(1) Image → (18) Angles → (1) Click. Weavy... + Qwen Edit Multi-Angle. (Full workflow in thread) PROCESS: 01. Import Qwen Edit Multiview LORA from Replicate. 02. Add an input node. 03. Duplicate a bunch of Qwen nodes 04. Vary angles and perspectives. 05. Generate. #weavy #promptshareshow more

By far the best way to generate images at... different angles is this 3D Camera Control node. Instead of describing angles with words, you just click the view you want. Simple UI, and the Qwen Image Edit 2511 multi-angle LoRA keeps things consistent across generations. Workflow below 👇show more

Ep 56 → Youtube Thumbnail Workflow. Elon vs Fast... Hours. (Full workflow in thread) PROCESS: 1. Create base characters 2. Composite characters. 3. Iterate Scenery 4. Add text + upscale/flatten. TOOLS: + Weavy: Workflow Creation + Midjourney: Character Gen + Nano Banana/SeedDream: Image Editing + Qwen: Changing perspective + Flux Fill/SD Content Aware: Inpainting + Rodin 3D: Text gen + placement + Bria: Background removal + Compositor: Canvasing + Kling 2.5: Video gen #weavy #promptshareshow more

The Making of a Coliseum Ship Battle. With Google... Earth + Weavy + Veo3 (With help from Runway/Flux/etc) PROCESS: 01. Screenshot Location on GE 02. Rexture + add details 03. Composite elements 04. Diagram Shot 05. Generate + iterate Used a lot of tools in this one. (More details in thread) #veo3 #promptshareshow more

MIDJOURNEY → Quality of life update. "Smart Select" now... is within Editor. PROCESS: 01. Open "Edit" 02. Upload an image 03. Choose "SELECT" 04. Highlight the area. 05. Select "Remove" or "Isolate" 06. Add prompt + generate #midjourneyshow more

Midjourney Video → Keyframes Released. It also works with... "extend." PROCESS: 01. Generate original image 02. Remove background. 03. Regenerate background. 04. Add both images as keyframes 05. Extend and continue. (More Details in thread) VIDEO PROMPT: Side profile tracking shot of a matte green Land Rover Defender driving from a [environment1] into a [environment2]. Smooth cinematic transition. [ENV1] blurs into a [ENV2]. Motion blur on car wheels. [LIGHTING1] replaces [LIGHTING2]. Steady camera on vehicle, looping seamless movement --motion high #midjourney #promptshareshow more

Here comes a really fast AI UGC content creator!... Here's a highly customizable workflow 1. Upload the Product Photo 2. Upload the Script 3. Click Run In a couple of mins, you have a vertical talking head video The best part is, it's cheap, fast and highly customizable! Photo → fal's Flux 2 Turbo Edit TTS → Qwen 3 TTS Video → LTX-2 Audio to Video In just a couple of mins, you'll have a video that you can share and batch out to promote your product for the next campaign! I'm sharing the workflow 👇🏽 so you can clone and edit as you wish!show more

We recently introduced Gemini Omni Flash, our first model... in the new Omni family. With Omni, you can easily create and edit high-quality videos from text, image, video or audio references. We recently gave developers access to it, and since then, we’ve seen builders all over the world use Omni to create a range of personal and professional projects. Here are some of our favorite ways we’ve seen builders use Omni so far ↓ 📽️ Switch angles and perspectives You can change camera angles, switch environments, and apply cinematic zooms — all without losing the thread of your original scene. Builder Leon Lin took full advantage of this capability, capturing a woman standing in the middle of a city from about 20 different perspectives. You see her from different angles: up close and far away, head on and in profile, from above, and from below. Some shots zoom in, while others hold still. And the background shifts, too.show more

