diff --git a/README.md b/README.md
index 8274614..71af00e 100644
--- a/README.md
+++ b/README.md
@@ -24,7 +24,6 @@ OpenTryOn is an open-source AI toolkit designed for fashion technology and virtu
- Nano Banana Pro (Gemini 3 Pro Image Preview) for advanced 4K image generation with search grounding
- FLUX.2 [PRO] high-quality image generation with text-to-image, image editing, and multi-image composition
- FLUX.2 [FLEX] flexible image generation with advanced controls (guidance, steps, prompt upsampling)
-
- Photon-Flash-1 (Luma AI): Fast and cost efficient image generation, ideal for rapid iteration and scale
- Photon-1 (Luma AI): High-fidelity default model for professional-grade quality, creativity and detailed prompt handling
- **Video Generation**:
@@ -151,6 +150,7 @@ LUMA_AI_API_KEY=your_luma_ai_api_key
- For Segmind, obtain your API key from the [Segmind API Portal](https://www.segmind.com/models/try-on-diffusion/api)
- For Nano Banana, obtain your API key from the [Google AI Studio](https://aistudio.google.com/app/apikey)
+- For FLUX.2 models, obtain your API key from [BFL AI](https://docs.bfl.ai/)
- For FLUX.2 models, obtain your API key from [BFL AI](https://docs.bfl.ai/)
- For Luma AI, obtain your API key from the [Luma Labs AI](https://lumalabs.ai/api)
@@ -1188,7 +1188,36 @@ segment_human(
## π¨ Demos
-The project includes several interactive Gradio demos for easy experimentation:
+The project includes several interactive demos for easy experimentation:
+
+### Virtual Try-On Demo (Web App) β NEW
+
+A modern, full-stack virtual try-on web application with FastAPI backend and Next.js frontend.
+
+**Features**:
+- Support for 4 AI models: Nano Banana, Nano Banana Pro, FLUX 2 Pro, FLUX 2 Flex
+- Multi-image upload with drag & drop
+- Real-time credit estimation
+- Modern, responsive UI
+- Production-ready API server
+
+**Quick Start**:
+
+1. Start the backend:
+```bash
+python api_server.py
+```
+
+2. In a new terminal, start the frontend:
+```bash
+cd demo/virtual-tryon
+npm install
+npm run dev
+```
+
+3. Open `http://localhost:3000` in your browser
+
+**Documentation**: See [`demo/virtual-tryon/README.md`](demo/virtual-tryon/README.md) and [`README_API_SERVER.md`](README_API_SERVER.md) for detailed instructions.
### Extract Garment Demo
@@ -1208,7 +1237,7 @@ python run_demo.py --name model_swap
python run_demo.py --name outfit_generator
```
-Each demo launches a web interface where you can interact with the models through a user-friendly UI.
+Gradio demos launch a web interface where you can interact with the models through a user-friendly UI.
## π Project Structure
@@ -1244,16 +1273,20 @@ opentryon/
β βββ pre_processing/ # Preprocessing for training
β βββ utils/ # Utility functions
βββ demo/ # Interactive demos
-β βββ extract_garment/ # Garment extraction demo
-β βββ model_swap/ # Model swap demo
-β βββ outfit_generator/ # Outfit generator demo
+β βββ virtual-tryon/ # Full-stack virtual try-on web app (Next.js + FastAPI)
+β βββ extract_garment/ # Garment extraction demo (Gradio)
+β βββ model_swap/ # Model swap demo (Gradio)
+β βββ outfit_generator/ # Outfit generator demo (Gradio)
βββ scripts/ # Installation scripts
+βββ api_server.py # FastAPI server for virtual try-on demo
βββ main.py # Main CLI entry point
+βββ run_demo.py # Demo launcher (Gradio demos)
βββ vton.py # Virtual try-on CLI (Amazon Nova Canvas, Kling AI, Segmind)
βββ image_gen.py # Image generation CLI (Nano Banana, FLUX.2)
-βββ run_demo.py # Demo launcher
βββ requirements.txt # Python dependencies
-βββ environment.yml # Conda environment
+βββ environment.yml # Conda environment
+βββ README_API_SERVER.md # API server documentation
+βββ setup.py # Package installation
```
## πΊοΈ TryOnDiffusion: Roadmap
@@ -1316,7 +1349,10 @@ Key dependencies include:
- PyJWT (>= 2.10.1)
- boto3 (== 1.40.64)
- python-dotenv (== 1.0.1)
-- google-genai (== 1.52.0)
+- google-genai (>= 1.52.0)
+- fastapi (== 0.124.0)
+- uvicorn[standard] (== 0.38.0)
+- python-multipart (== 0.0.20)
- lumaai (== 1.18.1)
See `requirements.txt` or `environment.yml` for the complete list of dependencies.
diff --git a/api_server.py b/api_server.py
new file mode 100644
index 0000000..8d84aef
--- /dev/null
+++ b/api_server.py
@@ -0,0 +1,471 @@
+"""
+FastAPI server for Virtual Try-On using multiple model providers.
+
+This server provides a simple REST API endpoint for virtual try-on generation
+using various image generation models:
+- Nano Banana and Nano Banana Pro (Google Gemini)
+- FLUX 2 Pro and FLUX 2 Flex (Black Forest Labs)
+"""
+
+import os
+import io
+import base64
+from datetime import datetime
+from pathlib import Path
+from typing import List, Optional, Tuple
+from fastapi import FastAPI, File, UploadFile, HTTPException, Form
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+from PIL import Image
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+# Import adapters
+from tryon.api.nano_banana import NanoBananaAdapter, NanoBananaProAdapter
+from tryon.api.flux2 import Flux2ProAdapter, Flux2FlexAdapter
+
+# Create output directory for generated images
+OUTPUT_DIR = Path("outputs/virtual_tryon")
+OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+# Supported aspect ratios for both adapters
+SUPPORTED_ASPECT_RATIOS = [
+ "1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"
+]
+
+
+def calculate_aspect_ratio(image: Image.Image) -> str:
+ """
+ Calculate the aspect ratio from an image and return the closest supported ratio.
+
+ Args:
+ image: PIL Image object
+
+ Returns:
+ str: Aspect ratio string in format "W:H" (e.g., "16:9")
+ """
+ width, height = image.size
+ ratio = width / height
+
+ # Map of supported ratios to their decimal values
+ ratio_map = {
+ "1:1": 1.0,
+ "2:3": 2/3,
+ "3:2": 3/2,
+ "3:4": 3/4,
+ "4:3": 4/3,
+ "4:5": 4/5,
+ "5:4": 5/4,
+ "9:16": 9/16,
+ "16:9": 16/9,
+ "21:9": 21/9,
+ }
+
+ # Find the closest matching aspect ratio
+ closest_ratio = "1:1" # Default
+ min_diff = float('inf')
+
+ for ratio_str, ratio_value in ratio_map.items():
+ diff = abs(ratio - ratio_value)
+ if diff < min_diff:
+ min_diff = diff
+ closest_ratio = ratio_str
+
+ return closest_ratio
+
+
+def get_image_dimensions(image: Image.Image) -> Tuple[int, int]:
+ """
+ Get image dimensions (width, height).
+
+ Args:
+ image: PIL Image object
+
+ Returns:
+ tuple: (width, height)
+ """
+ return image.size
+
+
+def calculate_resolution(image: Image.Image) -> str:
+ """
+ Calculate resolution from image dimensions in "widthxheight" format.
+
+ Args:
+ image: PIL Image object
+
+ Returns:
+ str: Resolution string in format "widthxheight" (e.g., "1024x1024")
+ """
+ width, height = image.size
+ return f"{width}x{height}"
+
+
+def map_resolution_to_pro_format(image: Image.Image) -> str:
+ """
+ Map image resolution to Nano Banana Pro format ("1K", "2K", or "4K").
+
+ The mapping is based on the maximum dimension:
+ - max_dimension <= 1500: "1K"
+ - max_dimension <= 3000: "2K"
+ - max_dimension > 3000: "4K"
+
+ Args:
+ image: PIL Image object
+
+ Returns:
+ str: Resolution in format "1K", "2K", or "4K"
+ """
+ width, height = image.size
+ max_dimension = max(width, height)
+
+ if max_dimension <= 1500:
+ return "1K"
+ elif max_dimension <= 3000:
+ return "2K"
+ else:
+ return "4K"
+
+app = FastAPI(
+ title="TryOn AI Virtual Try-On API",
+ description="Virtual try-on API using multiple model providers (Nano Banana, FLUX 2 Pro, FLUX 2 Flex)",
+ version="1.0.0"
+)
+
+# CORS middleware to allow requests from Next.js frontend
+app.add_middleware(
+ CORSMiddleware,
+ allow_origins=["http://localhost:3000", "http://127.0.0.1:3000"], # Next.js dev server
+ allow_credentials=True,
+ allow_methods=["*"],
+ allow_headers=["*"],
+)
+
+
+@app.get("/")
+async def root():
+ """Root endpoint."""
