What's the first thing that comes to mind when you look at this character? Majesty, power, mystery, something else? I'm curious about your first impression.”

Where the Heavens Meet the Sea.

I've made a animation character and I'm struggling to really produce a comedy sketch video of about ten seconds each.

What I want to achieve:

Running an open video model and not be tied to an expensive video platform, If that is even possible. Basically queue my ideas of videos to create, fire up gpu, run them through a video model, have decent output and iterate where needed.

What I did so far:

- Create a character pack about 20 images in different poses.
- set up a quick workflow where a sketch is written through AI and then I'm trying to generate it as a test.
- Technically: I'm running Minimax H3 on a GPU and asked Claude to write prompts based on sketch ideas that specifically can steer H3 to get correct video output.

Where I'm struggling is that the sketch writing is pretty crap (even Opus 5.5 seems not great at it) and I'm not sure if any AI model can give me decent sketch ideas and morph it to correct prompting towards a video model. The video quality output itself is ok but not perfect, sometimes the character has some weirdness to it, so suddenly a third arm pops up or some movement seems weird.

Just to be sure, I'm really starting out with this and definitely not an expert. I've just asked GPT what would be best to start with for what I want to achieve and this setup seemed to be best. I'm not sure i'm on the right path. Days of testing still delivers no improvement.

Anyone who has experience and can advise what to do?

I've spent about 7 days building a North Atlantic island in Unity URP (WIP). I wanted to see how much I could enhance my tech art and graphics programming abilities with AI, using mosty Opus 5.5 and Astra for a few critiques on techniques used.

The goal: one island you can walk across from the surf to a snowy summit, that looks good wherever you stop and look around. The terrain is real elevation data from Lofoten in Norway, reshaped and modified into an island about 4 × 5 km with a 1,000 m peak. Overcast is normal, fog is common and sunshine is rare.

Not a single thing was placed manually, there's procedural systems to place anything from fallen leaves to the meso-/macro-scale terrain changes, undergrowth and rock placement etc. AI-generated procedural systems produce all the terrain surfaces, generate most of the trees, plants and grasses and their placement. Some rocks fallen trees are pre-made assets, but some of those too are procedurally manipulated.

So far: the terrain and its rock, moss and heath; birch and pine forests from my own tree and forest generator, 25,000+ trees; and hundreds of thousands of ferns and ground plants; an ocean with waves and surf, underwater visuals with caustics, lakes, ponds with murky water, a stream and a waterfall; clouds that form and dissolve; rain, fog, starry sky and a full day cycle.

Terrain surfaces are textured in high-resolution with quite high pixel density (per metre) detail with diffuse color and normals, and some surfaces also utilize parallax mapping. These details are then blended together based on a set of rules which take the local terrain shapes, altitude and a few other factors into consideration. There's no "distant" locations on the island, every spot is equally detailed.

Trees and the undergrowth plants have a wind deformation system, and they react to rain visually. Various fine-grained growth and placement rules exist, as an example lichen grows more likely certain spots of the rocky hillsides and big rocks, pond water is still if wind doesn't touch it, etc.

The system currently has kilometres of draw distance, custom volumetrics, atmospheric system, lighting/shadow-casting and geometry generation in compute shaders.

Footage straight from the engine, running well above 60 fps at 1440p. Work in progress.

Wildlife and sound not yet implemented.

Terrain based on Nasjonal høydemodell DTM 1 m, © Kartverket (CC BY 4.0), modified.

Hello, I’ve recently been working on a Discord bot demo, specifically a *Blue Lock* roleplay bot. I’ve run into a bit of a dilemma is it possible to ask players for their characters' traits, convert those into a prompt, and then have an AI generate a completely unique character design based on that? I’ve already trained an AI and created a model on Hugging Face, but when I tested it... the results were terrible. Is there a better way to go about this, or is this even feasible?

Daenerys’ Diet #diet #daenerystargaryen #gameofthrones #dietplan #food

TLDR: Instead of telling the AI what to change, try describing the change in what you would physically see in the image.

I've been generating and editing a lot of AI images lately, and I've noticed something that might be helpful to other people. When you're trying to fix something in an image, it seems to work a lot better if you describe exactly what you want to see rather than just telling the AI what to change.

For example, I had an image of a guy giving a thumbs up, but the AI had given him two left hands. I kept telling it to change the one hand to a right hand, but it just kept making the same mistake. Instead of telling it to fix the hand, I described where I wanted the fingers and thumb to be visible from the viewer's perspective. It fixed it immediately.