AN AWS ENGINEER QUIETLY BUILT A 2 PETABYTE HOME... SERVER FOR $9/MONTH THAT KILLS A $3,400/MONTH CLOUD STORAGE BILL the lenovo thinkstation pgx ships nvidia's gb10 grace blackwell superchip and 128gb of unified memory in a box the size of a mac mini at 1.2kg it runs an 80b qwen3 coder model at 25 to 40 tokens per second and a 196b step-3.5-flash moe model at 20 tokens per second locally the gb10 packs 6,144 cuda cores, 192 fifth-generation tensor cores and rates at 1 petaflop of fp4 with sparsity from a single 240 watt usb-c power supply fine tuning qwen 2.5 7b with lora took 18 minutes and 41gb of unified memory while the gpu pulled 65 watts and peaked at 77 degrees the box pulls a docker container from nvidia's registry and serves a frontier model on your local network with tool calling and zero data leaving your desk bookmark this and read the article belowshow more

Midjourney + Kling + Sora. Testing new workflows. Process:... 01. Midjourney for base images 02. Kling Elements to combine 03. Sora Blend MJ Prompt 1: cinematic still, showing the moment a conscious creator designs humanity --ar 16:9 --q 2 --p --s 650 MJ Prompt 2: cinematic still, Mayan shaman wearing intricate ceremonial attire, ancient ritual, light rays and shadows, smoke interacting with light --ar 16:9 --q 2 --p --s 650 Kling Elements Prompt: A cinematic tracking shot follows behind man conducting sorcery in a dark cave as he summons an ancient mayan spirt through a portal. The camera pushes in on the portal passing the mans hand from a low angle as he is conjuring a teal-green portal. Suddenly, an ancient mayan spirit emerges from the center of the portal-exploding onto the scene with an cinematic flair adorned in ritualistic attire and a massive headdress - showing his full body - as he enters the scene with presence and awe. Natural smoky textures billow and pulsate. Shot in cinematic 4k. #midjourney #kling #promptshare Kling AIshow more

Gemini Omni is changing video creation and most people... still don't know what it can actually do. Here are 7 things you can do with it right now: 1. Image to Video in multiple styles: Upload a photo. describe the style. Gemini Omni turns it into a video. cinematic, anime, realistic. 2. Reimagine camera angles: Take any image and visualize it from a completely different angle. no reshooting. just describe it. 3. Change backgrounds: Swap the background of any video through plain conversation. no green screen. no editing software. 4. Change hairstyle: Describe a new hairstyle. Gemini Omni applies it. characters stay consistent across every frame. 5. visualize with moodboards: feed it a moodboard, audio, and a brief. it builds the video around the full creative reference — not just a text prompt. 6. swap characters and objects mid-scene: replace people, props, and objects in an existing video. the scene stays consistent. the physics hold up. 7. edit physics: describe how you want things to move. Gemini Omni adjusts the physics of the scene through conversation.show more

FIVE LAYERS OF AGENT ENGINEERING, EACH ONE WRAPS THE... ONE BELOW IT. IF YOU SKIP LAYER 2, YOUR LAYER 5 WILL LOOK BROKEN WHEN IT IS ACTUALLY JUST STANDING ON NOTHING. for weeks i debated harness vs loop vs graph like they were competing choices. then a stack diagram made the shape obvious. they are not choices. they are floors. 01 | prompt engineering. the message. unit of work: one input. inputs are role, instructions, examples, format. output is a single raw response. 02 | context engineering. the memory. unit of work: what stays in the window. a curator selects, compresses, and drops from query, docs, memory, prior turns, and tool outputs before the prompt runs. 03 | harness engineering. the machine. unit of work: the machine itself. gather (context + prompt) → LLM → tools or sub-agents → verifier → final response. the article calls this the operating environment. 04 | loop engineering. the system. unit of work: the run. goal + success criteria + max iterations + budget + completion check wrap around one harness pass. failed pass appends results to context and retries. 05 | graph engineering. the topology. unit of work: the graph run. goal + nodes + edges + state schema. graph routes to agent nodes, tool nodes, or human approval. a reviewer node with a different model and fresh context checks the final answer. the wrapping is the whole point. layer 5 assumes layer 4 works. layer 4 assumes layer 3 works. skip layer 2 and layer 3's verifier keeps failing without a clear reason. this is why swapping the model is a one-day project and swapping the stack is a quarter. the model is the commodity. the five layers around it are the engineering. full three-layer breakdown of the top of the stack (harness, loop, graph) in the post below.show more