+ return {
+ "message": "TryOn AI Virtual Try-On API",
+ "version": "1.0.0",
+ "endpoints": {
+ "POST /api/v1/virtual-tryon": "Generate virtual try-on image"
+ },
+ "providers": [
+ "nano-banana",
+ "nano-banana-pro",
+ "flux-2-pro",
+ "flux-2-flex"
+ ]
+ }
+
+
+@app.get("/health")
+async def health():
+ """Health check endpoint."""
+ return {"status": "healthy"}
+
+
+@app.post("/api/v1/virtual-tryon")
+async def virtual_tryon(
+ model_image: UploadFile = File(..., description="Model/person image"),
+ garment_images: List[UploadFile] = File(..., description="Garment images"),
+ provider: str = Form(default="nano-banana", description="Provider: 'nano-banana', 'nano-banana-pro', 'flux-2-pro', or 'flux-2-flex'"),
+ prompt: Optional[str] = Form(default=None, description="Optional custom prompt"),
+ resolution: Optional[str] = Form(default="1K", description="Resolution for nano-banana-pro: '1K', '2K', or '4K'"),
+ aspect_ratio: Optional[str] = Form(default=None, description="Optional aspect ratio (e.g., '16:9')"),
+ width: Optional[int] = Form(default=None, description="Output image width (for FLUX 2 models)"),
+ height: Optional[int] = Form(default=None, description="Output image height (for FLUX 2 models)"),
+ seed: Optional[int] = Form(default=None, description="Random seed for reproducibility (for FLUX 2 models)"),
+ guidance: Optional[float] = Form(default=None, description="Guidance scale 1.5-10 (for FLUX 2 Flex, default: 3.5)"),
+ steps: Optional[int] = Form(default=None, description="Number of generation steps (for FLUX 2 Flex, default: 28)"),
+ safety_tolerance: Optional[int] = Form(default=2, description="Safety tolerance 0-5 (for FLUX 2 models, default: 2)")
+):
+ """
+ Generate virtual try-on image from model image and garment images.
+
+ Uses multi-image composition feature of various models to combine
+ the model image with multiple garment images.
+
+ Supported providers:
+ - nano-banana: Google Gemini Nano Banana (basic)
+ - nano-banana-pro: Google Gemini Nano Banana Pro (supports resolution)
+ - flux-2-pro: Black Forest Labs FLUX 2 Pro (high quality)
+ - flux-2-flex: Black Forest Labs FLUX 2 Flex (advanced controls)
+
+ Args:
+ model_image: Single model/person image
+ garment_images: List of garment images (top, jeans, scarf, hat, etc.)
+ provider: Model provider ('nano-banana', 'nano-banana-pro', 'flux-2-pro', or 'flux-2-flex')
+ prompt: Optional custom prompt for generation
+ resolution: Resolution for nano-banana-pro ('1K', '2K', or '4K')
+ aspect_ratio: Optional aspect ratio (for Nano Banana models)
+ width: Output image width in pixels (for FLUX 2 models, minimum: 64)
+ height: Output image height in pixels (for FLUX 2 models, minimum: 64)
+ seed: Random seed for reproducibility (for FLUX 2 models)
+ guidance: Guidance scale 1.5-10 (for FLUX 2 Flex only, default: 3.5)
+ steps: Number of generation steps (for FLUX 2 Flex only, default: 28)
+ safety_tolerance: Safety tolerance 0-5 (for FLUX 2 models, default: 2)
+
+ Returns:
+ JSON response with base64-encoded result image
+ """
+ try:
+ # Validate provider
+ valid_providers = ["nano-banana", "nano-banana-pro", "flux-2-pro", "flux-2-flex"]
+ if provider not in valid_providers:
+ raise HTTPException(
+ status_code=400,
+ detail=f"Invalid provider '{provider}'. Must be one of: {', '.join(valid_providers)}"
+ )
+
+ # Validate inputs
+ if not model_image:
+ raise HTTPException(status_code=400, detail="Model image is required")
+
+ if not garment_images or len(garment_images) == 0:
+ raise HTTPException(status_code=400, detail="At least one garment image is required")
+
+ # Read model image
+ model_image_bytes = await model_image.read()
+ model_pil = Image.open(io.BytesIO(model_image_bytes))
+
+ # Calculate aspect ratio and resolution from model image
+ calculated_aspect_ratio = calculate_aspect_ratio(model_pil)
+ calculated_resolution = calculate_resolution(model_pil)
+ model_width, model_height = get_image_dimensions(model_pil)
+
+ # Use calculated aspect ratio if not provided, otherwise use the provided one
+ final_aspect_ratio = aspect_ratio if aspect_ratio else calculated_aspect_ratio
+
+ # Map resolution to appropriate format based on provider
+ # For nano-banana-pro, use "1K", "2K", or "4K" format
+ # For nano-banana, resolution is not used (only aspect ratio)
+ # For FLUX 2 models, use width/height parameters instead
+ if provider == "nano-banana-pro":
+ # Use provided resolution if valid, otherwise map from image dimensions
+ if resolution and resolution in ["1K", "2K", "4K"]:
+ final_resolution = resolution
+ else:
+ final_resolution = map_resolution_to_pro_format(model_pil)
+ elif provider in ["flux-2-pro", "flux-2-flex"]:
+ # For FLUX 2, use model dimensions as default width/height if not provided
+ if width is None:
+ width = model_width
+ if height is None:
+ height = model_height
+ final_resolution = f"{width}x{height}"
+ else:
+ # For nano-banana, resolution is not used, but keep calculated for reference
+ final_resolution = calculated_resolution
+
+ # Read garment images and combine with model image
+ # First image should be model, followed by garments
+ images_list = [model_pil]
+ for garment_file in garment_images:
+ garment_bytes = await garment_file.read()
+ garment_pil = Image.open(io.BytesIO(garment_bytes))
+ images_list.append(garment_pil)
+
+ # Prepare prompt
+ if not prompt:
+ prompt = (
+ "Create a realistic virtual try-on image showing the person wearing the provided garments. "
+ "CRITICAL REQUIREMENTS - Preserve all details exactly:\n"
+ "1. GARMENT EXTRACTION: The garment images may contain people wearing the garments. "
+ "IGNORE and EXTRACT ONLY the garment itself - do not use any person, model, or human figure "
+ "from the garment images. Focus solely on the garment: its shape, design, patterns, colors, "
+ "textures, and all visual details. Remove or ignore any human elements from garment images.\n"
+ "2. GARMENT PRESERVATION: Keep ALL garment details completely intact - patterns, colors, textures, "
+ "designs, prints, logos, text, embroidery, sequins, and any decorative elements must remain "
+ "identical to the original garment images. Do not alter, fade, or modify any garment features.\n"
+ "3. PERSON PRESERVATION: Keep the person's face, body shape, skin tone, hair, and physical "
+ "characteristics exactly as shown in the FIRST image (model image). Only apply the extracted "
+ "garments from the subsequent images to this person. Do not use any person from garment images.\n"
+ "4. PARTIAL GARMENT HANDLING: If the person in the model image is wearing a full-body outfit "
+ "(dress, jumpsuit, etc.) but the provided garment is only upper-body (top, shirt, blouse) or "
+ "lower-body (pants, jeans, skirt), place the provided garment correctly over the corresponding "
+ "body part. For the remaining uncovered body parts, generate an appropriate complementary garment "
+ "that matches: (a) the person's physical characteristics and body type, (b) the person's style "
+ "and personality traits visible in the model image, (c) the style, color scheme, and design "
+ "aesthetic of the provided garment. The complementary garment should create a cohesive, "
+ "harmonious outfit that looks natural and well-coordinated.\n"
+ "5. FITTING: The extracted garments should fit naturally on the person's body from the first image, "
+ "following their body contours and proportions realistically, while maintaining all original "
+ "garment details from the garment images.\n"
+ "6. COMPOSITION: The first image is the model/person to dress. The following images contain "
+ "garments (top, bottom, accessories, etc.) - extract ONLY the garments from these images, "
+ "ignoring any people shown. Combine the extracted garments to create a cohesive outfit where "
+ "each garment maintains its original appearance and fits the person naturally.\n"
+ "7. REALISM: The final image should look like a professional photograph of the person from the "
+ "first image wearing the exact extracted garments (and complementary garments if needed), with "
+ "realistic lighting, shadows, and fabric draping."
