movie-title design. Lead runs directly toward camera, laughing, then covers the lens with her hand. Hard cut to black exactly on the final beat. CINEMATIC LOOK Feature-film-level cinematography: 24mm chase shots, 35mm movement, 50mm portraits, natural handheld micro-movement, 180° shutter and realistic motion blur. Fine 35mm film grain, subtle highlight halation, soft cinematic bloom and expensive highlight roll-off. Color progression: cool rainy city → warm earthy market → cyan misty mountains → golden coast → deep cyan/red neon → cool mountain atmosphere → rich cinematic blue-hour finale. Keep natural warm skin throughout. TRANSITION RULE Every transition must be physically motivated: bus wipe → water splash → elevator doors → jacket wipe → tram wipe → reflection/whip → crowd reveal → hand-to-lens ending. Never visibly morph locations. No portals, liquid AI transformations, speed ramps, floating cameras or impossible movements. Cuts should be so clean viewers replay them to understand how they happened. REALISM LOCK Same exact lead identity throughout. Real skin texture, correct hands, natural running, realistic footsteps, weighted hair and clothing, earphone cable bouncing with movement, physically correct reflections and splashes. Background people move independently and never freeze or duplicate. No warped architecture, plastic skin, beauty-filter face or AI look. MUSIC / SOUND Original 120 BPM premium cinematic-electronic travel track synchronized tightly to every transition. Start with minimal bass and crisp percussion, build through the chase, open into an uplifting melodic hook at the coast, become deeper at neon night, strip down during the cable-car/crowd search, then massive satisfying beat drop at the friend reveal and strongest musical section for the final run. Layer realistic footsteps, traffic, splash, elevator ding, wind, tram rumble, cable-car hum, crowd ambience, fabric movement, pigeon wings and genuine laughter. No dialogue. No voiceover. No lyrics.

Nexora

24,180 Aufrufe • vor 8 Tagen

Seedance 2.5 just got an upgrade with 1080p only on Higgsfield... you can now ONE SHOT commercials like this here's exactly how to do it (with a gift at then end): 1/ write the prompt as a timestamped breakdown > split the spot second by second > put the exact dialogue inside each window in quotes, the model speaks it word for word with lip sync > match the generation length to your timestamps, a 21 second script generated at 15 compresses and the delivery desyncs 2/ composition is named - never hoped for > name the camera: "handheld front camera, chest-up framing, natural micro shakes" for UGC, "35mm, slow push-in, product centered" for a produced spot > name the light: "golden hour through the windshield" or "ring light with slight reflections in the eyes" > name the grade: "high contrast, cool tones, warm skin" > whatever you leave unstated gets invented and locked for the whole clip 3/ characters hold when you anchor them > generate a first frame image before any video: real skin texture, visible pores, one fixed imperfection like freckles so drift becomes instantly visible > feed it in as the reference and open every prompt with "the same person as the reference, identical face, hair and outfit" > the @ system locks it harder: @.character for the face, @.style for the look, @.audio for the voice > then write the micro behaviors: a glance away and back, a pre-line breath, fingers adjusting grip... small involuntary movement is what reads human, and you get it by naming it 4/ sound is written - not defaulted > end every prompt with an audio block: "clear phone-mic voice with light room tone" for UGC, "clean studio voice, no echo" for a produced spot > name the music under the dialogue: "soft upbeat synth instrumental running quietly underneath" > one delivery word for the read: "delivery: fed up" produces a performance, an adjective stack produces nothing 5/ sharp text is quoted text > write the exact label or on-screen text in quotes with its style > unquoted text gets invented typography that garbles between frames > print brand names big, a bold label survives every shot while a small tag melts 6/ the consistency laws > repeat the product description verbatim in every prompt, faces anchor but products drift > count objects scene-wide: "exactly one bottle in the entire scene, no duplicate on any surface" > close the wardrobe: "small gold studs, no other jewellery, no rings, no watch" > every state change happens across a cut: the swatch on her hand in shot one, blended in shot two, no clip contains the transition... the viewer's brain supplies it and the shortcut for UGC: take an ad that already converted, ask gemini for a 1:1 timestamped breakdown of everything on screen, swap in your product and script -> that breakdown is your prompt set 9:16 for shortform, 16:9 for the spot, generate straight at 1080p and ship RT + reply to this post and i'll send you my full guide to make your own creatives
0:29

Seedance 2.5 just got an upgrade with 1080p only on Higgsfield... you can now ONE SHOT commercials like this here's exactly how to do it (with a gift at then end): 1/ write the prompt as a timestamped breakdown > split the spot second by second > put the exact dialogue inside each window in quotes, the model speaks it word for word with lip sync > match the generation length to your timestamps, a 21 second script generated at 15 compresses and the delivery desyncs 2/ composition is named - never hoped for > name the camera: "handheld front camera, chest-up framing, natural micro shakes" for UGC, "35mm, slow push-in, product centered" for a produced spot > name the light: "golden hour through the windshield" or "ring light with slight reflections in the eyes" > name the grade: "high contrast, cool tones, warm skin" > whatever you leave unstated gets invented and locked for the whole clip 3/ characters hold when you anchor them > generate a first frame image before any video: real skin texture, visible pores, one fixed imperfection like freckles so drift becomes instantly visible > feed it in as the reference and open every prompt with "the same person as the reference, identical face, hair and outfit" > the @ system locks it harder: @.character for the face, @.style for the look, @.audio for the voice > then write the micro behaviors: a glance away and back, a pre-line breath, fingers adjusting grip... small involuntary movement is what reads human, and you get it by naming it 4/ sound is written - not defaulted > end every prompt with an audio block: "clear phone-mic voice with light room tone" for UGC, "clean studio voice, no echo" for a produced spot > name the music under the dialogue: "soft upbeat synth instrumental running quietly underneath" > one delivery word for the read: "delivery: fed up" produces a performance, an adjective stack produces nothing 5/ sharp text is quoted text > write the exact label or on-screen text in quotes with its style > unquoted text gets invented typography that garbles between frames > print brand names big, a bold label survives every shot while a small tag melts 6/ the consistency laws > repeat the product description verbatim in every prompt, faces anchor but products drift > count objects scene-wide: "exactly one bottle in the entire scene, no duplicate on any surface" > close the wardrobe: "small gold studs, no other jewellery, no rings, no watch" > every state change happens across a cut: the swatch on her hand in shot one, blended in shot two, no clip contains the transition... the viewer's brain supplies it and the shortcut for UGC: take an ad that already converted, ask gemini for a 1:1 timestamped breakdown of everything on screen, swap in your product and script -> that breakdown is your prompt set 9:16 for shortform, 16:9 for the spot, generate straight at 1080p and ship RT + reply to this post and i'll send you my full guide to make your own creatives

