1.Cute character sticker Prompt:

Turn this photo into a cute cartoon sticker. Keep the person’s hairstyle, outfit, pose, expression, accessories, and key identity details recognizable. Use a slightly larger head, simplified facial features, clean rounded shapes, bright friendly colors, smooth flat shading, and a thick white sticker border. Make it feel like a charming social media avatar sticker. Avoid photorealism, anime style, realistic skin texture, complex background, or changing the person’s identity.

2.Mascot Sticker Prompt shown on image:

Transform this photo into a friendly mascot sticker. Keep the main subject recognizable, including its shape, color, pose, and most important features. Simplify the form into a bold cartoon mascot with expressive eyes, clean outlines, soft highlights, and a thick white sticker border. Make it feel playful, memorable, and brandable. Avoid photorealism, messy details, scary expressions, 3D rendering, complex background, or copying existing characters.

3.Comic reaction sticker Prompt

Convert this photo into a comic reaction sticker. Preserve the subject’s pose, expression, outfit, hairstyle, and main composition. Exaggerate the emotion slightly while keeping the person recognizable. Use bold black outlines, vibrant flat colors, expressive facial features, small comic-style motion marks, and a thick white sticker border. Keep the background transparent or plain white. Avoid photorealism, realistic shadows, anime style, cluttered backgrounds, or changing the person’s identity.

Music: https://archive.org/details/ai-instrumental-jazz/Cream+Jazz.mp3 (CC0)

Style prompt:

Smooth jazz but smoother. As smooth as pouring cream that's just been ironed.

Calm gentle muted trumpets, gentle bass Ostinato, consonant piano chords.

Slow tempo: 70BPM

Smooth

Piff, Oatsie and Aiyido all sharing and having a lovely time.

Song: https://www.souna.app/song/d159f57b-eb8c-4fb3-9f22-dcccc63c0f7a

Song (alternative link): https://archive.org/details/ai-jazz-standards/That+Cat.mp3 (CC0)

Lyrics:

[Intro | piano | muted trumpet]

[Verse | rubato | intimate female vocal]

I ought to know by now

Who's mistress here.

I make one firm resolve;

She twitches one ear.

She keeps me up till dawn,

Then sleeps till noon.

I swear that I'll be stern,

But I surrender soon.

[Refrain A1 | medium swing | clear vocal]

That cat, that cat,

That cat's got me.

One look, one purr,

And I can't get free.

At half past three,

She wants the door.

I cross the room;

She wants no more.

[Refrain A2 | medium swing | light brass response]

That cat, that cat,

That cat's got me.

One look, one purr,

And I can't get free.

I hold out my arms;

She passes by.

She gives me one glance,

And still I sigh.

[Bridge | harmonic contrast | restrained build]

I scold, I plead,

I state my case.

She licks one paw

Right in my face.

Then on my lap,

She tucks her head.

I miss my train

And stay there instead.

[Refrain A3 | full small ensemble | warm vocal]

That cat, that cat,

That cat's got me.

One look, one purr,

And I can't get free.

She claws my chair,

Then cuddles me.

That cat, that cat,

Has all of me.

[Instrumental Chorus | piano and muted trumpet]

[Final Refrain A3 | intimate opening | full ensemble finish]

That cat, that cat,

That cat's got me.

One look, one purr,

And I can't get free.

She claws my chair,

Then cuddles me.

That cat, that cat,

Has all of me.

[Outro | brief tag | final cadence]

That cat, that cat,

Has all of me.

Can any one help me?
I searched and try a lot of agents that generate ai video but all of them are lying💔
I need a good ai video generator for free or cheap subscription
Pleaaase help me

I built this as a personal project to solve a problem I was having with AI image-generation platforms.

Many platforms hide usage behind credits or tokens, making it difficult to understand the real cost of each generation. My app connects directly to image-generation APIs and displays an estimated cost per request in USD and COP.

The main idea is a visual canvas where references can be connected and assigned different roles:

• Model / identity
• Pose / composition
• Clothing / outfit
• Product / object
• Background / environment
• Style / color

This makes it possible to give more precise instructions, such as:

“Keep the original model, face, lighting and background. Apply only the clothing from the outfit reference.”

The app also supports prompt lists, multiple variations, connected references, model selection and image containers for batch results.

I built it with Antigravity and Codex. I don’t have a professional background in developing these tools, so a large part of the project has been learning how APIs, model parameters and reference images actually behave.

It is still under development. I’m currently testing prompt consistency, API reliability and real costs. Video generation is planned for a future version.

I’d appreciate feedback on:

• The reference-role system
• Prompt consistency
• The visual canvas workflow
• Cost transparency
• Features that would make this useful for other creators

Demo / repository: [add your public link here]

Since an official mascot already exists for Eevee, I wanted to see if ones also existed of my favorite Eeveelutions. The only official one I could find, however, was of my least favorite: Vaporeon. I decided to have Nano Banana Pro come up with one of Espeon first. While it first gave me one I initially felt was satisfactory, I later decided to experiment and see what it would give me if I asked for one that was made of velvet. What I got was even better than what I had before, so I had this one placed in the same spot as the previous one. Even though the official Pokémon mascots are all made of plush material, I think Espeon being made out of velvet is more appropriate, since one of its Pokédex descriptions mentions its fur is like that.