+ )
+
+ # Initialize adapter and generate
+ if provider == "nano-banana":
+ adapter = NanoBananaAdapter()
+ # Generate with basic adapter using calculated aspect ratio
+ result_images = adapter.generate_multi_image(
+ images=images_list,
+ prompt=prompt,
+ aspect_ratio=final_aspect_ratio
+ )
+ elif provider == "nano-banana-pro":
+ adapter = NanoBananaProAdapter()
+ # Generate with Pro adapter (supports resolution) using calculated resolution and aspect ratio
+ result_images = adapter.generate_multi_image(
+ images=images_list,
+ prompt=prompt,
+ resolution=final_resolution,
+ aspect_ratio=final_aspect_ratio
+ )
+ elif provider == "flux-2-pro":
+ adapter = Flux2ProAdapter()
+ # Generate with FLUX 2 Pro adapter
+ # Build kwargs for FLUX 2 Pro
+ flux_kwargs = {
+ "safety_tolerance": safety_tolerance if safety_tolerance is not None else 2,
+ "output_format": "png"
+ }
+ if width is not None:
+ flux_kwargs["width"] = width
+ if height is not None:
+ flux_kwargs["height"] = height
+ if seed is not None:
+ flux_kwargs["seed"] = seed
+
+ result_images = adapter.generate_multi_image(
+ prompt=prompt,
+ images=images_list,
+ **flux_kwargs
+ )
+ else: # flux-2-flex
+ adapter = Flux2FlexAdapter()
+ # Generate with FLUX 2 Flex adapter (supports guidance and steps)
+ # Build kwargs for FLUX 2 Flex
+ flux_kwargs = {
+ "safety_tolerance": safety_tolerance if safety_tolerance is not None else 2,
+ "output_format": "png",
+ "guidance": guidance if guidance is not None else 5,
+ "steps": steps if steps is not None else 50,
+ "prompt_upsampling": True
+ }
+ if width is not None:
+ flux_kwargs["width"] = width
+ if height is not None:
+ flux_kwargs["height"] = height
+ if seed is not None:
+ flux_kwargs["seed"] = seed
+
+ result_images = adapter.generate_multi_image(
+ prompt=prompt,
+ images=images_list,
+ **flux_kwargs
+ )
+
+ if not result_images:
+ raise HTTPException(status_code=500, detail="No images generated")
+
+ # Get first result image and convert to PIL Image
+ result_image = result_images[0]
+
+ # Convert image to PIL Image if needed
+ # FLUX 2 adapters return PIL Images directly
+ # Nano Banana adapters return Google GenAI image types that need conversion
+ if not isinstance(result_image, Image.Image):
+ # Google GenAI image type has image_bytes attribute
+ if hasattr(result_image, 'image_bytes'):
+ # Convert bytes to PIL Image
+ result_image = Image.open(io.BytesIO(result_image.image_bytes))
+ elif hasattr(result_image, 'to_pil'):
+ # If it has a to_pil method, use it
+ result_image = result_image.to_pil()
+ else:
+ # Try to get bytes from the image object
+ try:
+ # Some GenAI image types expose bytes directly
+ image_bytes = bytes(result_image)
+ result_image = Image.open(io.BytesIO(image_bytes))
+ except (TypeError, AttributeError):
+ raise HTTPException(
+ status_code=500,
+ detail=f"Unable to convert image type {type(result_image)} to PIL Image. "
+ f"Image attributes: {dir(result_image)}"
+ )
+
+ # Generate filename with timestamp
+ timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f")
+ filename = f"tryon_{provider}_{timestamp}.png"
+ filepath = OUTPUT_DIR / filename
+
+ # Save image to disk
+ try:
+ # Ensure image is in RGB mode for saving
+ if result_image.mode != 'RGB':
+ result_image = result_image.convert('RGB')
+
+ # Save to file
+ result_image.save(str(filepath), 'PNG')
+
+ # Also save to BytesIO for base64 encoding
+ img_buffer = io.BytesIO()
+ result_image.save(img_buffer, 'PNG')
+ img_buffer.seek(0)
+ img_base64 = base64.b64encode(img_buffer.read()).decode('utf-8')
+
+ except Exception as e:
+ raise HTTPException(
+ status_code=500,
+ detail=f"Error saving image: {str(e)}"
+ )
+
+ # Build response with provider-specific metadata
+ response_data = {
+ "success": True,
+ "image": f"data:image/png;base64,{img_base64}",
+ "provider": provider,
+ "num_garments": len(garment_images),
+ "saved_path": str(filepath),
+ "filename": filename,
+ "model_dimensions": {"width": model_width, "height": model_height},
+ }
+
+ # Add provider-specific metadata
+ if provider in ["nano-banana", "nano-banana-pro"]:
+ response_data.update({
+ "aspect_ratio": final_aspect_ratio,
+ "calculated_aspect_ratio": calculated_aspect_ratio,
+ "resolution": final_resolution,
+ "calculated_resolution": calculated_resolution
+ })
+ elif provider in ["flux-2-pro", "flux-2-flex"]:
+ response_data.update({
+ "output_dimensions": {"width": width or model_width, "height": height or model_height},
+ "safety_tolerance": safety_tolerance if safety_tolerance is not None else 2,
+ })
+ if seed is not None:
+ response_data["seed"] = seed
+ if provider == "flux-2-flex":
+ response_data.update({
+ "guidance": guidance if guidance is not None else 3.5,
+ "steps": steps if steps is not None else 28,
+ })
+
+ return JSONResponse(response_data)
+
+ except ValueError as e:
+ raise HTTPException(status_code=400, detail=str(e))
+ except Exception as e:
+ import traceback
+ error_details = f"Error generating try-on: {str(e)}\n{traceback.format_exc()}"
+ print(error_details) # Log to console
+ raise HTTPException(status_code=500, detail=f"Error generating try-on: {str(e)}")
+
+
+if __name__ == "__main__":
+ import uvicorn
+ uvicorn.run(app, host="0.0.0.0", port=8000)
+
diff --git a/demo/virtual-tryon/.eslintrc.json b/demo/virtual-tryon/.eslintrc.json
new file mode 100644
index 0000000..f18272b
--- /dev/null
+++ b/demo/virtual-tryon/.eslintrc.json
@@ -0,0 +1,4 @@
+{
+ "extends": "next/core-web-vitals"
+}
+
diff --git a/demo/virtual-tryon/.gitignore b/demo/virtual-tryon/.gitignore
new file mode 100644
index 0000000..1403e90
--- /dev/null
+++ b/demo/virtual-tryon/.gitignore
@@ -0,0 +1,36 @@
+# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
+
+# dependencies
+/node_modules
+/.pnp
+.pnp.js
+
+# testing
+/coverage
+
+# next.js
+/.next/
+/out/
+
+# production
+/build
+
+# misc
+.DS_Store
+*.pem
+
+# debug
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+
+# local env files
+.env*.local
+
+# vercel
+.vercel
+
+# typescript
+*.tsbuildinfo
+next-env.d.ts
+
diff --git a/demo/virtual-tryon/README.md b/demo/virtual-tryon/README.md
new file mode 100644
index 0000000..7df0d6d
--- /dev/null
+++ b/demo/virtual-tryon/README.md
@@ -0,0 +1,322 @@
+# Virtual Try-On Demo
+
+A modern, full-stack virtual try-on application featuring a Next.js frontend and FastAPI backend. Generate realistic virtual try-on images using state-of-the-art AI models including Nano Banana, Nano Banana Pro, FLUX 2 Pro, and FLUX 2 Flex.
+
+## π― Features
+
+- **πΌοΈ Modern UI**: Beautiful, responsive Next.js interface with drag & drop support
+- **π€ Multiple AI Models**: Choose from 4 powerful image generation models
+ - **Nano Banana**: Fast, efficient (Gemini 2.5 Flash) - 1024px
+ - **Nano Banana Pro**: Advanced (Gemini 3 Pro) - up to 4K with search grounding
+ - **FLUX 2 Pro**: High-quality professional results
+ - **FLUX 2 Flex**: Flexible with advanced controls (guidance, steps, prompt upsampling)
+- **π€ Multi-Image Upload**: Upload model image + multiple garment images
+- **π° Cost Estimation**: Real-time credit calculation based on resolution and image count
+- **π Live Processing**: View generation progress and results
+- **π± Responsive Design**: Works seamlessly on desktop, tablet, and mobile devices
+
+## ποΈ Architecture
+
+The demo consists of two components:
+
+1. **Frontend (Next.js 15)**
+ - Located in `demo/virtual-tryon/`
+ - Modern React/TypeScript application
+ - Tailwind CSS for styling
+ - Real-time API communication
+
+2. **Backend (FastAPI)**
+ - Located in project root: `api_server.py`
+ - Uses OpenTryOn API SDK (`tryon.api`)
+ - Supports 4 model providers
+ - Automatic image processing and storage
+
+## π Quick Start
+
+### Prerequisites
+
+- **Backend Requirements**:
+ - Python 3.10+
+ - FastAPI 0.124.0
+ - Uvicorn 0.38.0
+ - OpenTryOn installed (`pip install -e .`)
+
+- **Frontend Requirements**:
+ - Node.js 18+
+ - npm or yarn
+
+- **API Keys** (at least one required):
+ - `GEMINI_API_KEY` for Nano Banana models
+ - `BFL_API_KEY` for FLUX 2 models
+
+### Step 1: Set Up Environment
+
+Create a `.env` file in the project root:
+
+```bash
+# Google Gemini (for Nano Banana models)
+GEMINI_API_KEY=your_gemini_api_key
+
+# Black Forest Labs (for FLUX 2 models)
+BFL_API_KEY=your_bfl_api_key
+```
+
+### Step 2: Start the Backend
+
+From the project root:
+
+```bash
+# Activate your environment
+conda activate opentryon # or source venv/bin/activate
+
+# Start the FastAPI server
+python api_server.py
+```
+
+The API server will start at `http://localhost:8000`
+
+**API Health Check**:
+```bash
+curl http://localhost:8000/health
+```
+
+### Step 3: Start the Frontend
+
+In a new terminal:
+
+```bash
+cd demo/virtual-tryon
+npm install
+npm run dev
+```
+
+The frontend will start at `http://localhost:3000`
+
+### Step 4: Try It Out!