Nanobanana Pro Higgsfield AI 🧩 なるほどこれは便利！！ いろんなショットを一発で出して、そこから選ぶ感じ 見事にアップスケールしてくれる プロンプトはリプ欄の元投稿を使わせていただきました... ””” Analyze the entire composition of the input image. Identify ALL key subjects present (whether it's a single person, a group/couple, a vehicle, or a specific object) and their spatial relationship/interaction. Generate a cohesive 3x3 grid "Cinematic Contact Sheet" featuring 9 distinct camera shots of exactly these subjects in the same environment. You must adapt the standard cinematic shot types to fit the content (e.g., if a group, keep the group together; if an object, frame the whole object): **Row 1 (Establishing Context):** 1. **Extreme Long Shot (ELS):** The subject(s) are seen small within the vast environment. 2. **Long Shot (LS):** The complete subject(s) or group is visible from top to bottom (head to toe / wheels to roof). 3. **Medium Long Shot (American/3-4):** Framed from knees up (for people) or a 3/4 view (for objects). **Row 2 (The Core Coverage):** 4. **Medium Shot (MS):** Framed from the waist up (or the central core of the object). Focus on interaction/action. 5. **Medium Close-Up (MCU):** Framed from chest up. Intimate framing of the main subject(s). 6. **Close-Up (CU):** Tight framing on the face(s) or the "front" of the object. **Row 3 (Details & Angles):** 7. **Extreme Close-Up (ECU):** Macro detail focusing intensely on a key feature (eyes, hands, logo, texture). 8. **Low Angle Shot (Worm's Eye):** Looking up at the subject(s) from the ground (imposing/heroic). 9. **High Angle Shot (Bird's Eye):** Looking down on the subject(s) from above. Ensure strict consistency: The same people/objects, same clothes, and same lighting across all 9 panels. The depth of field should shift realistically (bokeh in close-ups). A professional 3x3 cinematic storyboard grid containing 9 panels. The grid showcases the specific subjects/scene from the input image in a comprehensive range of focal lengths. **Top Row:** Wide environmental shot, Full view, 3/4 cut. **Middle Row:** Waist-up view, Chest-up view, Face/Front close-up. **Bottom Row:** Macro detail, Low Angle, High Angle. All frames feature photorealistic textures, consistent cinematic color grading, and correct framing for the specific number of subjects or objects analyzed. """show more

Everyone's sleeping on image-to-3D AI models. They can make... your app look incredibly unique, with just a little effort. Here's how. This is my calorie tracker, built in a week with nothing but prompting. Just Claude Code + a couple APIs. The visuals are all AI-generated. I'll be sharing the full workflow + all the crazy technical stuff Claude and I did to make this work, so nobody has to struggle through it like me. Deep dive coming soon! Till then, this is the high-level idea: 1. Get a clean image of the food (or whatever your asset is) - In my app, the user describes foods via text, or attaches images (or both) - If text, an LLM extracts the food description and formats it into a specific prompt I tuned for this design, and we generate an image using Z-Image Turbo through fal - If image, we do the same thing but with FLUX.2 [dev] to edit the user image into our reference design - Originally, both used Google Nano Banana, but switching to open models cut costs and latency a ton 2. Gaussian splatting (2D image → 3D model) - I tried various 2D-to-3D options on fal and ended up with TripoSplat as my preferred balance of speed, cost, latency; this turns an image into a 3D model that looks super high quality (link below) - The app displays the 2D image while our backend generates the 3D splat - We "groom" the splat to reduce size and load time by culling low-opacity/scale points 3. Render efficiently on device Originally, it looked great but ran at 10 FPS. Getting to 120 FPS was a crazy journey. TL;DR: - SwiftUI had to go; it forced us to render each asset in independent MTKViews, which wasn't workable - Instead, we composite every dish into one full-bleed CAMetalLayer using MetalSplatter (link below) - We had to make some optimizations within MetalSplatter's code too, to reduce the overhead of sorting points per render Then I added some finishing touches like the subtle rotation and parallax as they move around. I think it turned out pretty cool :) Overall, this took some effort, but we still got it done in less than a day. Hopefully your agent can follow in the footsteps of mine and do it much faster. Keep an eye out for the bigger writeup, which'll give your agent everything it needs. If you have any questions, drop em below!show more