Machina

12,785 Aufrufe • vor 28 Tagen

Gym day: survived, sweated, and somehow left proud 💪😅 Created with Seedance 2.5 on WaveSpeedAI Prompt: Create a 30-second casual gym vlog featuring the same young woman in her early twenties. She has natural everyday beauty, and her face and hair remain identical throughout the entire video. Camera & visual style One continuous handheld front-facing smartphone selfie vlog, always filmed from her own point of view with the phone held in her own hand at arm’s length. No third-person camera, external camera, tripod, cinematic camera movement, or professional filming. Make it look like a real modern smartphone recording: - Mild handheld shake and natural walking bounce - Occasional autofocus hunting - Small exposure shifts and minor framing imperfections - Natural front-camera lens distortion - Soft warm natural daylight transitioning toward early evening - Natural, uncorrected smartphone color - No color grading, beauty filter, or skin smoothing - Same woman, same face and hair throughout - She holds the phone herself in every shot - No subtitles, captions, logos, watermarks, or on-screen text - No brand or character names - Never show a reference sheet or duplicate subject Outfit She is wearing a cute, trendy, realistic gym outfit appropriate for a casual workout vlog: fitted athletic top, comfortable high-waisted leggings or shorts, clean sneakers, and minimal accessories. The styling should feel fashionable but natural and practical for the gym. Scene She is spending a casual day at the gym and filming herself throughout her workout. She enters the gym while holding her phone at arm’s length, smiling into the front camera. She briefly sweeps the phone toward the workout area, showing treadmills, weights, machines, and other gym-goers in the background, then brings it back to her face. She grins and says upbeat: “Okay, gym day! Let’s get this workout started!” She walks toward the workout area, naturally bouncing the phone with her steps. She glances at the equipment, smiles at the camera, and starts a light warm-up. Keep the movements natural and unscripted, with brief moments of her adjusting her hair, checking her form, and laughing at herself. She moves into a short workout sequence while still filming herself handheld: a few casual gym exercises, light cardio, and a quick strength-training moment. Keep the camera mostly selfie-facing, occasionally tilting naturally toward the equipment before returning to her face. She looks slightly out of breath but happy and says with a playful laugh: “Why did I think this was gonna be easy?” She takes a quick water break, holding her bottle near the selfie camera before taking a sip. She smiles and catches her breath while natural gym ambience continues around her. Later, after finishing the workout, she walks toward the gym exit with the phone still in her hand. Her hair is slightly messier and she looks pleasantly tired. She gives the camera a satisfied smile, lightly wipes her forehead, and says: “Okay… I’m actually proud of myself.” She gives a small tired laugh, waves at the camera, and lowers the phone slightly for a relaxed ending. Audio Diegetic sound only, no background music. Include realistic gym ambience: treadmill hum, weights clanking, machine sounds, footsteps, distant conversations, subtle ventilation, water bottle sounds, and natural room tone. Every spoken line should be delivered frontally with clearly visible lip movement and natural timing. Keep the entire sequence fast, casual, spontaneous, and realistic, with natural transitions and enough brief visual moments to fill approximately 30 seconds without making the dialogue feel rushed. The final result should feel like an authentic personal gym vlog recorded casually on a modern smartphone.
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Gym day: survived, sweated, and somehow left proud 💪😅 Created with Seedance 2.5 on WaveSpeedAI Prompt: Create a 30-second casual gym vlog featuring the same young woman in her early twenties. She has natural everyday beauty, and her face and hair remain identical throughout the entire video. Camera & visual style One continuous handheld front-facing smartphone selfie vlog, always filmed from her own point of view with the phone held in her own hand at arm’s length. No third-person camera, external camera, tripod, cinematic camera movement, or professional filming. Make it look like a real modern smartphone recording: - Mild handheld shake and natural walking bounce - Occasional autofocus hunting - Small exposure shifts and minor framing imperfections - Natural front-camera lens distortion - Soft warm natural daylight transitioning toward early evening - Natural, uncorrected smartphone color - No color grading, beauty filter, or skin smoothing - Same woman, same face and hair throughout - She holds the phone herself in every shot - No subtitles, captions, logos, watermarks, or on-screen text - No brand or character names - Never show a reference sheet or duplicate subject Outfit She is wearing a cute, trendy, realistic gym outfit appropriate for a casual workout vlog: fitted athletic top, comfortable high-waisted leggings or shorts, clean sneakers, and minimal accessories. The styling should feel fashionable but natural and practical for the gym. Scene She is spending a casual day at the gym and filming herself throughout her workout. She enters the gym while holding her phone at arm’s length, smiling into the front camera. She briefly sweeps the phone toward the workout area, showing treadmills, weights, machines, and other gym-goers in the background, then brings it back to her face. She grins and says upbeat: “Okay, gym day! Let’s get this workout started!” She walks toward the workout area, naturally bouncing the phone with her steps. She glances at the equipment, smiles at the camera, and starts a light warm-up. Keep the movements natural and unscripted, with brief moments of her adjusting her hair, checking her form, and laughing at herself. She moves into a short workout sequence while still filming herself handheld: a few casual gym exercises, light cardio, and a quick strength-training moment. Keep the camera mostly selfie-facing, occasionally tilting naturally toward the equipment before returning to her face. She looks slightly out of breath but happy and says with a playful laugh: “Why did I think this was gonna be easy?” She takes a quick water break, holding her bottle near the selfie camera before taking a sip. She smiles and catches her breath while natural gym ambience continues around her. Later, after finishing the workout, she walks toward the gym exit with the phone still in her hand. Her hair is slightly messier and she looks pleasantly tired. She gives the camera a satisfied smile, lightly wipes her forehead, and says: “Okay… I’m actually proud of myself.” She gives a small tired laugh, waves at the camera, and lowers the phone slightly for a relaxed ending. Audio Diegetic sound only, no background music. Include realistic gym ambience: treadmill hum, weights clanking, machine sounds, footsteps, distant conversations, subtle ventilation, water bottle sounds, and natural room tone. Every spoken line should be delivered frontally with clearly visible lip movement and natural timing. Keep the entire sequence fast, casual, spontaneous, and realistic, with natural transitions and enough brief visual moments to fill approximately 30 seconds without making the dialogue feel rushed. The final result should feel like an authentic personal gym vlog recorded casually on a modern smartphone.