+
+1. Open `http://localhost:3000` in your browser
+2. Select a model (Nano Banana, Nano Banana Pro, FLUX 2 Pro, or FLUX 2 Flex)
+3. Upload a model/person image
+4. Upload garment images (shirts, pants, accessories, etc.)
+5. Click "Generate" and wait for the AI-generated result!
+
+## π Project Structure
+
+```
+demo/virtual-tryon/
+βββ app/
+β βββ layout.tsx # Root layout with metadata
+β βββ page.tsx # Main UI component with generation logic
+β βββ globals.css # Global styles and Tailwind config
+βββ components/
+β βββ ui/ # Reusable UI components
+β β βββ button.tsx
+β β βββ card.tsx
+β βββ image-upload.tsx # Single image upload
+β βββ multi-image-upload.tsx # Multiple image upload
+βββ lib/
+β βββ utils.ts # Utility functions
+βββ pricing_config.json # Credit pricing configuration
+βββ README.md # This file
+
+../../api_server.py # FastAPI backend server
+```
+
+## π¨ Tech Stack
+
+### Frontend
+- **Next.js 15** - React framework with App Router
+- **TypeScript** - Type-safe development
+- **Tailwind CSS 3.4** - Utility-first CSS
+- **React Dropzone** - Drag & drop uploads
+- **React Icons** - Icon library
+
+### Backend
+- **FastAPI 0.124.0** - Modern Python web framework
+- **Uvicorn 0.38.0** - ASGI server
+- **OpenTryOn SDK** - AI model adapters
+ - `NanoBananaAdapter`
+ - `NanoBananaProAdapter`
+ - `Flux2ProAdapter`
+ - `Flux2FlexAdapter`
+
+## π§ API Server Details
+
+The backend (`api_server.py`) provides a REST API for virtual try-on generation.
+
+### Endpoints
+
+#### `POST /api/v1/virtual-tryon`
+
+Generate virtual try-on images.
+
+**Parameters**:
+- `model_image` (file, required): Model/person image
+- `garment_images` (files, required): One or more garment images
+- `provider` (string, optional): Model to use
+ - `nano-banana` (default) - Fast, 1024px
+ - `nano-banana-pro` - Advanced, up to 4K
+ - `flux-2-pro` - High quality
+ - `flux-2-flex` - Advanced controls
+- `prompt` (string, optional): Custom generation prompt
+- `resolution` (string, optional): For nano-banana-pro: `1K`, `2K`, or `4K`
+- `aspect_ratio` (string, optional): e.g., `16:9`, `1:1`
+- Additional FLUX 2 parameters: `width`, `height`, `seed`, `guidance`, `steps`, `safety_tolerance`
+
+**Response**:
+```json
+{
+ "success": true,
+ "image": "data:image/png;base64,...",
+ "provider": "nano-banana",
+ "num_garments": 2,
+ "saved_path": "outputs/virtual_tryon/tryon_nano-banana_20250119_143022.png",
+ "filename": "tryon_nano-banana_20250119_143022.png",
+ "model_dimensions": {"width": 838, "height": 1176}
+}
+```
+
+#### `GET /health`
+
+Health check endpoint.
+
+**Response**:
+```json
+{
+ "status": "healthy"
+}
+```
+
+### CORS Configuration
+
+The API server allows requests from:
+- `http://localhost:3000` (Next.js dev server)
+- `http://127.0.0.1:3000`
+
+## π³ Pricing Configuration
+
+Credits are calculated dynamically based on:
+- **Model provider** (different pricing strategies)
+- **Image resolution** (higher resolution = more credits)
+- **Number of images** (model image + garment images)
+
+Edit `pricing_config.json` to customize pricing for each model.
+
+## π Usage Example
+
+### Using curl:
+
+```bash
+curl -X POST "http://localhost:8000/api/v1/virtual-tryon" \
+ -F "model_image=@person.jpg" \
+ -F "garment_images=@shirt.jpg" \
+ -F "garment_images=@jeans.jpg" \
+ -F "provider=nano-banana-pro" \
+ -F "resolution=2K"
+```
+
+### Using Python:
+
+```python
+import requests
+
+url = "http://localhost:8000/api/v1/virtual-tryon"
+
+files = {
+ 'model_image': open('person.jpg', 'rb'),
+ 'garment_images': [
+ open('shirt.jpg', 'rb'),
+ open('jeans.jpg', 'rb')
+ ]
+}
+
+data = {
+ 'provider': 'flux-2-pro'
+}
+
+response = requests.post(url, files=files, data=data)
+result = response.json()
+
+if result['success']:
+ print(f"Image saved to: {result['saved_path']}")
+```
+
+## π― Model Comparison
+
+| Model | Speed | Quality | Max Resolution | Special Features |
+|-------|-------|---------|----------------|------------------|
+| **Nano Banana** | β‘β‘β‘ Fast | βββ Good | 1024px | Efficient, low cost |
+| **Nano Banana Pro** | β‘β‘ Medium | ββββ Great | 4K | Search grounding, high resolution |
+| **FLUX 2 Pro** | β‘ Slow | βββββ Excellent | Custom | Professional quality |
+| **FLUX 2 Flex** | β‘ Slow | βββββ Excellent | Custom | Advanced controls, fine-tuning |
+
+## π Troubleshooting
+
+### "Failed to fetch" Error
+
+**Cause**: Frontend cannot connect to backend
+
+**Solutions**:
+1. Ensure API server is running: `python api_server.py`
+2. Check if port 8000 is available: `lsof -i :8000`
+3. Verify API URL in frontend (should be `http://localhost:8000`)
+4. Check browser console (F12) for detailed errors
+
+### API Key Errors
+
+**Error**: `No API key provided` or `Invalid API key`
+
+**Solution**:
+1. Add API keys to `.env` file in project root
+2. Restart the API server to load new environment variables
+
+### Import Errors
+
+**Error**: `ModuleNotFoundError: No module named 'tryon'`
+
+**Solution**: Install OpenTryOn in development mode:
+```bash
+pip install -e .
+```
+
+## π Learn More
+
+- **[OpenTryOn Documentation](https://tryonlabs.github.io/opentryon/)** - Full documentation
+- **[API Reference](../../README_API_SERVER.md)** - Detailed API server documentation
+- **[Main README](../../README.md)** - OpenTryOn overview and installation
+
+## π Production Deployment
+
+### Backend (API Server)
+
+Deploy using uvicorn or gunicorn:
+
+```bash
+# Using uvicorn
+uvicorn api_server:app --host 0.0.0.0 --port 8000 --workers 4
+
+# Using gunicorn with uvicorn workers
+gunicorn api_server:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:8000
+```
+
+### Frontend (Next.js)
+
+Build and deploy:
+
+```bash
+npm run build
+npm start
+```
+
+Or deploy to Vercel:
+
+```bash
+vercel deploy
+```
+
+Don't forget to set `NEXT_PUBLIC_API_URL` environment variable to your production API URL.
+
+## π License
+
+This project is part of the OpenTryOn repository and follows the same license (CC BY-NC 4.0).