Instead of GRWM, let's cook with me. Cooked on... GPT Image 2 + Happy Horse on BudgetPixel AI Prompt Create a 10-second cinematic food-commercial video following a STRICT 9-panel storyboard sequence. The AI MUST follow the storyboard EXACTLY in order with smooth cinematic continuity between every shot. Do NOT skip panels, merge scenes, change camera angles randomly, or alter the cooking process. STRICT VIDEO RULES EXACTLY 9 sequential scenes Maintain the SAME young Western blonde woman throughout the entire video Same wardrobe, hairstyle, kitchen environment, props, and food consistency in every shot Keep realistic Indonesian bubur ayam preparation accurate Smooth transitions between scenes Realistic live-action cinematography ONLY No animation, no cartoon style, no surreal visuals Professional food-commercial pacing Every scene should feel connected like a luxury Netflix food documentary VISUAL STYLE Ultra realistic cinematic food videography Warm morning lighting Indonesian street-food atmosphere blended with modern cozy kitchen aesthetic Rich golden tones Soft steam atmosphere Shallow depth of field Smooth cinematic motion blur Macro food photography look Premium commercial composition 24fps cinematic motion 4K ultra realism Natural cooking ambience audio Steam and glossy textures highly visible STRICT 9-PANEL VIDEO STORYBOARD PANEL 1 — “Morning Preparation” (0:00–0:01) Wide cinematic establishing shot. Young blonde Western woman enters a cozy Indonesian-inspired kitchen carrying fresh ingredients toward a wooden counter. Warm sunrise light enters through the window. Slow handheld cinematic camera movement. PANEL 2 — “The Bubur Pot” (0:01–0:02) Extreme close-up of a large steaming pot of thick bubur ayam. The woman slowly stirs the porridge with a metal ladle. Heavy steam rises dramatically into warm light. Macro cinematic food detail. PANEL 3 — “Careful Seasoning” (0:02–0:03) Close-up of the woman sprinkling spices and seasoning into the bubbling porridge. Focused expression. Shallow depth of field with cinematic hand movement. PANEL 4 — “Pouring the Porridge” (0:03–0:04) Slow-motion macro shot of thick glossy porridge being poured from ladle into a white ceramic bowl. Steam rises beautifully. Camera follows the pouring motion smoothly. PANEL 5 — “Preparing Toppings” (0:04–0:05) Fast cinematic montage of toppings being prepared: shredded chicken, chopped scallions, fried shallots, soybeans, crackers. Quick macro cuts with elegant food styling. PANEL 6 — “Topping Assembly” (0:05–0:06) Dynamic slow-motion shot of toppings dropping into the bowl one by one. Floating crumbs and steam visible. Luxury commercial close-up angles. PANEL 7 — “Golden Broth Finish” (0:06–0:07) Golden chicken broth poured over the porridge creating rich ripples. Sambal carefully added on the side. Camera slowly rotates around the bowl. PANEL 8 — “Final Food Presentation” (0:07–0:08.5) Completed bubur ayam placed on a warm wooden table. The woman adjusts the bowl presentation gently. Steam rises naturally. Crispy toppings highly detailed. PANEL 9 — “Hero Shot” (0:08.5–0:10) Final cinematic hero frame. The blonde Western woman sits beside the finished bubur ayam smiling softly toward camera in warm morning light. Slow cinematic push-in camera movement. Shallow depth of field. Elegant premium food-commercial ending with cinematic focus pull. TECHNICAL NOTES Smooth cinematic transitions only Keep camera movement elegant and controlled Avoid fast chaotic edits Maintain realistic physics and food textures Steam must remain visible in most scenes Food should always look fresh, glossy, warm, and appetizing Cinematic luxury advertisement quality throughout The AI MUST strictly follow all 9 storyboard panels in exact order without improvisationshow more

