FaceForgeAI – AI-Powered Portrait Generation & Editing

Generate and modify realistic human portraits from natural language descriptions using Stable Diffusion.
Designed for forensics, investigations, and creative industries, FaceForge AI turns witness descriptions into accurate portraits, allows targeted edits, and matches against a face database for possible identity suggestions.

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Table of Contents

• Overview
• Features
• Tech Stack
• Project Workflow
• Screenshots
• Flowchart
• Getting Started
• Usage
• Future Improvements

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Overview

FaceForge AI enables text-driven portrait creation and targeted facial modifications.
The system follows these key steps:

1. Generate a face from a natural language description.
2. Edit specific facial features using inpainting.
3. Match the final portrait with a face database using CLIP embeddings.

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Features

Text-to-Portrait Generation

• Input a natural language prompt (e.g., "young woman with long black hair")
• Generate a realistic portrait using Stable Diffusion

Feature-Specific Inpainting

• Mask specific facial regions
• Apply prompts like "change eyes to blue" or "add scar on cheek"
• Preserve the rest of the face while editing

Facial Embedding & Matching

• Encode the portrait with CLIP embeddings
• Compare against a curated database
• Display top 3 matches with confidence scores

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Tech Stack

• Diffusion Models: StableDiffusionPipeline, StableDiffusionInpaintPipeline
• Embeddings: OpenAI CLIP for similarity search
• Frontend: Gradio interface
• Language: Python 3.8+
• Dataset: Curated Asian celebrity faces (for cultural relevance)
• Execution: Google Colab / Local GPU

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Screenshots

Text-to-Portrait Generation

*Generates a realistic portrait directly from a text description.*

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Feature-Specific Inpainting

*Modify selected facial features without affecting the rest of the image.*

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Face Matching Results

*Matches generated portraits with the closest identities from the database.*

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Flowchart

*The complete process from description to identity suggestion.*

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Getting Started

Prerequisites

• Python 3.8+
• GPU (local or via Colab for best performance)

Installation

git clone https://github.com/Keerthana1226/FaceforgeAI
cd FaceForgeAI

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Usage

Run the Gradio interface:

python app.py

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Future Improvements

• Add multiple ethnicity datasets for wider coverage
• Implement 3D face reconstruction
• Improve inpainting with higher resolution support
• Support voice-based descriptions