+
diff --git a/demo/virtual-tryon/app/globals.css b/demo/virtual-tryon/app/globals.css
new file mode 100644
index 0000000..8d6a8a9
--- /dev/null
+++ b/demo/virtual-tryon/app/globals.css
@@ -0,0 +1,75 @@
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+:root {
+ --primary: #ef4444;
+ --primary-dark: #dc2626;
+ --neutral-dark: #171717;
+ --neutral-light: #fafafa;
+ --shadow-sm: 0 1px 2px 0 rgb(0 0 0 / 0.05);
+ --shadow-md: 0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1);
+ --shadow-lg: 0 10px 15px -3px rgb(0 0 0 / 0.1), 0 4px 6px -4px rgb(0 0 0 / 0.1);
+ --shadow-xl: 0 20px 25px -5px rgb(0 0 0 / 0.1), 0 8px 10px -6px rgb(0 0 0 / 0.1);
+}
+
+* {
+ @apply border-neutral-200;
+}
+
+body {
+ font-family: 'Inter', ui-sans-serif, system-ui, sans-serif;
+ @apply bg-neutral-50 text-neutral-900 antialiased;
+ background-color: #fafafa;
+}
+
+@layer components {
+ .btn-primary {
+ @apply bg-primary-500 text-white px-6 py-3 rounded-lg font-medium hover:bg-primary-600 transition-all duration-200;
+ box-shadow: 0 1px 2px 0 rgb(0 0 0 / 0.05), 0 1px 3px 0 rgb(0 0 0 / 0.1);
+ }
+
+ .btn-primary:hover {
+ box-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1);
+ }
+
+ .input-field {
+ @apply w-full px-4 py-3 border border-neutral-300 rounded-lg focus:outline-none focus:ring-2 focus:ring-primary-500 focus:border-transparent transition-all;
+ background-color: #ffffff;
+ box-shadow: 0 1px 2px 0 rgb(0 0 0 / 0.05);
+ }
+
+ .card {
+ @apply bg-white rounded-lg border border-neutral-200 p-6;
+ background-color: #ffffff;
+ box-shadow: 0 1px 3px 0 rgb(0 0 0 / 0.1), 0 1px 2px -1px rgb(0 0 0 / 0.1);
+ }
+
+ .sidebar-link {
+ @apply flex items-center gap-3 px-4 py-3 rounded-lg text-neutral-600 transition-colors duration-200;
+ background-color: transparent;
+ }
+
+ .sidebar-link:hover {
+ @apply bg-neutral-50;
+ }
+
+ .sidebar-link-active {
+ @apply bg-primary-50 text-primary-600 font-medium;
+ background-color: #fef2f2;
+ }
+
+ .sidebar-shadow {
+ box-shadow: 1px 0 3px 0 rgb(0 0 0 / 0.05);
+ }
+
+ .header-shadow {
+ box-shadow: 0 1px 3px 0 rgb(0 0 0 / 0.1), 0 1px 2px -1px rgb(0 0 0 / 0.1);
+ }
+
+ .image-placeholder {
+ background: linear-gradient(135deg, #f5f5f5 0%, #fafafa 100%);
+ box-shadow: inset 0 2px 4px 0 rgb(0 0 0 / 0.05);
+ }
+}
+
diff --git a/demo/virtual-tryon/app/layout.tsx b/demo/virtual-tryon/app/layout.tsx
new file mode 100644
index 0000000..5f95a9a
--- /dev/null
+++ b/demo/virtual-tryon/app/layout.tsx
@@ -0,0 +1,27 @@
+import type { Metadata } from 'next'
+import { Inter } from 'next/font/google'
+import './globals.css'
+
+const inter = Inter({
+ subsets: ['latin'],
+ display: 'swap',
+ variable: '--font-inter',
+})
+
+export const metadata: Metadata = {
+ title: 'TryOn AI: Virtual Try-On Demo',
+ description: 'Virtual try-on application for fashion garments',
+}
+
+export default function RootLayout({
+ children,
+}: {
+ children: React.ReactNode
+}) {
+ return (
+
+
{children}
+
+ )
+}
+
diff --git a/demo/virtual-tryon/app/page.tsx b/demo/virtual-tryon/app/page.tsx
new file mode 100644
index 0000000..82b69a7
--- /dev/null
+++ b/demo/virtual-tryon/app/page.tsx
@@ -0,0 +1,582 @@
+'use client'
+
+import { useState, useMemo, useEffect } from 'react'
+import { Card, CardHeader, CardTitle, CardContent } from '@/components/ui/card'
+import { Button } from '@/components/ui/button'
+import { ImageUpload } from '@/components/image-upload'
+import { MultiImageUpload } from '@/components/multi-image-upload'
+import { HiSparkles, HiUser, HiXMark, HiMagnifyingGlass, HiPhoto } from 'react-icons/hi2'
+import Link from 'next/link'
+import pricingConfig from '../pricing_config.json'
+
+const API_URL = process.env.NEXT_PUBLIC_API_URL || 'http://localhost:8000'
+
+type Provider = 'nano-banana' | 'nano-banana-pro' | 'flux-2-pro' | 'flux-2-flex'
+
+interface PricingConfig {
+ models: {
+ [key: string]: {
+ pricing_strategy: string
+ credits_per_image?: number
+ credits_by_resolution?: { [key: string]: number }
+ base_credits_by_mode?: { [key: string]: number }
+ resolution_multipliers?: { [key: string]: number }
+ input_image_multipliers?: { [key: string]: number }
+ default_resolution?: string
+ default_mode?: string
+ }
+ }
+ fallback: {
+ default_credits_per_image: number
+ }
+}
+
+interface ImageDimensions {
+ width: number
+ height: number
+}
+
+function mapResolutionToNanoBananaPro(maxDimension: number): string {
+ if (maxDimension <= 1500) {
+ return '1K'
+ } else if (maxDimension <= 3000) {
+ return '2K'
+ } else {
+ return '4K'
+ }
+}
+
+function findClosestResolution(
+ width: number,
+ height: number,
+ availableResolutions: { [key: string]: number }
+): string {
+ const megapixels = (width * height) / 1_000_000
+ let closestRes = '1024x1024'
+ let minDiff = Infinity
+
+ for (const [res, multiplier] of Object.entries(availableResolutions)) {
+ // Parse resolution string like "1024x1024" to get dimensions
+ const [resWidth, resHeight] = res.split('x').map(Number)
+ const resMegapixels = (resWidth * resHeight) / 1_000_000
+ const diff = Math.abs(resMegapixels - megapixels)
+
+ if (diff < minDiff) {
+ minDiff = diff
+ closestRes = res
+ }
+ }
+
+ return closestRes
+}
+
+function calculateCredits(
+ provider: Provider,
+ numGarmentImages: number,
+ imageDimensions: ImageDimensions | null,
+ pricingConfig: PricingConfig
+): number {
+ const modelConfig = pricingConfig.models[provider]
+ if (!modelConfig) {
+ return pricingConfig.fallback.default_credits_per_image
+ }
+
+ const totalInputImages = 1 + numGarmentImages // 1 model image + garment images
+
+ switch (modelConfig.pricing_strategy) {
+ case 'flat_rate':
+ return modelConfig.credits_per_image || pricingConfig.fallback.default_credits_per_image
+
+ case 'resolution_based':
+ // Use image dimensions if available, otherwise use default
+ if (imageDimensions) {
+ const maxDimension = Math.max(imageDimensions.width, imageDimensions.height)
+ const resolution = mapResolutionToNanoBananaPro(maxDimension)
+ const creditsByRes = modelConfig.credits_by_resolution || {}
+ return creditsByRes[resolution] || pricingConfig.fallback.default_credits_per_image
+ }
+ const defaultRes = modelConfig.default_resolution || '1K'
+ const creditsByRes = modelConfig.credits_by_resolution || {}
+ return creditsByRes[defaultRes] || pricingConfig.fallback.default_credits_per_image
+
+ case 'dynamic':
+ // For virtual try-on, we use multi-image mode
+ const baseCredits = modelConfig.base_credits_by_mode?.['multi-image'] ||
+ modelConfig.base_credits_by_mode?.['image2image'] ||
+ pricingConfig.fallback.default_credits_per_image
+
+ // Get resolution multiplier based on actual image dimensions
+ let resolutionMultiplier = 1.0
+ if (imageDimensions && modelConfig.resolution_multipliers) {
+ const resolution = findClosestResolution(
+ imageDimensions.width,
+ imageDimensions.height,
+ modelConfig.resolution_multipliers
+ )
+ resolutionMultiplier = modelConfig.resolution_multipliers[resolution] || 1.0
+ } else {
+ // Fallback to default resolution
+ const defaultResolution = modelConfig.default_resolution || '1024x1024'
+ resolutionMultiplier = modelConfig.resolution_multipliers?.[defaultResolution] || 1.0
+ }
+
+ // Get input image multiplier (cap at 8 images)
+ const inputImageCount = Math.min(totalInputImages, 8)
+ const inputImageMultiplier = modelConfig.input_image_multipliers?.[String(inputImageCount)] || 1.0
+
+ return Math.round(baseCredits * resolutionMultiplier * inputImageMultiplier)
+
+ default:
+ return pricingConfig.fallback.default_credits_per_image
+ }
+}
+
+export default function Home() {