Claude Cowork Sub-Agents are f*cking cracked 🤯 One prompt... → 50 competitor ads analyzed, hooks extracted, and a full creative brief generated. 10 AI agents running in parallel, under 5 minutes. All inside Claude Cowork. Perfect for DTC brands and agencies who are still doing creative research and ad production one task at a time inside Claude. If you're analyzing competitor ads one by one, copying hooks into a spreadsheet manually, writing brief after brief from scratch, and watching Claude's output quality fall off a cliff after the 15th variation because the context window is completely bloated... Sub-agents eliminate the entire bottleneck: → Drop in a spreadsheet of 50 competitor ads and spin up 10 parallel sub-agents → Each sub-agent analyzes 5 ads simultaneously — hooks, angles, CTAs, emotional tone, creative format → They report structured summaries back to the main agent without bloating the context → The main agent synthesizes patterns across all 50 ads into a competitive intel brief → Then spin up another round of sub-agents to generate 30 ad copy variations across 10 personas → Each sub-agent writes for 1-2 personas in a fresh context — so variation 30 is as sharp as variation 1 No analyzing ads one at a time. No context window blowing up halfway through. No copy quality degrading after the first dozen variations. What this gives you: → 50 competitor ads broken down in minutes — hooks, angles, CTAs, formats, all structured → Pattern analysis across the full dataset that you'd miss reviewing ads individually → 30+ ad copy variations with persona-specific messaging that actually stays sharp → A workflow you can save as reusable skills and trigger with one command next time → The same output quality on the last task as the first Built 100% inside Claude Cowork with sub-agents. I put together a full DTC playbook: 5 bulk workflows with copy-paste prompts, the exact sub-agent prompting pattern, batching guidelines, and an honest breakdown of when this setup is worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)show more

NASA ARTEMIS II MISSION UPDATE: DAY 7 The crew... and the Orion spacecraft are approximately 57,157 km (35,518 mi) from the Moon. They are also about 380,631 km (236,512 mi) from Earth and are traveling at around 2,029 km/h (1,261 mph). The mission is currently 62.3% completed. Yesterday was a very big day for the mission as this culminated in the Lunar Flyby, which included the closest approach to the Moon at a distance of 4,067 km (6,545 mi), occurring at 11:02 UTC (MET+5/00:25). Following this, a record was set for the furthest distance humans had ever traveled from Earth, at a distance of 406,771 km (252,756 mi), which occurred at 23:02 UTC (MET+5/00:27). The crew also witnessed an Earthrise and solar eclipse during this time, before the lunar observation period concluded. Moving on to today's expected events, first up we have the crew wakeup, which is expected to occur at 15:35 UTC (MET+5/17:00). Following this, Orion will exit the lunar sphere of influence, which is expected to occur at 17:25 UTC (MET+5/18:50). Then, after that, will be the Crew Daily Planning Conference (PDC), which will occur at 18:05 UTC (MET+5/19:30). Moving on to the next event after that is PAO: Orion to ISS crew call (audio only), which is expected to happen at 18:40 UTC (MET+5/20:05). Then, following that, will be the Post Lunar flyby science debrief, which will occur at 19:00 UTC (MET+5/20:25). This will then be followed by a crew off-duty period that will start at 19:30 UTC (MET+5/20:55) and will last until 22:20 UTC (MET+5/23:45). Then, after that, will be the Return Trajectory Correction burn #1 (if needed) at 01:03 UTC (MET+6/02:28). And following that will be crew pre sleep at 04:35 UTC (MET+6/06:00), followed by the sleep period at 07:05 UTC (MET+6/08:30). And don't forget, you can tune into our Artemis II Real-Time Tracking 24/7 stream to watch the rest of the mission! NSF Artemis II Real Time Tracking 24/7 | NSF - NASASpaceflight.comshow more