I've noticed the same thing with changing camera angles. If I tell it to rotate the camera 90 degrees, sometimes it barely changes anything. But if I describe what that angle would actually look like, like seeing the guy from the side with only one side of his face visible and his other arm mostly hidden behind his body, it seems to understand that much better.

It's made a pretty big difference for me, especially when the AI keeps repeating the same mistake over and over.

Just thought I'd share in case it helps anyone else. Curious if anyone has noticed this too.

Hey y’all!

I'm getting married in a few weeks, and I'm hoping this community can help me figure out how to create a video for my wedding reception.

A little backstory: My mom passed away from cancer in 2024. One of the traditional moments at a wedding reception is the mother-son dance, and unfortunately, that's something I won't get to experience with her.

So, I had an idea to create an AI-generated video of my mom and me dancing together through the years. Basically, I'd love to show us dancing at different stages of my life, from when I was a little kid to my teenage years, and eventually to me as an adult at my wedding.

I've already experimented with Higgsfield and Seedance to create a few scenes and snippets. Some have turned out pretty well, but I've struggled with getting consistent faces, natural movements, and making the dancing look believable.

What I'm looking for and what I would need help with...

I've seen tons of Instagram Reels and TikToks where people use AI to put their faces onto other people's bodies, whether they're doing elaborate dances, funny stunts, or recreating movie scenes. Some of these look pretty realistic.

I'm wondering if I could use the same approach for my video.

For example, if I found an existing video of a mother and son dancing, could I use AI to replace their faces with mine and my mom's? Ideally, I'd like to find different dancing clips with various camera angles and perspectives, swap in our faces, and stitch everything together into one video.

A few questions:

1. Are there any apps or websites that make this kind of video face-swapping relatively easy?
2. Can these tools work with two faces in the same video while keeping their appearances consistent?
3. Would it be easier to use existing dance footage and swap faces, or generate the scenes entirely through AI?
4. Has anyone done something similar and can recommend a workflow that doesn't require extensive video editing experience?

I already have plenty of photos of my mom and me from different stages of my life, so reference images aren't an issue. My biggest priority is getting our faces to look like us while making the dancing feel natural.

The final video would probably be around 2–3 minutes.

This is obviously a pretty personal project, and I'd love to make something meaningful that I can share with my family during the reception.

Any recommendations, tutorials, tools, or workflows would be greatly appreciated.

Thanks so much, y'all!

I'd like to find a tool thats good at creating realistic life-like characters where I can control facial fractures in detail.

What's the best options? Ideally free or not too expensive.

Luminous Relief Synthesis (LRS) Formal Technique Specification — Version 1.0 Canonical demonstration: Where the Heavens Meet the Sea (2026), generated visual study Status: Proposed, reproducible artistic synthesis; not an established historical art movement or a proven first-of-its-kind technique. Media: Oil or acrylic/mixed-media painting; digital painting; generative image workflows. 0. Concise definition Luminous Relief Synthesis is a scene-building method in which (1) a legible representational composition, (2) an atmospheric light field, (3) directional sculptural mark-making, (4) a rhythmically organized geometric vocabulary, and (5) selective ornamental highlights are controlled by the same visual flow structure. Form establishes the world. Light establishes atmosphere. Texture communicates motion. Geometry establishes rhythm. Ornament communicates significance.

Crucial distinction: LRS is not a collage of five historical styles. Its defining rule is that several kinds of visual information must agree about what is happening in the scene. Marks should not be independently placed because they look attractive; they should encode motion, illumination, hierarchy, or symbolic emphasis.

1. Verified historical foundations Artist Documented technique Specific LRS inheritance What is NOT inherited Vincent van Gogh Thick, directional, rhythmic strokes; impasto; juxtaposed complementary colors Raised or simulated marks show energy, force and directional movement Reproduction of familiar compositions or signature subjects Claude Monet Broken strokes, perceptual emphasis on fleeting illumination, colored shadows A coherent, colored atmosphere unifies distinct surface treatments Uncontrolled blur or indiscriminate pastel coloration Katsushika Hokusai Strong key-block outlines, multiple aligned color layers, sophisticated large/small form placement Clear contour hierarchy, compressed silhouettes, controlled overlap and perspective Copying The Great Wave or recurring iconography Wassily Kandinsky Form/color relationships, geometric abstraction, rhythmic and musical associations A geometric 'score' reinforces visual motion and emotional cadence Random floating circles or shapes without compositional meaning Gustav Klimt Gold leaf and other metallic media; ornamental geometry; variations in surface reflectivity Precious-looking accents encode significance, focal hierarchy and material contrast Gold covering every surface by default