+ const [modelImage, setModelImage] = useState(null)
+ const [garmentImages, setGarmentImages] = useState([])
+ const [resultImage, setResultImage] = useState(null)
+ const [isGenerating, setIsGenerating] = useState(false)
+ const [error, setError] = useState(null)
+ const [provider, setProvider] = useState('nano-banana')
+ const [imageDimensions, setImageDimensions] = useState(null)
+ const [isModalOpen, setIsModalOpen] = useState(false)
+
+ // Create preview URLs for model and garment images
+ const [modelPreviewUrl, setModelPreviewUrl] = useState(null)
+ const [garmentPreviewUrls, setGarmentPreviewUrls] = useState([])
+
+ // Update preview URLs when images change
+ useEffect(() => {
+ if (modelImage) {
+ const url = URL.createObjectURL(modelImage)
+ setModelPreviewUrl(url)
+ return () => URL.revokeObjectURL(url)
+ } else {
+ setModelPreviewUrl(null)
+ }
+ }, [modelImage])
+
+ useEffect(() => {
+ const urls = garmentImages.map(file => URL.createObjectURL(file))
+ setGarmentPreviewUrls(urls)
+ return () => {
+ urls.forEach(url => URL.revokeObjectURL(url))
+ }
+ }, [garmentImages])
+
+ // Extract image dimensions when model image is uploaded (reuse preview URL)
+ useEffect(() => {
+ if (modelPreviewUrl) {
+ const img = new Image()
+
+ img.onload = () => {
+ setImageDimensions({
+ width: img.width,
+ height: img.height
+ })
+ }
+
+ img.onerror = () => {
+ setImageDimensions(null)
+ }
+
+ img.src = modelPreviewUrl
+ } else {
+ setImageDimensions(null)
+ }
+ }, [modelPreviewUrl])
+
+ // Calculate credits based on provider, number of images, and image dimensions
+ const estimatedCredits = useMemo(() => {
+ return calculateCredits(
+ provider,
+ garmentImages.length,
+ imageDimensions,
+ pricingConfig as PricingConfig
+ )
+ }, [provider, garmentImages.length, imageDimensions])
+
+ const handleGenerate = async () => {
+ if (!modelImage || garmentImages.length === 0) {
+ setError('Please upload a model image and at least one garment image')
+ return
+ }
+
+ setIsGenerating(true)
+ setError(null)
+ setResultImage(null)
+
+ try {
+ const formData = new FormData()
+ formData.append('model_image', modelImage)
+
+ garmentImages.forEach((garment) => {
+ formData.append('garment_images', garment)
+ })
+
+ formData.append('provider', provider)
+ formData.append('prompt', 'Create a realistic virtual try-on image showing the person wearing the provided garments. CRITICAL REQUIREMENTS - Preserve all details exactly: 1. GARMENT EXTRACTION: The garment images may contain people wearing the garments. IGNORE and EXTRACT ONLY the garment itself - do not use any person, model, or human figure from the garment images. Focus solely on the garment: its shape, design, patterns, colors, textures, and all visual details. Remove or ignore any human elements from garment images. 2. GARMENT PRESERVATION: Keep ALL garment details completely intact - patterns, colors, textures, designs, prints, logos, text, embroidery, sequins, and any decorative elements must remain identical to the original garment images. Do not alter, fade, or modify any garment features. 3. PERSON PRESERVATION: Keep the person\'s face, body shape, skin tone, hair, and physical characteristics exactly as shown in the FIRST image (model image). Only apply the extracted garments from the subsequent images to this person. Do not use any person from garment images. 4. PARTIAL GARMENT HANDLING: If the person in the model image is wearing a full-body outfit (dress, jumpsuit, etc.) but the provided garment is only upper-body (top, shirt, blouse) or lower-body (pants, jeans, skirt), place the provided garment correctly over the corresponding body part. For the remaining uncovered body parts, generate an appropriate complementary garment that matches: (a) the person\'s physical characteristics and body type, (b) the person\'s style and personality traits visible in the model image, (c) the style, color scheme, and design aesthetic of the provided garment. The complementary garment should create a cohesive, harmonious outfit that looks natural and well-coordinated. 5. FITTING: The extracted garments should fit naturally on the person\'s body from the first image, following their body contours and proportions realistically, while maintaining all original garment details from the garment images. 6. COMPOSITION: The first image is the model/person to dress. The following images contain garments (top, bottom, accessories, etc.) - extract ONLY the garments from these images, ignoring any people shown. Combine the extracted garments to create a cohesive outfit where each garment maintains its original appearance and fits the person naturally. 7. REALISM: The final image should look like a professional photograph of the person from the first image wearing the exact extracted garments (and complementary garments if needed), with realistic lighting, shadows, and fabric draping.')
+
+ const response = await fetch(`${API_URL}/api/v1/virtual-tryon`, {
+ method: 'POST',
+ body: formData,
+ })
+
+ if (!response.ok) {
+ const errorData = await response.json()
+ throw new Error(errorData.detail || 'Failed to generate try-on image')
+ }
+
+ const data = await response.json()
+
+ if (data.success && data.image) {
+ setResultImage(data.image)
+ } else {
+ throw new Error('No image received from server')
+ }
+ } catch (err) {
+ console.error('Error generating try-on:', err)
+
+ // Provide more specific error messages
+ if (err instanceof TypeError && err.message.includes('fetch')) {
+ setError(`Cannot connect to API server at ${API_URL}. Please ensure the server is running.`)
+ } else if (err instanceof Error) {
+ setError(err.message)
+ } else {
+ setError('An error occurred while generating the try-on image')
+ }
+ } finally {
+ setIsGenerating(false)
+ }
+ }
+
+ return (
+
+ {/* Main Content */}
+
+ {/* Header */}
+
+
+
+
+ {/* Main Title */}
+
+
Virtual Try-On
+
Generate realistic try-on images with AI
+
+
+
+
+
+
+ {/* Content Area */}
+
+
+ {/* Left Panel - Input Form */}
+
+ {/* Model Selection */}
+
+
+ Select Model
+
+
+
+
+
+
+
+
+
+
+
+ {/* Model Image Upload */}
+
+
+ Model Image
+
+
+
+
+
+
+ {/* Garment Images Upload */}
+
+
+ Garment Images
+
+
+
+
+
+
+ {/* Estimated Cost */}
+
+
+
+ π°
+ Estimated Cost
+
+
{estimatedCredits} Credits
+
+
+ {imageDimensions && (
+
+ Resolution: {imageDimensions.width}Γ{imageDimensions.height}px
+
+ )}
+ {garmentImages.length > 0 && (
+
+ {1 + garmentImages.length} image{1 + garmentImages.length !== 1 ? 's' : ''} total
+
+ )}
+
+
+
+ {/* Generate Button */}
+
+
+ {/* Error Message */}
+ {error && (
+
+ )}
+
+
+ {/* Right Panel - Image Output */}
+
+
+
+ Generated Image
+
+
+
+ {resultImage ? (
+ <>
+
+

+
+
+ >
+ ) : (
+
+
+
+
+
No Image Generated
+
Generated image will appear here after completion
+
+ )}
+
+
+
+
+
+
+
+
+ {/* Comparison Modal */}
+ {isModalOpen && resultImage && (
+
setIsModalOpen(false)}
+ >
+
e.stopPropagation()}
+ style={{ backgroundColor: '#ffffff', boxShadow: '0 20px 25px -5px rgb(0 0 0 / 0.1), 0 10px 10px -5px rgb(0 0 0 / 0.04)' }}
+ >
+ {/* Modal Header */}
+
+
Image Comparison
+
+
+
+ {/* Modal Content */}
+
+
+ {/* Model Image */}
+
+
Model Image
+ {modelPreviewUrl ? (
+
+

+
+ ) : (
+
+ )}
+
+
+ {/* Garment Images */}
+
+
+ Garment Images ({garmentPreviewUrls.length})
+
+ {garmentPreviewUrls.length > 0 ? (
+
+ {garmentPreviewUrls.map((url, index) => (
+
+

+
+ ))}
+
+ ) : (
+
+ )}
+
+
+ {/* Generated Result */}
+
+
Generated Result
+
+

+
+
+
+
+
+
+ )}
+
+ )
+}
diff --git a/demo/virtual-tryon/components/image-upload.tsx b/demo/virtual-tryon/components/image-upload.tsx
