Convert images into optimized AI prompts for image generation
Create bicep heart trend videos from a single portrait using AI
Stage
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Founded
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Based in
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Pricing model
Freemium
Paid
Pricing
360 Credits: $7.9 (discounted from $9.9), valid for 1 month. 800 Credits: $15.9 (discounted from $25.9), valid for 1 month. 1500 Credits: $25.9 (discounted from $42), valid for 1 month. All plans include Image to Prompt, Prompt Enhancement, Text/Image to Image, Private Generation, Commercial License
One attempt: $9.99 USD (1 credit); Three attempts: $24.99 USD (3 credits); Seven attempts: $49.99 USD (7 credits). One-time purchases with no subscription. Each generation attempt uses 1 credit.
Key features
Multi-Model Support: generates optimized prompts for General, Stable Diffusion, and Flux models
Detailed Image Analysis using GPT technology to extract composition, style, colors, and subject details
Aspect & Resolution Detection that provides ideal ratio and resolution information
One-Click Generation from uploaded reference images
Direct Image Generation on platform using GPT-Image and Flux models
Prompt Enhancement to transform simple text descriptions into detailed prompts
Fixed pose template requiring no custom prompts or reference videos
Local photo preview before uploading or generating
6-second 720p MP4 video output in 3:4 portrait format
Seven-day account-protected download period
Silent video with no watermark
Supports JPEG, PNG and WebP formats up to 8 MB
Powered by Seedance 2.0 Mini AI model
One-time credit purchases with no subscription
What makes it different
Saves 95% time compared to manual prompting
GPT-4 Vision powered analysis for highly accurate prompts
Supports 3+ compatible AI image models with single interface
Preset fixed pose template specific to the bicep heart trend, eliminating need for custom prompts
Transforms a single portrait into animation without reference video uploads
Local preview of photo quality before committing credits
Affordable one-time purchases starting at $9.99 for single attempts
Real AI results with transparent limitations and examples