Zara

19,143 Aufrufe • vor 25 Tagen

Wan 3.0 vs Seedance 2.5 - same viral video There is only one ruler and it's clear who prompt: Raw vertical phone video (UGC), handheld throughout, filmed by a friend who walks with the group, casual sway, natural night lighting, wide-angle lens, deep focus. Characters The hero is a young woman with long dark hair in a deep-purple one-shoulder dress with a small shoulder bag. Her three friends: one in a dark brown dress, a blonde in a black wrap dress, a blonde in a white mini dress — party dresses and sandals. Laughing, spontaneous night-out energy. Setting A luxury marina at night — a stone quay along a narrow water slip flanked on both sides by large moored luxury yachts, big white hulls rising on either side, masts and rigging above, fenders on the hulls. Warm orange street lamps, palm trees, distant city lights. The yachts glow with blue-turquoise underwater LED lights spilling into the water; a yellow mooring line runs to the stone. Shot list 0.0s–4.0s — Wide tracking shot, eye level, camera moving backward The camera walks backward ahead of the four women as they stroll toward it down the marina promenade, framed head-to-toe, laughing and chatting in French; warm lamplight and palm trees behind, slight handheld bob. 4.0s–6.0s — Medium shot, eye level, backward track + quick left pan The woman in the purple dress surges ahead of the group toward the lens, one arm raised, hair flying; the camera, on their left, keeps tracking back and pans to hold her. 6.0s–8.0s — Medium-wide, camera tilts down-left to follow, whip motion She reaches the quay edge between the moored luxury yachts and launches headfirst over the edge; the handheld camera whips left and tilts down to chase her off the stone. 8.0s–10.0s — High-angle wide, looking down at the water, slight jolt From up on the quay the camera looks down as she plunges headfirst into the blue-turquoise water in the slip between the big yacht hulls — a big splash, the underwater lights glowing around the impact; the handheld frame jolts slightly with the motion. 10.0s–13.0s — High-angle medium, looking down, small handheld drift She surfaces in the teal water, gasping and laughing up at the camera, hair slicked back, treading water. 13.0s–16.0s — Handheld tilt up and back down, slight zoom The camera lifts off the water and tilts up to a person leaning on the deck railing of one of the moored luxury yachts, watching her in the water, then tilts back down and zooms slightly in on her still treading and laughing. 16.0s–20.0s — High-angle medium, tilting to follow her up She swims to the stone quay wall, reaches up and grabs a thick dark mooring pole, and hauls herself out; the camera tilts upward with her as she rises from the water, legs braced on the stone. 20.0s–23.0s — Low/close medium at the quay edge, static handheld She climbs onto the stone lip, rolls onto her side, soaked dress clinging, then pushes up to her feet; the camera holds close, catching the water running off her. 23.0s–27.0s — Medium shot, eye level, loose handheld reframe Back on the promenade, dripping wet, she flips her long wet hair forward and wrings it out, laughing, as her friends and passing pedestrians move behind her. 27.0s–30.0s — Medium shot, eye level, camera settles Still dripping, she straightens up and strikes a confident, playful pose for the camera — hand on hip, tossing her wet hair back with a big smile — her friends laughing around her; the camera holds on the pose to end. Audio Live sync sound — friends laughing and shouting excitedly in French, a scream at the leap, a big water splash, water sloshing against the yacht hulls, wet footsteps on stone, ambient night marina sounds. No music. Style Raw amateur vertical phone footage, natural night lighting, warm street lamps mixing with the turquoise underwater yacht glow, authentic handheld motion.
0:30