new file mode 100644
index 0000000..2a263cc
--- /dev/null
+++ b/demo/virtual-tryon/components/image-upload.tsx
@@ -0,0 +1,385 @@
+'use client'
+
+import { useCallback, useState, useEffect, useRef } from 'react'
+import { useDropzone } from 'react-dropzone'
+import { HiPhoto, HiXMark, HiPlus } from 'react-icons/hi2'
+import { cn } from '@/lib/utils'
+
+interface ImageUploadProps {
+ onImageChange: (file: File | null) => void
+ currentImage: File | null
+ previewUrl?: string | null
+ label?: string
+ description?: string
+ accept?: Record
+ maxFiles?: number
+ multiple?: boolean
+ layout?: 'grid' | 'horizontal' | 'masonry' | 'compact'
+ gridCols?: 2 | 3 | 4 | 5
+}
+
+export function ImageUpload({
+ onImageChange,
+ currentImage,
+ previewUrl,
+ label,
+ description,
+ accept = { 'image/*': ['.jpeg', '.jpg', '.png', '.webp'] },
+ maxFiles = 1,
+ multiple = false,
+ layout = 'grid',
+ gridCols = 3,
+}: ImageUploadProps) {
+ const [preview, setPreview] = useState(previewUrl || null)
+ const currentFileRef = useRef(null)
+
+ useEffect(() => {
+ // Reset preview if no image
+ if (!currentImage && !previewUrl) {
+ setPreview(null)
+ currentFileRef.current = null
+ return
+ }
+
+ // Use previewUrl if provided (external preview)
+ if (previewUrl) {
+ setPreview(previewUrl)
+ return
+ }
+
+ // Create preview from currentImage file
+ if (currentImage) {
+ // Check if this is the same file we already processed
+ const isSameFile = currentFileRef.current === currentImage
+ if (isSameFile) {
+ // Already have preview for this file, don't recreate
+ return
+ }
+
+ // Mark this file as processed
+ currentFileRef.current = currentImage
+
+ // Create new preview
+ const reader = new FileReader()
+ reader.onloadend = () => {
+ setPreview(reader.result as string)
+ }
+ reader.readAsDataURL(currentImage)
+ }
+ }, [currentImage, previewUrl])
+
+ const onDrop = useCallback(
+ (acceptedFiles: File[]) => {
+ if (acceptedFiles.length > 0) {
+ const file = acceptedFiles[0]
+ onImageChange(file)
+ }
+ },
+ [onImageChange]
+ )
+
+ const { getRootProps, getInputProps, isDragActive } = useDropzone({
+ onDrop,
+ accept,
+ maxFiles,
+ multiple,
+ disabled: maxFiles === 1 && preview !== null,
+ })
+
+ const handleRemove = () => {
+ onImageChange(null)
+ setPreview(null)
+ }
+
+ const hasImage = preview !== null
+ const canUpload = maxFiles === 1 ? !hasImage : true
+
+ // Grid Layout (Default)
+ if (layout === 'grid') {
+ // Responsive grid: 1 col on mobile, 2 on tablet, original on desktop
+ const gridColsClass = {
+ 2: 'grid-cols-1 sm:grid-cols-2',
+ 3: 'grid-cols-1 sm:grid-cols-2 lg:grid-cols-3',
+ 4: 'grid-cols-2 sm:grid-cols-3 lg:grid-cols-4',
+ 5: 'grid-cols-2 sm:grid-cols-3 lg:grid-cols-5',
+ }[gridCols] || 'grid-cols-1 sm:grid-cols-2 lg:grid-cols-3'
+
+ return (
+
+ {label && (
+
+ )}
+ {description && (
+
{description}
+ )}
+
+
+ {/* Upload Dropzone - Always First */}
+ {canUpload && (
+
+
+
+
+
+
+
+
+ {isDragActive ? 'Drop here' : 'Upload'}
+
+
+ {isDragActive ? 'Release' : 'Click or drag'}
+
+
+
+
+ )}
+
+ {/* Uploaded Image - Only show once */}
+ {hasImage && preview && (
+
+

+
+
+ )}
+
+
+ )
+ }
+
+ // Horizontal Scroll Layout
+ if (layout === 'horizontal') {
+ return (
+
+ {label && (
+
+ )}
+ {description && (
+
{description}
+ )}
+
+
+ {/* Upload Dropzone */}
+ {canUpload && (
+
+ )}
+
+ {/* Uploaded Image - Only show once */}
+ {hasImage && preview && (
+
+

+
+
+ )}
+
+
+ )
+ }
+
+ // Masonry Layout
+ if (layout === 'masonry') {
+ return (
+
+ {label && (
+
+ )}
+ {description && (
+
{description}
+ )}
+
+
+ {/* Upload Dropzone */}
+ {canUpload && (
+
+
+
+
+
+
+
+ {isDragActive ? 'Drop here' : 'Upload Image'}
+
+
+
+ )}
+
+ {/* Uploaded Image - Only show once */}
+ {hasImage && preview && (
+
+

+
+
+ )}
+
+
+ )
+ }
+
+ // Compact Layout
+ if (layout === 'compact') {
+ return (
+
+ {label && (
+
+ )}
+ {description && (
+
{description}
+ )}
+
+
+ {/* Upload Dropzone - Compact */}
+ {canUpload && (
+
+
+
+
+ )}
+
+ {/* Uploaded Image - Only show once */}
+ {hasImage && preview && (
+
+

+
+
+ )}
+
+
+ )
+ }
+
+ // Fallback to grid
+ return null
+}
diff --git a/demo/virtual-tryon/components/multi-image-upload.tsx b/demo/virtual-tryon/components/multi-image-upload.tsx
new file mode 100644
index 0000000..ded1cbe
--- /dev/null
+++ b/demo/virtual-tryon/components/multi-image-upload.tsx
@@ -0,0 +1,402 @@
+'use client'
+
+import { useCallback, useState, useEffect } from 'react'
+import { useDropzone } from 'react-dropzone'
+import { HiPhoto, HiXMark, HiPlus } from 'react-icons/hi2'
+import { cn } from '@/lib/utils'
+
+interface GarmentImage {
+ file: File
+ preview: string
+ id: string
+ category?: string
+}
+
+interface MultiImageUploadProps {
+ onImagesChange: (files: File[]) => void
+ currentImages: File[]
+ label?: string
+ description?: string
+ accept?: Record
+ maxFiles?: number
+ categories?: string[]
+ layout?: 'grid' | 'horizontal' | 'masonry' | 'compact'
+ gridCols?: 2 | 3 | 4 | 5
+}
+
+export function MultiImageUpload({
+ onImagesChange,
+ currentImages,
+ label,
+ description,
+ accept = { 'image/*': ['.jpeg', '.jpg', '.png', '.webp'] },
+ maxFiles = 10,
+ categories = ['Top', 'Jeans', 'Scarf', 'Hat', 'Glasses'],
+ layout = 'grid',
+ gridCols = 4,
+}: MultiImageUploadProps) {
+ const [garmentImages, setGarmentImages] = useState([])
+
+ useEffect(() => {
+ // Initialize from currentImages
+ const images = currentImages.map((file, index) => ({
+ file,
+ preview: URL.createObjectURL(file),
+ id: `garment-${index}-${Date.now()}`,
+ }))
+ setGarmentImages(images)
+ }, [currentImages])
+
+ const onDrop = useCallback(
+ (acceptedFiles: File[]) => {
+ const newImages: GarmentImage[] = acceptedFiles.map((file) => ({
+ file,
+ preview: URL.createObjectURL(file),
+ id: `garment-${Date.now()}-${Math.random()}`,
+ }))
+
+ const updatedImages = [...garmentImages, ...newImages].slice(0, maxFiles)
+ setGarmentImages(updatedImages)
+ onImagesChange(updatedImages.map((img) => img.file))
+ },
+ [garmentImages, maxFiles, onImagesChange]
+ )
+
+ const { getRootProps, getInputProps, isDragActive } = useDropzone({
+ onDrop,
+ accept,
+ multiple: true,
+ maxFiles,
+ })
+
+ const handleRemove = (id: string) => {
+ const updatedImages = garmentImages.filter((img) => {
+ if (img.id === id) {
+ URL.revokeObjectURL(img.preview)
+ return false
+ }
+ return true
+ })
+ setGarmentImages(updatedImages)
+ onImagesChange(updatedImages.map((img) => img.file))
+ }
+
+ const canAddMore = garmentImages.length < maxFiles
+
+ // Grid Layout (Default) - Upload zone as first item
+ if (layout === 'grid') {
+ // Responsive grid: 2 cols on mobile, 3 on tablet, original on desktop
+ const gridColsClass = {
+ 2: 'grid-cols-2',
+ 3: 'grid-cols-2 sm:grid-cols-3',
+ 4: 'grid-cols-2 sm:grid-cols-3 lg:grid-cols-4',
+ 5: 'grid-cols-2 sm:grid-cols-3 lg:grid-cols-5',
+ }[gridCols] || 'grid-cols-2 sm:grid-cols-3 lg:grid-cols-4'
+
+ return (
+
+ {label && (
+
+ )}
+ {description && (
+
{description}
+ )}
+
+
+ {/* Upload Dropzone - Always First */}
+ {canAddMore && (
+
+
+
+
+
+
+
+
+ {isDragActive ? 'Drop here' : 'Upload'}
+
+
+ {isDragActive ? 'Release' : 'Click or drag'}
+
+
+ {garmentImages.length > 0 && (
+
+ {garmentImages.length} / {maxFiles}
+
+ )}
+
+
+ )}
+
+ {/* Uploaded Images */}
+ {garmentImages.map((garment) => (
+
+

+
+ {garment.category && (
+
+ {garment.category}
+
+ )}
+
+ ))}
+
+
+ {categories.length > 0 && garmentImages.length === 0 && (
+
+ {categories.map((category) => (
+
+ {category}
+
+ ))}
+
+ )}
+
+ {!canAddMore && (
+
+ Maximum {maxFiles} images reached. Remove some to add more.