GPT Image 2 + Seedance 2.0 on OpenArt Prompt:... Create a professional production storyboard sheet for a cinematic Japanese cooking video. Format: A wide horizontal storyboard layout, 16:9 aspect ratio, arranged in a clean 3x3 grid with 9 panels total. Thin black borders separating each frame. Warm parchment/off-white background like a printed production board. At the top center, add the title: JAPANESE BEEF BOWL — Production Storyboard Each panel should have a small white label box in the top-left corner with the panel number in brackets: [1], [2], [3], etc. Under each panel, add a short italic serif caption starting with a two-digit number and an em dash. Visual style: High-end cinematic food photography, warm rustic Japanese kitchen, moody amber lighting, shallow depth of field, steam, dark wooden table, handmade ceramic bowls, old kitchen tools in the background, realistic textures, glossy sauce, appetizing food details, premium commercial cooking video look. Storyboard panels: [1] Close-up of hands slicing raw beef into thick bite-sized pieces on a worn wooden cutting board with a large chef's knife. Caption: 01 — Slice beef into bite-sized pieces. [2] Close-up of beef pieces searing in a black cast-iron pan, caramelized golden-brown edges, sizzling oil, steam rising, chopsticks turning one piece. Caption: 02 — Sear beef until browned. [3] Close-up of soy sauce being poured from a small ceramic cup into the hot pan, dark sauce bubbling around the beef, steam filling the frame. Caption: 03 — Add soy sauce to the pan. [4] Beef pieces simmering in a thick glossy sauce, chopsticks lifting a glazed piece, sauce bubbling heavily in the pan. Caption: 04 — Simmer beef in the sauce. [5] A wooden rice paddle scooping freshly steamed white rice into a large handmade ceramic bowl. Caption: 05 — Scoop steamed rice into bowl. [6] Thick Japanese-style savory sauce being poured over the mound of white rice in the ceramic bowl, glossy dark sauce spreading over the rice. Caption: 06 — Drizzle sauce over rice. [7] Glazed beef slices being placed carefully over the rice with chopsticks, close-up, rich caramelized shine. Caption: 07 — Arrange glazed beef over rice. [8] Finished bowl being assembled with green onions, soft-boiled egg halves, pickled ginger, sesame seeds, and fresh vegetables around the beef. Caption: 08 — Add vegetables, egg, and garnish. [9] Final hero shot of the completed Japanese beef bowl on a rustic wooden table, glossy beef, golden egg yolks, steam rising, hands resting near the bowl, cinematic food commercial look. Caption: 09 — Completed beef bowl, hero shot. Make the entire storyboard feel like a polished production planning sheet for a premium Japanese beef bowl commercial. Keep every panel realistic, cinematic, warm, detailed, and consistent in lighting, color palette, kitchen environment, and bowl design. Video Prompt: CRITICAL INSTRUCTION: The reference image contains a 9-step chronological cooking storyboard for a Japanese Beef Bowl. Animate the chef seamlessly through these exact 9 steps in order. Start at Step 1 (Slice raw beef into bite-sized pieces), flow into Step 2 (Sear beef until browned), then Step 3 (Add soy sauce to the pan). Continue through Step 4 (Simmer beef in the sauce), Step 5 (Scoop steamed rice into bowl), Step 6 (Drizzle sauce over rice), Step 7 (Arrange glazed beef over rice), Step 8 (Add vegetables, egg, and garnish), finishing on Step 9 (Completed beef bowl hero shot). Prioritize the strict sequence of actions. No music. No subtitles. Location: Traditional Japanese kitchen. 15 seconds, 16:9, realistic, cinematic, appetizing, natural camera movement. Warm moody lighting, shallow depth of field, rich steam, glossy sauce, premium food commercial quality.show more