These artists were historically influential and drew from overlapping cultural traditions; their tools are not exclusive property of any one artist. The LRS synthesis and its parameters below are contemporary design proposals, not claims about the artists' own working recipes. Supporting references

1. National Gallery of Art — Van Gogh's directional, rhythmic strokes: https://www.nga.gov/educational-resources/mind-van-gogh
2. National Gallery, London — definition and uses of impasto: https://www.nationalgallery.org.uk/paintings/glossary/impasto
3. Metropolitan Museum of Art — Impressionism, broken strokes, color, and light: https://www.metmuseum.org/pt/essays/impressionism-art-and-modernity
4. Metropolitan Museum of Art — Monet's methods and pictorial development: https://www.metmuseum.org/toah/hd/cmon/ho_56.135.1.htm
5. Metropolitan Museum of Art — scientific analysis of Hokusai's Great Wave printing: https://www.metmuseum.org/en/about-the-met/conservation-and-scientific-research/conservation-stories/2020/hokusai-great-wave
6. British Museum — Hokusai's key-block production: https://www.britishmuseum.org/hokusai-resources
7. Guggenheim — Kandinsky's geometric/color relationships: https://www.guggenheim.org/artwork/1992
8. Museum of Modern Art — Kandinsky's interests in color and basic geometric forms: https://www.moma.org/artists/2981-vasily-kandinsky
9. Belvedere Museum — Klimt's gold, materials and surface effects: https://www.belvedere.at/en/stories/why-did-gustav-klimt-use-gold
10. Belvedere Museum — conservation and layering details in The Kiss: https://sammlung.belvedere.at/objects/6678/der-kuss-liebespaar
11. The five non-negotiable laws
12. Representational anchor. A recognizable subject must remain readable at thumbnail size. The entire scene may not dissolve into undifferentiated ornament.
13. Shared flow. The subject's directional forces determine the orientations of marks and the arrangement of abstract accents. This is the distinctive coupling mechanism.
14. One consistent light logic. Establish a principal light source and an environment-wide response. Metallic gleams may be stylized, but they should be intentionally exceptional rather than accidentally contradictory.
15. Unequal hierarchy. Texture, geometric density and ornament must differ by region and depth; not all regions may compete equally.
16. Earned ornament. Every conspicuous gold/metallic or geometric intervention should support a focal point, a rhythm, a transition, or a deliberate symbolic idea. Failure of any law indicates that the image is a related hybrid image, but does not fully satisfy this LRS v1.0 specification.
17. The LRS field model At each location p = (x,y) on a normalized canvas, define five conceptual fields:

• D(p) — depth, from foreground to background.
• F(p) — flow, a two-dimensional vector representing perceived movement (wind, water, foliage, cloud or the intended reading path).
• L(p) — light, including intensity, hue, incidence and atmospheric scattering.
• S(p) — salience, or importance to the composition and narrative.
• M(p) — meaning, a semantic map identifying regions where deliberate ornament is appropriate. These are design maps, not required physical simulations. A human painter may establish them with a few arrows and shaded diagrams; a digital artist may use separate editable layers or masks; a generative workflow may express them in prompt or conditioning instructions. Derived operations Texture: orientation(p) ≈ angle(F(p)). Larger/more legible directional strokes belong where motion and salience are high; small subdued strokes may describe calm or distant regions. Contour: outline_strength(p) = f(subject boundary, S(p), D(p)). Make nearer or important silhouettes crisp; simplify or soften far-away forms unless a deliberate exception serves composition. Geometry: geometry(p) = motif_family + rhythm(F(p)) + emphasis(S(p)). Repetition and spacing respond to movement and focal hierarchy; shapes are not scatter decoration. Ornament: ornament_density(p) = g(S(p), M(p), L(p)). Gilding may highlight importance or symbolic resonance, and its reflections should usually support the lighting structure. Atmosphere: color(p) = local_material_color ⊕ illumination ⊕ depth_haze, where ⊕ signifies artistically combined influences, not a mathematically specified blending function. None of these expressions assumes empirically calibrated weights. They describe dependency relationships and can be implemented as manual art direction or software constraints.