Wan 3.0 vs Seedance 2.5 - same viral video There is only one ruler and it's clear who prompt: Raw vertical phone video (UGC), handheld throughout, filmed by a friend who walks with the group, casual sway, natural night lighting, wide-angle lens, deep focus. Characters The hero is a young woman with long dark hair in a deep-purple one-shoulder dress with a small shoulder bag. Her three friends: one in a dark brown dress, a blonde in a black wrap dress, a blonde in a white mini dress — party dresses and sandals. Laughing, spontaneous night-out energy. Setting A luxury marina at night — a stone quay along a narrow water slip flanked on both sides by large moored luxury yachts, big white hulls rising on either side, masts and rigging above, fenders on the hulls. Warm orange street lamps, palm trees, distant city lights. The yachts glow with blue-turquoise underwater LED lights spilling into the water; a yellow mooring line runs to the stone. Shot list 0.0s–4.0s — Wide tracking shot, eye level, camera moving backward The camera walks backward ahead of the four women as they stroll toward it down the marina promenade, framed head-to-toe, laughing and chatting in French; warm lamplight and palm trees behind, slight handheld bob. 4.0s–6.0s — Medium shot, eye level, backward track + quick left pan The woman in the purple dress surges ahead of the group toward the lens, one arm raised, hair flying; the camera, on their left, keeps tracking back and pans to hold her. 6.0s–8.0s — Medium-wide, camera tilts down-left to follow, whip motion She reaches the quay edge between the moored luxury yachts and launches headfirst over the edge; the handheld camera whips left and tilts down to chase her off the stone. 8.0s–10.0s — High-angle wide, looking down at the water, slight jolt From up on the quay the camera looks down as she plunges headfirst into the blue-turquoise water in the slip between the big yacht hulls — a big splash, the underwater lights glowing around the impact; the handheld frame jolts slightly with the motion. 10.0s–13.0s — High-angle medium, looking down, small handheld drift She surfaces in the teal water, gasping and laughing up at the camera, hair slicked back, treading water. 13.0s–16.0s — Handheld tilt up and back down, slight zoom The camera lifts off the water and tilts up to a person leaning on the deck railing of one of the moored luxury yachts, watching her in the water, then tilts back down and zooms slightly in on her still treading and laughing. 16.0s–20.0s — High-angle medium, tilting to follow her up She swims to the stone quay wall, reaches up and grabs a thick dark mooring pole, and hauls herself out; the camera tilts upward with her as she rises from the water, legs braced on the stone. 20.0s–23.0s — Low/close medium at the quay edge, static handheld She climbs onto the stone lip, rolls onto her side, soaked dress clinging, then pushes up to her feet; the camera holds close, catching the water running off her. 23.0s–27.0s — Medium shot, eye level, loose handheld reframe Back on the promenade, dripping wet, she flips her long wet hair forward and wrings it out, laughing, as her friends and passing pedestrians move behind her. 27.0s–30.0s — Medium shot, eye level, camera settles Still dripping, she straightens up and strikes a confident, playful pose for the camera — hand on hip, tossing her wet hair back with a big smile — her friends laughing around her; the camera holds on the pose to end. Audio Live sync sound — friends laughing and shouting excitedly in French, a scream at the leap, a big water splash, water sloshing against the yacht hulls, wet footsteps on stone, ambient night marina sounds. No music. Style Raw amateur vertical phone footage, natural night lighting, warm street lamps mixing with the turquoise underwater yacht glow, authentic handheld motion.

Stav Zilbershtein

187,732 Aufrufe • vor 18 Tagen

everyone in iOS development should watch this. seriously, it might change the whole industry. i pointed claude code at a live ios device running on revyl, typed "test everything," and walked away. here's what's actually happening: ① you don't write the tests. no scripts, no selectors, no test plan. i never told it which screens to open or what to check. it read the app, decided what mattered, and tested it. the entire instruction was "test everything." ② it built its own test team. it looked at the app, clocked that it's basically four mini apps (rides, delivery, services, account), and split itself into 4 agents, one per surface. scoping coverage like that is usually a person's whole afternoon. it did it in seconds, unprompted. ③ all four ran at the same time, each on its own live device. this is where revyl comes in. every agent gets its own live ios session in the cloud, so four running apps get tested in parallel instead of taking turns on one simulator. serial testing turns coverage into a time tax. running all of it at once removes the tax. ④ it tests like a person, not like a script. each agent drives the app the way a user would, taps through the flows, and visually checks each screen against what it expected to see. nothing is pinned to a brittle element id, so renaming a button doesn't take down half your suite. that one detail is the most annoying thing about how we test today, and it just quietly goes away. ⑤ no xcuitest, no sims melting your laptop. i didn't write a single xcuitest script, and there were no simulators booting on my machine. the agents run on cloud devices, so coverage stops being capped by what your laptop can handle. the part that got me isn't that an agent tested an app. it's that i never told it how. i handed it a device and an intent, and it figured out the scoping, the parallelizing, and the driving on its own. if you still write and maintain mobile ui tests by hand, i'm not sure that lasts the year.
0:47

everyone in iOS development should watch this. seriously, it might change the whole industry. i pointed claude code at a live ios device running on revyl, typed "test everything," and walked away. here's what's actually happening: ① you don't write the tests. no scripts, no selectors, no test plan. i never told it which screens to open or what to check. it read the app, decided what mattered, and tested it. the entire instruction was "test everything." ② it built its own test team. it looked at the app, clocked that it's basically four mini apps (rides, delivery, services, account), and split itself into 4 agents, one per surface. scoping coverage like that is usually a person's whole afternoon. it did it in seconds, unprompted. ③ all four ran at the same time, each on its own live device. this is where revyl comes in. every agent gets its own live ios session in the cloud, so four running apps get tested in parallel instead of taking turns on one simulator. serial testing turns coverage into a time tax. running all of it at once removes the tax. ④ it tests like a person, not like a script. each agent drives the app the way a user would, taps through the flows, and visually checks each screen against what it expected to see. nothing is pinned to a brittle element id, so renaming a button doesn't take down half your suite. that one detail is the most annoying thing about how we test today, and it just quietly goes away. ⑤ no xcuitest, no sims melting your laptop. i didn't write a single xcuitest script, and there were no simulators booting on my machine. the agents run on cloud devices, so coverage stops being capped by what your laptop can handle. the part that got me isn't that an agent tested an app. it's that i never told it how. i handed it a device and an intent, and it figured out the scoping, the parallelizing, and the driving on its own. if you still write and maintain mobile ui tests by hand, i'm not sure that lasts the year.

