This content originally appeared on DEV Community and was authored by Brian Laposa
Title: Red Star Realism: Revolutionary Generative AI Propaganda with Google Gemini 2.5 Flash Image!!
published: True
tags: devchallenge, googleaichallenge, ai, gemini
What I Built
Red Star Realism utilizes the power of generative AI to inform the masses! This app creatively emulates the visual style, motifs, and color palette of Socialist Realist style. This iconic art style hails from mid-20th-century Soviet Union and its severe and monolithic style is easily recognizable.
Demo
You can try the deployed app here:
[Red Star Realism App] https://red-star-realism-365757207239.us-west1.run.app
Below is a walkthrough video demonstration of the workflow and outputs:
https://www.youtube.com/embed/Dom-wlS_MLU?si=s3i8omjKVfv1vHvu
How I Used Google AI Studio
Red Star Realism leverages Google AI Studio’s Gemini 2.5 Flash and Vision APIs for real-time multimodal inference. The app posts image uploads to a backend that performs image analysis using Gemini’s powerful text and image analysis features. Uploads are processed to generate appropriate slogans based on image context. Everything from language to UI visuals is carefully tailored to exaggerate this aesthetic for entertainment and educational purposes.
Multimodal Features
- Image Analysis and Generation Users upload any image and choose from the appropriate slogans and backgrounds Create your portrait as the generalissimo or a hero of the proletariat!
- Socialist Realist Style: Every graphic, badge, and piece of feedback channels the socialist realist style—dramatic reds and golds, heroic worker motifs, bold block fonts, and stylized propaganda flourishes.
- Dynamic Slogans: Powered by Gemini’s world-class multimodal AI models, so every slogan is inspired by a combination of real pose and expression analysis with a communist twist!
Red Star Realism is both a rich technical showcase and a collective celebration of AI, aesthetics, and creative expression.
This content originally appeared on DEV Community and was authored by Brian Laposa