Edge-Diffusion-v1.4

KO | EN

gitlite — search

#javascript #python #react #ai #llm #golang #machine-learning #deep-learning #docker #java #vue #pytorch #mcp #open-source

Edge-Diffusion-v1.4

(★ 10)

Edge AI image generation on Android, powered by Stable Diffusion v1.4. Generate stunning images locally without internet — no rate limits, no cloud dependency.

Edge-Diffusion-v1.4 Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# 📱  Edge Diffusion v1.4

> *AI Image Generation in Your Pocket – Fully Offline*

Edge Diffusion v1.4 is an Android application that brings the power of Stable Diffusion v1.4 directly to your mobile device - no internet connection required! \
Designed and developed as part of my Bachelor’s Final Year Project, this app enables fully offline AI image generation, giving users complete control, privacy and creativity on the go.

## 📸 Screenshots
![App UI](https://raw.githubusercontent.com/zwnkoko/Edge-Diffusion-v1.4/master/images/1_App_UI.PNG "App UI") \
*Prompt input screen with customizable parameters*

![Generated Image](https://raw.githubusercontent.com/zwnkoko/Edge-Diffusion-v1.4/master/images/demo_pic.PNG "Generated Image") \
 *Example image generated on-device*

## ✨ Key Features

- **Local Image Generation** using the Stable Diffusion pipeline — no cloud dependency.
- **Stable Diffusion v1.4 Pipeline** – fully implemented in Kotlin and optimized for Android.
- **Customizable Parameters** for creative control:
    - Prompt input for text-to-image generation
    - Denoising steps for fine-tuned detail
    - Seed control for reproducibility
    - Advanced settings (see screenshots below)
- **Privacy-First Design**: All computations happen on-device, ensuring privacy, security, and zero reliance on external servers.
- **Offline by Design**: Works without any internet connection — perfect for remote or low-connectivity environments.
- **LLM-Powered Prompt Enrichment (Optional)**: When connected to a local network, the app can leverage a LAN-hosted Language Model to enhance your prompts with richer details (e.g., colors, physical attributes), improving image quality and accuracy.

## 🛠 Tech Stack

| Category              | Technologies                               |
| --------------------- | ------------------------------------------ |
| Mobile App            | Kotlin, Jetpack Compose                    |
| AI & Model Deployment | PyTorch, ONNX, Hugging Face                |
| LAN Server (Optional) | FastAPI, TinyLlama                         |
| Other Tools           | Android Studio, Gradle, Visual Studio Code |

## 🏗 Architecture Diagram

![System Architecture](https://raw.githubusercontent.com/zwnkoko/Edge-Diffusion-v1.4/master/images/System_Architecture.PNG "System Architecture") \
 *System Architecture*

![App Architecture](https://raw.githubusercontent.com/zwnkoko/Edge-Diffusion-v1.4/master/images/Android_App_Architecture.PNG "App Architecture") \
 *App Architecture*

## 🖼 Image Quality vs Denoising Steps

Below are examples showing how image quality improves as the number of denoising steps increases:

> **Tip:** Typically, **20 steps** is a balanced trade-off between quality and speed.

### Example 1: Astronaut Riding a Horse
![Astronaut Riding a Horse](https://raw.githubusercontent.com/zwnkoko/Edge-Diffusion-v1.4/master/images/Denosing_Steps_1.PNG "Astronaut Riding a Horse")

### Example 2: Oil Painting of Nature
![Oil Painting of Nature](https://raw.githubusercontent.com/zwnkoko/Edge-Diffusion-v1.4/master/images/Denosing_Steps_2.PNG "Oil Painting of Nature")

### Example 3: Futuristic City
![Futuristic City](https://raw.githubusercontent.com/zwnkoko/Edge-Diffusion-v1.4/master/images/Denosing_Steps_3.PNG "Futuristic City")

Edge-Diffusion-v1.4

Edge-Diffusion-v1.4 Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Edge-Diffusion-v1.4

Edge-Diffusion-v1.4 Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README