Landseer Enga

23,963 Aufrufe • vor 3 Monaten

Some people still think AI does't look real - This video just ended the argument Made with Seedance 2.5 1080p on maxfusion Full prompt: Raw vertical phone video (UGC), handheld throughout, filmed by a friend who walks with the group, casual sway, natural night lighting, wide-angle lens, deep focus. Characters: The hero is a young woman with long dark hair in a deep-purple one-shoulder dress with a small shoulder bag. Her three friends: one in a dark brown dress, a blonde in a black wrap dress, a blonde in a white mini dress — party dresses and sandals. Laughing, spontaneous night-out energy. Setting: A luxury marina at night — a stone quay along a narrow water slip flanked on both sides by large moored luxury yachts, big white hulls rising on either side, masts and rigging above, fenders on the hulls. Warm orange street lamps, palm trees, distant city lights. The yachts glow with blue-turquoise underwater LED lights spilling into the water; a yellow mooring line runs to the stone. [0.0s–4.0s] — Wide tracking shot, eye level, camera moving backward. The camera walks backward ahead of the four women as they stroll toward it down the marina promenade, framed head-to-toe, laughing and chatting in French; warm lamplight and palm trees behind, slight handheld bob. [4.0s–6.0s] — Medium shot, eye level, backward track + quick left pan. The woman in the purple dress surges ahead of the group toward the lens, one arm raised, hair flying; the camera, on their left, keeps tracking back and pans to hold her. [6.0s–8.0s] — Medium-wide, camera tilts down-left to follow, whip motion. She reaches the quay edge between the moored luxury yachts and launches headfirst over the edge; the handheld camera whips left and tilts down to chase her off the stone. [8.0s–10.0s] — High-angle wide, looking down at the water, slight jolt. From up on the quay the camera looks down as she plunges headfirst into the blue-turquoise water in the slip between the big yacht hulls — a big splash, the underwater lights glowing around the impact; the handheld frame jolts slightly with the motion. [10.0s–13.0s] — High-angle medium, looking down, small handheld drift. She surfaces in the teal water, gasping and laughing up at the camera, hair slicked back, treading water. [13.0s–16.0s] — Handheld tilt up and back down, slight zoom. The camera lifts off the water and tilts up to a person leaning on the deck railing of one of the moored luxury yachts, watching her in the water, then tilts back down and zooms slightly in on her still treading and laughing. [16.0s–20.0s] — High-angle medium, tilting to follow her up. She swims to the stone quay wall, reaches up and grabs a thick dark mooring pole, and hauls herself out; the camera tilts upward with her as she rises from the water, legs braced on the stone. [20.0s–23.0s] — Low/close medium at the quay edge, static handheld. She climbs onto the stone lip, rolls onto her side, soaked dress clinging, then pushes up to her feet; the camera holds close, catching the water running off her. [23.0s–27.0s] — Medium shot, eye level, loose handheld reframe. Back on the promenade, dripping wet, she flips her long wet hair forward and wrings it out, laughing, as her friends and passing pedestrians move behind her. [27.0s–30.0s] — Medium shot, eye level, camera settles. Still dripping, she straightens up and strikes a confident, playful pose for the camera — hand on hip, tossing her wet hair back with a big smile — her friends laughing around her; the camera holds on the pose to end. Audio: Live sync sound — friends laughing and shouting excitedly in French, a scream at the leap, a big water splash, water sloshing against the yacht hulls, wet footsteps on stone, ambient night marina sounds. No music. Style: Raw amateur vertical phone footage, natural night lighting, warm street lamps mixing with the turquoise underwater yacht glow, authentic handheld motion.
0:30

Some people still think AI does't look real - This video just ended the argument Made with Seedance 2.5 1080p on maxfusion Full prompt: Raw vertical phone video (UGC), handheld throughout, filmed by a friend who walks with the group, casual sway, natural night lighting, wide-angle lens, deep focus. Characters: The hero is a young woman with long dark hair in a deep-purple one-shoulder dress with a small shoulder bag. Her three friends: one in a dark brown dress, a blonde in a black wrap dress, a blonde in a white mini dress — party dresses and sandals. Laughing, spontaneous night-out energy. Setting: A luxury marina at night — a stone quay along a narrow water slip flanked on both sides by large moored luxury yachts, big white hulls rising on either side, masts and rigging above, fenders on the hulls. Warm orange street lamps, palm trees, distant city lights. The yachts glow with blue-turquoise underwater LED lights spilling into the water; a yellow mooring line runs to the stone. [0.0s–4.0s] — Wide tracking shot, eye level, camera moving backward. The camera walks backward ahead of the four women as they stroll toward it down the marina promenade, framed head-to-toe, laughing and chatting in French; warm lamplight and palm trees behind, slight handheld bob. [4.0s–6.0s] — Medium shot, eye level, backward track + quick left pan. The woman in the purple dress surges ahead of the group toward the lens, one arm raised, hair flying; the camera, on their left, keeps tracking back and pans to hold her. [6.0s–8.0s] — Medium-wide, camera tilts down-left to follow, whip motion. She reaches the quay edge between the moored luxury yachts and launches headfirst over the edge; the handheld camera whips left and tilts down to chase her off the stone. [8.0s–10.0s] — High-angle wide, looking down at the water, slight jolt. From up on the quay the camera looks down as she plunges headfirst into the blue-turquoise water in the slip between the big yacht hulls — a big splash, the underwater lights glowing around the impact; the handheld frame jolts slightly with the motion. [10.0s–13.0s] — High-angle medium, looking down, small handheld drift. She surfaces in the teal water, gasping and laughing up at the camera, hair slicked back, treading water. [13.0s–16.0s] — Handheld tilt up and back down, slight zoom. The camera lifts off the water and tilts up to a person leaning on the deck railing of one of the moored luxury yachts, watching her in the water, then tilts back down and zooms slightly in on her still treading and laughing. [16.0s–20.0s] — High-angle medium, tilting to follow her up. She swims to the stone quay wall, reaches up and grabs a thick dark mooring pole, and hauls herself out; the camera tilts upward with her as she rises from the water, legs braced on the stone. [20.0s–23.0s] — Low/close medium at the quay edge, static handheld. She climbs onto the stone lip, rolls onto her side, soaked dress clinging, then pushes up to her feet; the camera holds close, catching the water running off her. [23.0s–27.0s] — Medium shot, eye level, loose handheld reframe. Back on the promenade, dripping wet, she flips her long wet hair forward and wrings it out, laughing, as her friends and passing pedestrians move behind her. [27.0s–30.0s] — Medium shot, eye level, camera settles. Still dripping, she straightens up and strikes a confident, playful pose for the camera — hand on hip, tossing her wet hair back with a big smile — her friends laughing around her; the camera holds on the pose to end. Audio: Live sync sound — friends laughing and shouting excitedly in French, a scream at the leap, a big water splash, water sloshing against the yacht hulls, wet footsteps on stone, ambient night marina sounds. No music. Style: Raw amateur vertical phone footage, natural night lighting, warm street lamps mixing with the turquoise underwater yacht glow, authentic handheld motion.