1. Canonical visual grammar 4.1 Scene architecture Establish three legible spatial bands: foreground / middle distance / background. Depth is necessary even when parts of the picture are intentionally flattened. A common working arrangement is intricate foreground, recognizable middle scene, restrained distant silhouettes — but the subject can reverse it if intentional. 4.2 Gesture and contour Choose one dominant gesture for the entire canvas: arc, rising diagonal, spiral, wave, radial burst, or horizontal drift. Add at most two subordinate gestures. All strong brushwork, key contours, geometric ornaments and reflections must either echo, counterbalance or intentionally interrupt these gestures. Contours have three jobs: define important silhouettes, protect object recognition where textures are energetic, and separate overlapping forms. Avoid outlining every leaf, wavelet and cloud identically. 4.3 Color and light Start with a base temperature relationship (for example, cool blue environment and warm gold light). Establish a single principal light direction and its reflections; use colored shadows rather than default black. Juxtapose discrete neighboring colors to make apparent light without airbrushing the entire canvas. Preserve dark, medium and bright value groups so that the design reads in grayscale. 4.4 Directional relief The relief system uses three levels: Level Function Typical region Low Quiet support; atmospheric fields Distant mountains, diffuse sky, large calm surfaces Medium Form and directional information Trees, architecture, shoreline, mid-distance water High Narrative energy and illuminated emphasis Cresting waves, prominent flora, cloud eddies, focal highlights

Rules: stroke orientation follows form or flow; width and height are varied intentionally; focal impasto should not obscure the focal object's silhouette. In a digital image, 'height' refers to visible simulated physical relief, not actual material thickness. 4.5 Geometric rhythm Pick a restrained motif vocabulary (for example, rings + short radiating lines + rare triangles). Repeat the motifs with meaningful variation in scale, spacing and orientation. A circle might recur as a cloud vortex, wave curl and floral rosette; each recurrence must belong to the depicted world rather than sitting on top as an unrelated sticker. 4.6 Ornament Use gilding sparingly enough that it remains special. Favor seam highlights, rhythmic node points, select reflected glints and significant object details. Avoid whole-image gold noise. If everything gleams, nothing carries hierarchy. 5. Reproducible 10-stage process Phase A — Design Stage 1: Specify intent. Write a one-sentence emotional thesis, a concrete subject, and the kind of movement the scene should suggest. E.g. 'A harbor feels serene yet dynamically alive.' Stage 2: Establish depth and reading path. Make a thumbnail in three value groups and mark one main visual route from entry to focus to secondary interest. Confirm that the silhouettes are recognizable without ornamental detail. Stage 3: Draw the flow field. Mark arrows for wind, waves, fabric, vegetation and cloud motion, and a separate arrow for intended eye travel. Reconcile contradictions deliberately. Stage 4: Fix lighting and palette. Design primary light, shadow temperature and reflective surfaces. Make a small color study without metallic accents. Phase B — Construct Stage 5: Build atmospheric masses. Establish broad local color, colored shadows, haze, and luminous transitions. Don't resolve all detail at once. Stage 6: Reinforce anchor shapes. Resolve focal silhouettes, overlap, perspective and strong contours; treat contour clarity as structural scaffolding. Stage 7: Lay directional relief. Add directional strokes at low/medium/high density in response to the flow field. Check for variation in width, stroke length, edge sharpness and apparent thickness. Stage 8: Compose geometric rhythm. Develop repeated shapes along the established gesture. The shapes should feel like an extension of the world's motion, not a second disconnected composition. Stage 9: Add earned metallic ornaments. Map focal importance and semantic motifs; place gold-like highlights only where the ornament contributes. Inspect the image without ornaments to verify it still works. Phase C — Validate Stage 10: Run reduction tests. Examine the work as a thumbnail, grayscale, blurred view, edge-only view and full-size detail. Remove clutter. Confirm that high-contrast texture, geometry and gold do not overpower the subject or erase atmospheric depth. 6. Suggested tuning ranges (heuristics, not historical facts) These are initial working defaults, not scientifically derived standards or rigid acceptance rules. Control Default starting point Notes Main gesture 1 dominant + 0–2 subordinate Extra dominant gestures weaken coherence Spatial depth 3 legible zones May compress for portraits or near-abstract scenes Palette 2 prevailing temperature families + small accents Material/local colors can expand actual pigment count Geometric motif families 2–3 Repeat with meaningful variation Gilded/metallic coverage Approx. 2–10% of total canvas area Measure only if useful; distribution matters more than exact percent Peak relief emphasis Concentrated in selected areas Avoid uniformly 'maximum texture' rendering Focal hierarchy 1 primary, 1–3 secondary interests May differ in large narrative works Contour hierarchy Strong near focal boundaries; softer elsewhere Use exceptions consciously

1. Manual, digital and AI implementation Physical painting

2. Work with a drawing and color underpainting before building relief.

3. Use paint consistency and palette knives or brushes to make directional ridges. Test material compatibility and curing/drying properties before combining mediums.