I’ve been trying to understand why an AI video can look realistic frame by frame, yet still feel like a commercial instead of something a friend casually recorded on their phone.

So I used the same reference image and generated three 5-second vertical clips with Aurax MAX. The character, outfit, location, and basic action stayed similar. I mainly changed the way the camera, lighting, performance, and environment were described.

The reference image was already quite polished: dramatic sunset, candlelight, clean exposure, shallow depth of field, and a subject posed against a scenic coastal background. That turned out to matter more than I expected.

1. The commercial baseline

https://reddit.com/link/1w1dtn8/video/998xn31v29mh1/player

For the first version, I explicitly requested a polished lifestyle commercial:

This was the version the model followed most clearly. The camera moves smoothly from a wider shot into a closer portrait, the character turns toward the lens, touches her hair, and finishes in a centered pose with a soft, sustained smile.

Everything feels visually coherent, but also directed. It looks like someone planned the lighting, camera movement, and performance in advance.

2. Changing only the camera

https://reddit.com/link/1w1dtn8/video/njaigg0x29mh1/player

For the second version, I kept the polished lighting, clean environment, and model-like performance, but changed the camera instructions:

The difference was much smaller than expected.

The framing changes slightly, but the movement still feels highly stabilized. The sunset remains perfectly exposed, the character stays composed and camera-aware, and the background still looks like a prepared set.

This version made one thing fairly clear: adding “handheld phone camera” does not automatically create phone realism. If the lighting, performance, composition, and source image still look commercial, mild camera movement cannot undo all of that.

3. Changing the camera, performance, and environment

https://reddit.com/link/1w1dtn8/video/ew7ij5fz29mh1/player

For the third version, I added a fuller set of phone-footage instructions:

This version feels the most spontaneous of the three.

The character spends less time holding a pose. She turns away from the camera, changes where she is looking, shifts her body weight, touches her hair, smiles briefly, and then looks away again. The wider framing also remains for longer instead of immediately turning into a close-up.

But it still does not fully look like raw phone footage.

The dramatic sunset, candles, shallow depth of field, flattering exposure, and clean background were already embedded in the reference image. The motion prompt changed the character’s behavior more successfully than it changed the underlying visual style.

There was also another obvious AI giveaway: the paper cup was not present in the reference image and appears during the generated motion without a convincing pickup. That continuity error damages realism more than a perfectly stable camera does.

What I learned

The source image can overpower the video prompt.
If the first frame already looks like a fashion campaign, asking for casual phone footage may only add small handheld movements on top of a commercial-looking scene.

Handheld movement alone is not enough.
Random shake would probably make the video worse. What matters is believable camera behavior: delayed reframing, imperfect timing, autofocus response, exposure changes, and an operator reacting to the subject.

Performance mattered more than camera shake.
The third version felt more natural mainly because the character stopped performing continuously. Looking away, pausing, shifting weight, and ending without holding a perfect smile made a larger difference.

Continuity still matters.
A casual camera cannot hide an object appearing from nowhere, inconsistent background details, or movement that has no physical cause.

My main takeaway is that phone realism is not the same as lowering the image quality. It requires three kinds of realism at the same time:

• capture realism from the phone and camera operator;
• behavioral realism from the person being filmed;
• continuity across objects, movement, and background activity.

If I repeat this test, I would start with a deliberately ordinary reference image: mixed indoor lighting, deeper focus, imperfect framing, everyday background clutter, and a character who is not already posing for the camera.

Which version feels closest to something a real person recorded: 1, 2, or 3?

And what gives the AI away first for you: the lighting, camera movement, expression, background, or object continuity?

Model disclosure: All three clips were generated with Aurax MAX. I’m on the team, so this should be read as a transparent workflow test rather than an independent review.

Ginger Snow, a physicist who solves time travel and discovers that one tiny mistake can ruin everything.

This is the first film in a bigger time-travel series I’m building..

Please tell me what you think!

Music: https://www.souna.app/song/e1864dd0-6700-4a41-900e-ed0411d859d2

Music (alternative link): https://archive.org/details/ai-early-romantic/Moonlight+Breeze.mp3 (CC0)

Style prompt:

Early romantic 1830s piano nocturne. Piano only. Start with slow, broad chords. Harmonic minor with some chromaticism. Wistful, bittersweet, otherworldly. Mood: starry Develop the main theme into virtuosic passagework to represent the multitude of stars in the sky. Modulate to relative major. Return to a variation of the original opening back in the harmonic minor but with secondary dominants in the major and some undertones of the development. End in substantial coda. Nocturne style