Stav Zilbershtein

417,459 Aufrufe • vor 25 Tagen

The girl who is late for her date Seedance 2.5 for you Prompt 👇 Create a 30-second cinematic 3D animated street-racing sequence with a stylized high-end video-game aesthetic, expressive cartoon characters, realistic vehicle physics, dynamic camera work, polished feature-film animation, and energetic comedic pacing. Scene 1 — The forgotten date: A stylish young woman with long black hair, expressive eyes, oversized sunglasses, silver hoop earrings, a cropped black leather jacket, fitted white top, high-waisted jeans, and chunky sneakers relaxes on her apartment sofa while scrolling through her phone. She suddenly checks the time, realizes she completely forgot about an important date, freezes in shock, drops her phone onto the sofa, and dramatically screams while jumping to her feet. Scene 2 — Instant transformation: She races toward her bedroom. Fast comedic cuts show her throwing on a red leather jacket, adjusting her earrings, grabbing her handbag, putting on sunglasses, and quickly fixing her hair. She grabs her keys and rushes out of the apartment. Scene 3 — The getaway car: She bursts into an underground parking garage and jumps into a sleek modified red sports car. The engine roars as she grips the steering wheel with determination. She looks at the clock, widens her eyes, and slams the accelerator. Scene 4 — Downtown launch: The car launches onto a busy city street. Low-angle shots capture the wheels spinning, tire smoke, reflections across the glossy bodywork, and the car accelerating between traffic. Buildings streak past as the camera rapidly switches between front, side, overhead, and interior shots. Scene 5 — The chaotic chase: She races through downtown, weaving around taxis, buses, delivery vans, and intersections. She takes a sharp corner in a controlled drift, narrowly passes through a closing traffic barrier, and cuts through a narrow alley as the camera follows with aggressive tracking movement. Scene 6 — Impossible shortcut: She spots a steep parking-ramp entrance and takes it at full speed. The car launches briefly over the ramp, lands smoothly, spins into a controlled drift, and exits onto another street. Use dramatic slow-motion impact, tire smoke, realistic suspension movement, and exaggerated but believable physics. Scene 7 — Finally there: She reaches a stylish rooftop café overlooking the city at golden hour and slides the car to a stop. She jumps out, quickly fixes her hair, checks herself in the car window, and runs toward the entrance. Scene 8 — The date: A stylish young man is waiting outside the café, looking at his watch. She arrives breathless and gives him an embarrassed smile. He looks at her for a moment, then laughs. She points toward the city and jokingly gestures that the traffic was not her fault. Final shot: They walk into the rooftop café together as the camera pulls backward. Through the glass windows, the red sports car remains parked below while the golden city skyline glows behind them. Visual style: Premium stylized 3D animation, expressive facial acting, exaggerated comedy, detailed character animation, realistic vehicle physics, cinematic lighting, vibrant downtown environment, realistic reflections, volumetric sunlight, tire smoke, subtle sparks, detailed car textures, natural hair and clothing movement, smooth camera animation, high-energy music-video pacing, polished AAA video-game cinematic quality. Camera: Constantly moving cinematic camera, low-angle tracking, aerial shots, interior POV, wheel close-ups, Dutch angles, whip pans, speed ramps, dramatic push-ins, realistic motion blur. Mood: Chaotic, funny, stylish, romantic, adrenaline-fueled. Audio: Energetic cinematic beat, engine revs, tire screeches, city ambience, footsteps, car doors, comedic reaction sounds, and natural dialogue. No subtitles, no logos, no watermark, no on-screen text.
0:30