4. Reserve metallic leaf or paint for late-stage controlled accents unless testing a deliberate underlayer technique.

5. Observe the real artwork in oblique illumination: physical impasto and metal reflect differently as light and viewing angle change.

6. Do not treat archival stability as guaranteed: grounds, adhesive size, coatings, medium ratios and drying time require medium-specific testing. Digital painting

7. Put structure, flow, atmosphere, contour, relief, geometric rhythm and ornament in distinct editable groups.

8. Use directional brushes with varied opacity, raised-edge normals/height maps or carefully rendered light/shadow on paint ridges.

9. If available, store Flow, Depth, Salience and Ornament masks separately.

10. Metallic glints need localized contrast, sharp transitions and restrained highlights; static gold-colored pixels cannot truly reproduce changing metallic reflectance.

11. Evaluate at intended display resolution to detect repetition or synthetic-looking stroke patterns. Generative-image direction Specify relationships instead of merely listing stylistic adjectives: 'Brush ridges follow wave currents; decorative rings reinforce those currents; glints collect on focal crests and selected floral forms; distant cliffs are quieter and cooler.' After generation, critique the output with the tests below and iterate. A successful prompt demonstrates a visual approximation; it does not prove a physical painting process occurred or establish novel artistic authorship by itself.

12. Canonical reference example: Where the Heavens Meet the Sea Subject: a Mediterranean-like imaginary harbor at twilight, viewed from a flowering hillside.

• Depth: tactile flowers and masonry in the foreground; town, harbor, boats and coastline in the middle; mountains and horizon behind.
• Principal gesture: swirling celestial arcs echoed in the curls of waves and curving foliage.
• Light: warm sunset and harbor illumination against cool marine blue and purple shadows.
• Texture: visibly thick painted ridges in flowers, clouds, water and rocks.
• Contour: distinct tree silhouette, sailboat shapes, cliff edges and wave crests.
• Geometric rhythm: circles, orbital rings, radiating lines and occasional triangular shapes integrated into sky and water.
• Ornament: golden petals, mosaic-like foreground fragments, atmospheric accents and reflected highlights. Critical qualification: The reference image is a generated two-dimensional image that depicts impasto and metallic surfaces. It is not documented as an actual oil painting or gold-leaf object. The example also approaches visual-density overload in its busy foreground and gilded sky; stricter LRS executions may benefit from deliberate quieter regions.

1. QA rubric and definition of done Score the following six dimensions on a 0–4 artist-assigned scale (0 = absent, 1 = weak, 2 = mixed, 3 = strong, 4 = exceptional). This is a review heuristic, not a validated psychometric measurement. Criterion What to inspect Readability Can the primary subject be identified quickly at thumbnail size? Flow coherence Do brushwork, contours and geometry support a common motion? Light integrity Do local colors and reflected highlights largely obey a consistent atmosphere? Depth & relief Does texture/edge specificity vary appropriately across spatial planes? Ornament discipline Is each major accent meaningfully placed, without overwhelming the focal point? Artistic unity Does the work feel like one visual language instead of five collaged styles?

Suggested approval rule:

• All five laws of §2 satisfied.
• Each rubric dimension scores at least 3/4, with a total of 20/24 or higher.
• The artist documents any deliberate exception to a rule and explains how it improves expression.
• A second reviewer can identify the primary gesture, focal point and lighting intent without being told. These thresholds define a convenient studio acceptance criterion, not an objective standard of artistic merit. Common failures and remedies Failure Diagnosis Remedy Gold everywhere Ornament loses meaning Remove gold from nonfocal areas Every mark swirls Flow feels monotonous; objects lose form Restore quiet strokes and counter-direction Geometry looks pasted on Shape motif isn't linked to motion Reposition/scale according to flow field Foreground and background equally sharp Depth collapses Suppress far edges, relief and contrast Colors luminous but shapes unreadable Color overwhelms structure Recheck thumbnail and silhouette Obvious imitation of one famous painting Synthesis lacks independent composition Change subject, staging, silhouette, and motif map Digital relief mistaken for physical relief Medium represented inaccurately Label as simulated texture and avoid physical medium claims