Seedance 2.0 on FlovaAI =================== Prompt: [Reference Identity Lock]... Image 1 is ONLY the main female protagonist. Her face, hairstyle, body type, and outfit must match Image 1 exactly and stay consistent for the entire video. Image 2 is ONLY a uniform reference. All four opponents wear the school uniform shown in Image 2. Never swap, merge, duplicate, or blend identities. The protagonist's identity comes ONLY from Image 1. The four opponents have NO reference images. They are defined by the text descriptions below. The four opponents must not resemble the protagonist, and they must not resemble each other. All five characters must remain clearly distinct and recognizable until the end. [Priority Order] 1. Preserve the protagonist's identity from Image 1. 2. Keep the four opponents visually distinct from her and from each other. 3. Maintain one continuous shot with no cuts. 4. Keep the classroom layout spatially consistent. 5. Make the action fast but readable and physically connected. 6. Keep the tone as a Korean school action drama, stylish but grounded. Korean school action drama classroom fight scene — 15 seconds, ONE CONTINUOUS SHOT, NO CUTS. A single uninterrupted handheld shot. No cuts, no scene transitions, no montage. The camera should feel handheld, with micro-jitters, slight rolling shutter, and raw unstable realism. The camera must physically travel through the same classroom space. Every transition must be motivated by camera movement, not editing. Whip pans are allowed, but they must not hide a cut. Do not teleport the camera or characters. The classroom layout and character positions must remain spatially consistent. Audio: No music. Only realistic school and classroom ambient sounds: old fluorescent light hum, distant hallway noise, ceiling fan, shoes scraping the floor, desks dragging, chair legs screeching, cloth friction, dull body impacts, and breathing that gradually becomes heavier. Breathing continues throughout the scene and keeps building. Lighting: Late afternoon in a Korean high school classroom. Mixed cool fluorescent light and warm sunlight through the windows. Dust floating in the sunlight. Soft fan shadows moving across desks and school uniforms. Main character: The Korean female high school student from Image 1, age 17–18. Cold, emotionless, calm, and intimidating. She barely speaks and does not scream during the fight. She remains composed from beginning to end. Her movements are efficient, explosive, and precise. Even if her frame is not large, she dominates through speed, timing, and accuracy. Main outfit: Exactly the outfit shown in Image 1. Do not change its colors, design, or details. Her jacket or outer layer is either removed and hanging on a chair, or worn in a slightly messy way. The action must be non-sexualized and combat-focused. Fabric movement, dust, sweat, wrinkles, and impact response should feel realistic. Opponent rules: Four Korean female high school students, all wearing the Hanlim Multi Art School uniform shown in Image 2. They have no reference images. Define them strictly by these descriptions and keep each one consistent: Opponent A: short black bob with straight bangs, medium build, round face. Opponent B: long straight hair tied in a high ponytail, tall and lean, sharp jawline. Opponent C: shoulder-length hair with side-swept bangs, slim build, narrow face. Opponent D: long wavy hair worn loose, slightly stocky and broad-shouldered. A, B, C, and D must each keep clearly different faces, hairstyles, body shapes, and silhouettes. They must not resemble the protagonist, and they must not resemble each other. No face duplication, no face merging, no identity confusion. Environment: An empty classroom at Hanlim Multi Art School, a Korean performing arts high school in Seoul. Green chalkboard, chalk tray, worn wooden desks, plastic chairs, classroom clock, class schedule poster, discipline/life-guidance posters, cleaning tools, blinds or curtains, wall study materials, and a slightly scuffed floor. Desks and chairs should react naturally to impacts, sliding, shaking, and collapsing when hit. Camera framing rules: Even during kicks, framing should stay around chest-level or eye-level. No low-angle shots under the skirt. Do not focus on legs, thighs, underwear, or fetish-like details. All action framing must prioritize faces, upper-body motion, impact, and spatial choreography. Continuous action and camera choreography: From 0 to 15 seconds, the fight continues without any cuts. The action should be stylish but readable, and every movement must be physically connected. 0–3s: The camera starts behind the protagonist at a slightly low handheld angle, drifting left through the classroom aisle. Opponent A grabs the protagonist's shoulder roughly and says in Korean: "야, 너 지금 뭐 하자는 거야?" The protagonist silently turns and lands one hard straight punch to A's face. At impact, use a very brief 15% slow motion: cheek ripple, dust particles, deep thud. A falls sideways into a desk. The camera dips slightly from the shock, then whip-pans right without cutting. 3–6s: Opponent B charges in from the right. The protagonist steps forward instead of retreating. A short body shot to the stomach. Immediate uppercut to the chin. Without pausing, she drives forward into a flying knee to B's chest. B is thrown backward across or into a desk. The camera follows the forward motion low, then rebounds upward with the impact. 6–9s: Opponent D attacks with two fast punches. The protagonist deflects both strikes with her arms, then flows into a turning backfist to D's face. As D staggers, she continues the same rotation into a spinning back elbow that lands hard on D's jaw or temple. D crashes sideways into two or three desks. The camera arcs around her shoulder and jitters slightly at each impact. No cuts. 9–12s: Opponent C rushes in from the chalkboard side. The protagonist clearly grabs C's collar with her left hand. C's face must be fully visible from the front and clearly different from the protagonist. The protagonist lands one short, hard punch to C's face, then immediately throws a powerful high kick or flying high kick into C's chest. The force sends C backward into the green chalkboard. The protagonist remains in the foreground and never touches the board. The protagonist's face should be side-profile or partially obscured. C's face should be clearly visible from the front at the moment of impact. Their faces must never overlap in frame. Use a very brief 20% slow motion at the chalkboard impact: chalk dust bursts outward, and C slides down the board. The camera pushes up with the impact, then tilts down as C slides. 12–15s: Through the chalk dust, the camera hard-pans right. D makes one final charge. The protagonist sidesteps and lands a tight uppercut to D's chin, followed immediately by a cross. D crashes into a row of desks, causing a chain reaction of collapsing desks and chairs. The camera drifts forward slowly. The protagonist adjusts her loose tie or ribbon and brushes chalk dust off her shoulder. Her expression stays cold and serious. She walks past the camera and exits the frame. Dust floats in the sunlight. Natural ending. =================== Made with Flova #FlovaAI #FlovaCPPshow more