The girl who is late for her date Seedance 2.5 for you Prompt 👇 Create a 30-second cinematic 3D animated street-racing sequence with a stylized high-end video-game aesthetic, expressive cartoon characters, realistic vehicle physics, dynamic camera work, polished feature-film animation, and energetic comedic pacing. Scene 1 — The forgotten date: A stylish young woman with long black hair, expressive eyes, oversized sunglasses, silver hoop earrings, a cropped black leather jacket, fitted white top, high-waisted jeans, and chunky sneakers relaxes on her apartment sofa while scrolling through her phone. She suddenly checks the time, realizes she completely forgot about an important date, freezes in shock, drops her phone onto the sofa, and dramatically screams while jumping to her feet. Scene 2 — Instant transformation: She races toward her bedroom. Fast comedic cuts show her throwing on a red leather jacket, adjusting her earrings, grabbing her handbag, putting on sunglasses, and quickly fixing her hair. She grabs her keys and rushes out of the apartment. Scene 3 — The getaway car: She bursts into an underground parking garage and jumps into a sleek modified red sports car. The engine roars as she grips the steering wheel with determination. She looks at the clock, widens her eyes, and slams the accelerator. Scene 4 — Downtown launch: The car launches onto a busy city street. Low-angle shots capture the wheels spinning, tire smoke, reflections across the glossy bodywork, and the car accelerating between traffic. Buildings streak past as the camera rapidly switches between front, side, overhead, and interior shots. Scene 5 — The chaotic chase: She races through downtown, weaving around taxis, buses, delivery vans, and intersections. She takes a sharp corner in a controlled drift, narrowly passes through a closing traffic barrier, and cuts through a narrow alley as the camera follows with aggressive tracking movement. Scene 6 — Impossible shortcut: She spots a steep parking-ramp entrance and takes it at full speed. The car launches briefly over the ramp, lands smoothly, spins into a controlled drift, and exits onto another street. Use dramatic slow-motion impact, tire smoke, realistic suspension movement, and exaggerated but believable physics. Scene 7 — Finally there: She reaches a stylish rooftop café overlooking the city at golden hour and slides the car to a stop. She jumps out, quickly fixes her hair, checks herself in the car window, and runs toward the entrance. Scene 8 — The date: A stylish young man is waiting outside the café, looking at his watch. She arrives breathless and gives him an embarrassed smile. He looks at her for a moment, then laughs. She points toward the city and jokingly gestures that the traffic was not her fault. Final shot: They walk into the rooftop café together as the camera pulls backward. Through the glass windows, the red sports car remains parked below while the golden city skyline glows behind them. Visual style: Premium stylized 3D animation, expressive facial acting, exaggerated comedy, detailed character animation, realistic vehicle physics, cinematic lighting, vibrant downtown environment, realistic reflections, volumetric sunlight, tire smoke, subtle sparks, detailed car textures, natural hair and clothing movement, smooth camera animation, high-energy music-video pacing, polished AAA video-game cinematic quality. Camera: Constantly moving cinematic camera, low-angle tracking, aerial shots, interior POV, wheel close-ups, Dutch angles, whip pans, speed ramps, dramatic push-ins, realistic motion blur. Mood: Chaotic, funny, stylish, romantic, adrenaline-fueled. Audio: Energetic cinematic beat, engine revs, tire screeches, city ambience, footsteps, car doors, comedic reaction sounds, and natural dialogue. No subtitles, no logos, no watermark, no on-screen text.

Smiling Khan

10,760 Aufrufe • vor 25 Tagen

ANYTHING THAT WAS EVER ANIMATED CAN NOW BE RE-SHOT Berserk, 1997, on the bottom. The same frames rebuilt photoreal in 2026 on top. Same composition, same lighting, same blocking - a different medium entirely. Nobody remade this. Someone re-shot it, frame for frame, from footage that already existed. Here's why this format works so well The original is already a perfect storyboard. Every shot in an anime was composed by a director decades ago -framing, camera angle, light direction, timing. You're not inventing anything, you're inheriting a finished shot list from people who knew what they were doing Side-by-side is the entire hook. Split-screen with the year stamped on each half does all the work. The audience isn't asked to be impressed by AI, they're just shown a before and after and left to react Recognition beats novelty. A random photoreal knight is a nice image. Griffith in that exact frame, in that exact light, is a memory being rendered - and that's what makes people stop Depth and pose come free. The source frame gives you composition and body position without a single prompt describing them. You only have to define the look The gap between styles is the payoff. Cel-shaded flat colors versus armor with real metal reflections -the further apart the two mediums, the harder the comparison lands The part nobody mentions This format is already a business. The cartoon-to-live-action trend broke out on Douyin months ago, and the people who brought it west first are clearing five figures a month on it — one creator running Tom and Jerry rebuilds pulled $11,900 last month on roughly $50 in monthly costs. Warner Bros spent $136,000,000 putting one of those cartoons in theaters. The format costs a subscription and a weekend now. Worth being straight about • Berserk belongs to its creator's estate and studio — this works as a demonstration and a tribute, but publishing it as your own IP or monetizing it directly is a different conversation • The technical possibility arrived way ahead of the legal framework, and that gap is still very much open Studios spend years deciding whether a live-action adaptation is worth the budget. Someone just did a scene of one over a weekend.
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ANYTHING THAT WAS EVER ANIMATED CAN NOW BE RE-SHOT Berserk, 1997, on the bottom. The same frames rebuilt photoreal in 2026 on top. Same composition, same lighting, same blocking - a different medium entirely. Nobody remade this. Someone re-shot it, frame for frame, from footage that already existed. Here's why this format works so well The original is already a perfect storyboard. Every shot in an anime was composed by a director decades ago -framing, camera angle, light direction, timing. You're not inventing anything, you're inheriting a finished shot list from people who knew what they were doing Side-by-side is the entire hook. Split-screen with the year stamped on each half does all the work. The audience isn't asked to be impressed by AI, they're just shown a before and after and left to react Recognition beats novelty. A random photoreal knight is a nice image. Griffith in that exact frame, in that exact light, is a memory being rendered - and that's what makes people stop Depth and pose come free. The source frame gives you composition and body position without a single prompt describing them. You only have to define the look The gap between styles is the payoff. Cel-shaded flat colors versus armor with real metal reflections -the further apart the two mediums, the harder the comparison lands The part nobody mentions This format is already a business. The cartoon-to-live-action trend broke out on Douyin months ago, and the people who brought it west first are clearing five figures a month on it — one creator running Tom and Jerry rebuilds pulled $11,900 last month on roughly $50 in monthly costs. Warner Bros spent $136,000,000 putting one of those cartoons in theaters. The format costs a subscription and a weekend now. Worth being straight about • Berserk belongs to its creator's estate and studio — this works as a demonstration and a tribute, but publishing it as your own IP or monetizing it directly is a different conversation • The technical possibility arrived way ahead of the legal framework, and that gap is still very much open Studios spend years deciding whether a live-action adaptation is worth the budget. Someone just did a scene of one over a weekend.