1. Reusable compact brief Reference prompt (adapt the bracketed concepts): Create an original Luminous Relief Synthesis artwork of [subject] expressing [emotion]. Establish a recognizable three-plane composition with a dominant [gesture] visual flow. Maintain [light source] and [palette temperature contrast] throughout the environment. Build perceptual atmospheric depth with broken-color transitions and colored shadows. Add crisp, selectively hierarchical contours to preserve shapes. Render sculptural, directional brush ridges that follow forces in wind, water, fabric or vegetation and vary by depth. Introduce [two or three geometric motifs] whose repetition and orientation reinforce those forces. Place precious-metal-like ornament only at selected points of symbolic or compositional significance; keep calm, materially quiet areas. The piece must read as one coherent visual language, not a collage of recognizable historical paintings. Do not reproduce an existing artwork.

Review instruction: 'Critique against the five LRS laws and six QA dimensions. Report explicit failures before any revision.' 11. Change-control and extensions

• v1.0: foundational definitions, field dependencies, ten-stage process and pass/fail rubric.
• Potential v1.1: three alternative motif vocabularies, standardized brush/height-map libraries, and controlled side-by-side trials against a generic mixed-style baseline.
• Potential v2.0: explicit machine-executable spatial masks, reproducible rendering pipeline, and comparative evaluation using multiple reviewers and multiple subjects. Honest originality statement: LRS is a named, articulated synthesis of historical methods and contemporary art-direction rules. Its operational specificity is real; absolute historical novelty, ownership of common methods and exclusive aesthetic distinctiveness are not established.

I mainly use chat gpt and ask it to edit / photoshop images for me.

For example, had a pic of my daughter looking scared holding onto the pull up bar. Asked it to make it look like she was hanging off a branch in a tall tree, just for jokes creating silly images.

But I always get a generic "against our code of conduct type response"

Is there any other ai app that can create images without such strick rules

Thanks

PUZZ LOOP: Arcade marble chaos rebuilt in native C++! 🔴🟡🔵

I had GPT 6 Astra analyze and disassemble the original 1998 arcade ROM, then build a fresh native Linux reconstruction with 100% procedural graphics, music and sound effects.

• C++17 + SDL2, with custom gameplay code running natively.
• 12 new stages across four visual themes, plus endless Panic mode.
• Matching three or more marbles, magnetic gap closure and cascading chain reactions.
• Procedural shaded marbles, engraved tracks, particles and animated score effects.
• Synthesized stereo soundtrack and responsive sound effects.
• Mouse aiming, marble swapping, pause and fullscreen.
• 1080p / 60 fps gameplay export with synchronized audio.

The autoplay uses normal shooting and collision rules and successfully completed all 12 stages.

A new reconstruction informed by real SH2 disassembly, with newly written gameplay and levels. It is not an exact decompilation of the original.

[Verse 1] Your hand on my waist Got me losing my name Skin damp, no shame You pull me in closer

Fingertips on fire Dragging slow down my spine My shirt half off And your mouth says mine

[Pre-Chorus] Lock the door Let it stay dark Room gets small When you hit my heart

Close like this I can’t think straight Your body talks And I obey

[Chorus] Keep your hands on me Keep your hands on me Make me weak in the sheets Keep your hands on me

Hot and reckless All up in my skin We get tangled up And do it again

[Verse 2] Your breath on my neck Leaves a bruise of heat I bite back words You drag them out of me

Bare legs, no rush Sweat on the linen We make a mess Then dive back in it

Your nails, my back That kind of fight We go too far Then stay all night

[Pre-Chorus] Lock the door Let it stay dark Room gets small When you hit my heart

Close like this I can’t think straight Your body talks And I obey

[Chorus] Keep your hands on me Keep your hands on me Make me weak in the sheets Keep your hands on me

Hot and reckless All up in my skin We get tangled up And do it again

[Bridge] Slow down Then don’t Say my name Then moan

Hold me tight Till I bend Come back hard Again

[Chorus] Keep your hands on me Keep your hands on me Make me weak in the sheets Keep your hands on me

Hot and reckless All up in my skin We get tangled up And do it again

Hi, I've been trying to create a simple "Spot the Difference" activity for my kids at school, but dispite warnings of global dominance and human subservance, img gen appears to be incapable.
Any suggestions that could provide a simple solution or a model that can deal with this request?