What if one drink could shrink you into a... magical adventure? GPT image 2 & Seedance 2.0 on WaveSpeedAI 🎁Exclusive GIVEAWAY 🏆$10 credits × 10 Winners Requirements: ✅ Follow WaveSpeedAI & WaveSpeedAI CPP ✅ RT and WaveSpeedAI Prompt:- Step 1: Generate storyboard with GPT Image 2 Create a wide 9-panel cinematic storyboard infographic in a clean 3x3 grid layout. Use realistic photography, cinematic realism, and warm golden-hour color grading. Each panel must be clearly numbered (01–09), include a bold scene title, and 2–3 short bullet points describing the action. Design it like a professional film-production storyboard used by directors and cinematographers. STORY TITLE: "THE COKE DAYDREAM" MAIN CHARACTER: Beautiful adult Western woman, shoulder-length blonde hair, blue eyes, stylish red-and-black uniform, confident and playful personality. VISUAL STYLE: Photorealistic, cinematic storytelling, Unreal Engine quality, warm sunlight, shallow depth of field, realistic skin textures, beautiful bokeh, lens flares, filmic composition, professional storyboard presentation. LAYOUT: Wide horizontal storyboard sheet. 3 rows × 3 columns. Each panel separated by thin black borders. Large panel numbers in top-left corner. Bold panel titles. Short bullet-point descriptions. Consistent character appearance across all panels. PANEL 01 — "A SUMMER BREAK" • Blonde woman relaxes in a sunny park. • Holds an ice-cold Coca-Cola bottle. • Warm golden sunlight through trees. PANEL 02 — "THE FIRST SIP" • Cinematic close-up of Coke bottle. • Sparkling condensation and reflections. • She takes a refreshing sip. PANEL 03 — "THE MAGIC BEGINS" • Strange dreamy feeling appears. • World starts changing scale. • Magical atmosphere fills the park. PANEL 04 — "SHRUNK!" • Tiny woman standing on giant tree branch. • Massive leaves and grass surround her. • Discovers she has become miniature. PANEL 05 — "GIANT PICNIC WORLD" • Exploring a picnic table. • Huge apples, cakes, juice bottles. • Giant Coca-Cola can towers above. PANEL 06 — "BUMBLEBEE RIDE" • Friendly giant bumblebee arrives. • She climbs onto its back. • Adventure flight begins. PANEL 07 — "SKY ADVENTURE" • Flying through clouds and sunlight. • Hair blowing dramatically in the wind. • Epic fantasy journey. PANEL 08 — "CHAOTIC FUN" • Bee races through splash fountains. • Water droplets explode around them. • Exciting high-energy action sequence. PANEL 09 — "BACK TO REALITY" • Normal size again on grassy hill. • Drinking Coca-Cola peacefully. • Smiles toward camera as sunset glows. DESIGN NOTES: Professional movie-previsualization storyboard. Consistent warm cinematic color palette. Clear visual progression from reality → fantasy adventure → peaceful resolution. High-end film production quality. Magazine-quality infographic design. Readable typography. Balanced composition in every frame. Masterpiece, ultra-detailed, realistic photography.show more