Nexlow

104,906 Aufrufe • vor 9 Tagen

save this post to get the most out of unlimited Seedance 2.5 for up to 33 days on Higgsfield i'm going to show you how to use loops to produce ANY video format: ads, cinema, vlogs, UGC, music videos... with one system idea > vault > agent > references > images > script > video > montage > upscaling Seedance 2.5 one-shots a full 30 second video, audio generated in the same pass, carrying up to 30 image, 10 video and 10 audio references into a single generation here's a full breakdown of the setup: > idea: steal taste from work that already worked: - frameset․app and shotdeck․com for film stills - savee․com and cosmos․so for boards - eyecannndy․com for transitions then have a vision model name the lens, light, palette and grain of your picks in one locked paragraph you paste into every prompt > vault: an obsidian folder as your reference bible, one page per asset (idea, locked style, character sheets, reference images, the exact prompts that worked) plus one index page, reviewed after every session so it never rots into dead files > agent: three commands make every model callable from Claude Code: - npm install -g @ higgsfield/cli - higgsfield auth login - npx skills add higgsfield-ai/skills and your agent now submits, polls, retries and logs every job > references: build reference images by hand first, midjourney for cinema and stylized shots, nanobanana pro or gpt images 2 for realism use one locked style across the whole project, recurring characters turned into full sheets (front, side, back, blank background), and once locked you never regenerate them, you fix the motion prompt instead > images: frames before motion, always, a frame costs seconds and a clip costs minutes, so exploration happens at the cheap layer and only winners get animated > script: every shot gets the same six details, subject, action, place, camera, style, rules, and the 30 seconds splits into four timed beats inside one prompt, 0-6 set the scene, 6-14 build it out, 14-24 the turn, 24-30 the end > video: every reference gets a job and a boundary, "Video 1 defines motion and pacing" is half the instruction, "do not use the person's identity, clothing or scene" is the half that stops one reference leaking into shots it was never meant to touch > montage: the cut is a text file, one line per clip with its duration and an audio flag, ffmpeg renders the film from it, so the whole edit reruns in seconds > upscaling: once, at the end, on the finished cut, 720p while exploring, 1080p for keepers, 4K only for the master (use Topaz) for UGC ads, the same loop with two changes render the hook clip alone first, approve the face and the voice before anything else inherits them, then anchor every later clip with the approved hook's audio so one voice carries the whole ad and the script math is fixed, about 3.5 words per second, a 30 second ad is roughly 105 words, counted before anything renders unlimited means every loop above costs nothing to run... start one tonight
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save this post to get the most out of unlimited Seedance 2.5 for up to 33 days on Higgsfield i'm going to show you how to use loops to produce ANY video format: ads, cinema, vlogs, UGC, music videos... with one system idea > vault > agent > references > images > script > video > montage > upscaling Seedance 2.5 one-shots a full 30 second video, audio generated in the same pass, carrying up to 30 image, 10 video and 10 audio references into a single generation here's a full breakdown of the setup: > idea: steal taste from work that already worked: - frameset․app and shotdeck․com for film stills - savee․com and cosmos․so for boards - eyecannndy․com for transitions then have a vision model name the lens, light, palette and grain of your picks in one locked paragraph you paste into every prompt > vault: an obsidian folder as your reference bible, one page per asset (idea, locked style, character sheets, reference images, the exact prompts that worked) plus one index page, reviewed after every session so it never rots into dead files > agent: three commands make every model callable from Claude Code: - npm install -g @ higgsfield/cli - higgsfield auth login - npx skills add higgsfield-ai/skills and your agent now submits, polls, retries and logs every job > references: build reference images by hand first, midjourney for cinema and stylized shots, nanobanana pro or gpt images 2 for realism use one locked style across the whole project, recurring characters turned into full sheets (front, side, back, blank background), and once locked you never regenerate them, you fix the motion prompt instead > images: frames before motion, always, a frame costs seconds and a clip costs minutes, so exploration happens at the cheap layer and only winners get animated > script: every shot gets the same six details, subject, action, place, camera, style, rules, and the 30 seconds splits into four timed beats inside one prompt, 0-6 set the scene, 6-14 build it out, 14-24 the turn, 24-30 the end > video: every reference gets a job and a boundary, "Video 1 defines motion and pacing" is half the instruction, "do not use the person's identity, clothing or scene" is the half that stops one reference leaking into shots it was never meant to touch > montage: the cut is a text file, one line per clip with its duration and an audio flag, ffmpeg renders the film from it, so the whole edit reruns in seconds > upscaling: once, at the end, on the finished cut, 720p while exploring, 1080p for keepers, 4K only for the master (use Topaz) for UGC ads, the same loop with two changes render the hook clip alone first, approve the face and the voice before anything else inherits them, then anchor every later clip with the approved hook's audio so one voice carries the whole ad and the script math is fixed, about 3.5 words per second, a 30 second ad is roughly 105 words, counted before anything renders unlimited means every loop above costs nothing to run... start one tonight

Machina

39,183 Aufrufe • vor 1 Monat