+
+ )}
+
+ )
+ }
+
+ // Horizontal Scroll Layout
+ if (layout === 'horizontal') {
+ return (
+
+ {label && (
+
+ )}
+ {description && (
+
{description}
+ )}
+
+
+ {/* Upload Dropzone - First */}
+ {canAddMore && (
+
+ )}
+
+ {/* Uploaded Images */}
+ {garmentImages.map((garment) => (
+
+

+
+
+ ))}
+
+
+ )
+ }
+
+ // Masonry Layout
+ if (layout === 'masonry') {
+ return (
+
+ {label && (
+
+ )}
+ {description && (
+
{description}
+ )}
+
+
+ {/* Upload Dropzone */}
+ {canAddMore && (
+
+
+
+
+
+
+
+ {isDragActive ? 'Drop here' : 'Upload'}
+
+
+
+ )}
+
+ {/* Uploaded Images */}
+ {garmentImages.map((garment) => (
+
+

+
+
+ ))}
+
+
+ )
+ }
+
+ // Compact Layout
+ if (layout === 'compact') {
+ return (
+
+ {label && (
+
+ )}
+ {description && (
+
{description}
+ )}
+
+
+ {/* Upload Dropzone - Compact */}
+ {canAddMore && (
+
+
+
+
+ )}
+
+ {/* Uploaded Images */}
+ {garmentImages.map((garment) => (
+
+

+
+
+ ))}
+
+
+ )
+ }
+
+ return null
+}
diff --git a/demo/virtual-tryon/components/ui/button.tsx b/demo/virtual-tryon/components/ui/button.tsx
new file mode 100644
index 0000000..537d711
--- /dev/null
+++ b/demo/virtual-tryon/components/ui/button.tsx
@@ -0,0 +1,51 @@
+import { cn } from '@/lib/utils'
+
+export function Button({
+ children,
+ variant = 'primary',
+ className,
+ ...props
+}: {
+ children: React.ReactNode
+ variant?: 'primary' | 'secondary' | 'outline'
+ className?: string
+} & React.ButtonHTMLAttributes) {
+ const variants = {
+ primary: 'bg-primary-500 text-white hover:bg-primary-600',
+ secondary: 'bg-neutral-100 text-neutral-700 hover:bg-neutral-200',
+ outline: 'border-2 border-primary-500 text-primary-500 hover:bg-primary-50',
+ }
+
+ const shadowStyles = variant === 'primary'
+ ? { boxShadow: '0 1px 2px 0 rgb(0 0 0 / 0.05), 0 1px 3px 0 rgb(0 0 0 / 0.1)' }
+ : {}
+
+ const hoverShadowStyles = variant === 'primary'
+ ? { boxShadow: '0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1)' }
+ : {}
+
+ return (
+
+ )
+}
+
diff --git a/demo/virtual-tryon/components/ui/card.tsx b/demo/virtual-tryon/components/ui/card.tsx
new file mode 100644
index 0000000..3350ab3
--- /dev/null
+++ b/demo/virtual-tryon/components/ui/card.tsx
@@ -0,0 +1,68 @@
+import { cn } from '@/lib/utils'
+
+export function Card({
+ children,
+ className,
+}: {
+ children: React.ReactNode
+ className?: string
+}) {
+ return (
+
+ {children}
+
+ )
+}
+
+export function CardHeader({
+ children,
+ className,
+}: {
+ children: React.ReactNode
+ className?: string
+}) {
+ return (
+
+ {children}
+
+ )
+}
+
+export function CardTitle({
+ children,
+ className,
+}: {
+ children: React.ReactNode
+ className?: string
+}) {
+ return (
+
+ {children}
+
+ )
+}
+
+export function CardContent({
+ children,
+ className,
+}: {
+ children: React.ReactNode
+ className?: string
+}) {
+ return (
+
+ {children}
+
+ )
+}
+
diff --git a/demo/virtual-tryon/next.config.js b/demo/virtual-tryon/next.config.js
new file mode 100644
index 0000000..159d810
--- /dev/null
+++ b/demo/virtual-tryon/next.config.js
@@ -0,0 +1,7 @@
+/** @type {import('next').NextConfig} */
+const nextConfig = {
+ reactStrictMode: true,
+}
+
+module.exports = nextConfig
+
diff --git a/demo/virtual-tryon/package-lock.json b/demo/virtual-tryon/package-lock.json
new file mode 100644
index 0000000..957a5c0
--- /dev/null
+++ b/demo/virtual-tryon/package-lock.json
@@ -0,0 +1,5877 @@
+{
+ "name": "virtual-tryon-demo",
+ "version": "0.1.0",
+ "lockfileVersion": 3,
+ "requires": true,
+ "packages": {
+ "": {
+ "name": "virtual-tryon-demo",
+ "version": "0.1.0",
+ "dependencies": {
+ "clsx": "^2.1.0",
+ "next": "^15.0.0",
+ "react": "^18.3.1",
+ "react-dom": "^18.3.1",
+ "react-dropzone": "^14.2.3",
+ "react-icons": "^5.2.1",
+ "tailwind-merge": "^2.2.1"
+ },
+ "devDependencies": {
+ "@types/node": "^20.11.0",
+ "@types/react": "^18.2.48",
+ "@types/react-dom": "^18.2.18",
+ "autoprefixer": "^10.4.17",
+ "eslint": "^8.56.0",
+ "eslint-config-next": "^15.0.0",
+ "postcss": "^8.4.33",
+ "tailwindcss": "^3.4.1",
+ "typescript": "^5.3.3"
+ }
+ },
+ "node_modules/@alloc/quick-lru": {
+ "version": "5.2.0",
+ "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
+ "integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==",
+ "dev": true,
+ "engines": {
+ "node": ">=10"
+ },
+ "funding": {
+ "url": "https://github.com/sponsors/sindresorhus"
+ }
+ },
+ "node_modules/@emnapi/core": {
+ "version": "1.7.1",
+ "resolved": "https://registry.npmjs.org/@emnapi/core/-/core-1.7.1.tgz",
+ "integrity": "sha512-o1uhUASyo921r2XtHYOHy7gdkGLge8ghBEQHMWmyJFoXlpU58kIrhhN3w26lpQb6dspetweapMn2CSNwQ8I4wg==",
+ "dev": true,
+ "optional": true,
+ "dependencies": {
+ "@emnapi/wasi-threads": "1.1.0",
+ "tslib": "^2.4.0"
+ }
+ },
+ "node_modules/@emnapi/runtime": {
+ "version": "1.7.1",
+ "resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.7.1.tgz",
+ "integrity": "sha512-PVtJr5CmLwYAU9PZDMITZoR5iAOShYREoR45EyyLrbntV50mdePTgUn4AmOw90Ifcj+x2kRjdzr1HP3RrNiHGA==",
+ "optional": true,
+ "dependencies": {
+ "tslib": "^2.4.0"
+ }
+ },
+ "node_modules/@emnapi/wasi-threads": {
+ "version": "1.1.0",
+ "resolved": "https://registry.npmjs.org/@emnapi/wasi-threads/-/wasi-threads-1.1.0.tgz",
+ "integrity": "sha512-WI0DdZ8xFSbgMjR1sFsKABJ/C5OnRrjT06JXbZKexJGrDuPTzZdDYfFlsgcCXCyf+suG5QU2e/y1Wo2V/OapLQ==",
+ "dev": true,
+ "optional": true,
+ "dependencies": {
+ "tslib": "^2.4.0"
+ }
+ },
+ "node_modules/@eslint-community/eslint-utils": {
+ "version": "4.9.0",
+ "resolved": "https://registry.npmjs.org/@eslint-community/eslint-utils/-/eslint-utils-4.9.0.tgz",
+ "integrity": "sha512-ayVFHdtZ+hsq1t2Dy24wCmGXGe4q9Gu3smhLYALJrr473ZH27MsnSL+LKUlimp4BWJqMDMLmPpx/Q9R3OAlL4g==",
+ "dev": true,
+ "dependencies": {
+ "eslint-visitor-keys": "^3.4.3"
+ },
+ "engines": {
+ "node": "^12.22.0 || ^14.17.0 || >=16.0.0"
+ },
+ "funding": {
+ "url": "https://opencollective.com/eslint"
+ },
+ "peerDependencies": {
+ "eslint": "^6.0.0 || ^7.0.0 || >=8.0.0"
+ }
+ },
+ "node_modules/@eslint-community/regexpp": {
+ "version": "4.12.2",
+ "resolved": "https://registry.npmjs.org/@eslint-community/regexpp/-/regexpp-4.12.2.tgz",
+ "integrity": "sha512-EriSTlt5OC9/7SXkRSCAhfSxxoSUgBm33OH+IkwbdpgoqsSsUg7y3uh+IICI/Qg4BBWr3U2i39RpmycbxMq4ew==",
+ "dev": true,
+ "engines": {
+ "node": "^12.0.0 || ^14.0.0 || >=16.0.0"
+ }
+ },
+ "node_modules/@eslint/eslintrc": {
+ "version": "2.1.4",
+ "resolved": "https://registry.npmjs.org/@eslint/eslintrc/-/eslintrc-2.1.4.tgz",
+ "integrity": "sha512-269Z39MS6wVJtsoUl10L60WdkhJVdPG24Q4eZTH3nnF6lpvSShEK3wQjDX9JRWAUPvPh7COouPpU9IrqaZFvtQ==",
+ "dev": true,
+ "dependencies": {
+ "ajv": "^6.12.4",
+ "debug": "^4.3.2",
+ "espree": "^9.6.0",
+ "globals": "^13.19.0",
+ "ignore": "^5.2.0",
+ "import-fresh": "^3.2.1",
+ "js-yaml": "^4.1.0",
+ "minimatch": "^3.1.2",
+ "strip-json-comments": "^3.1.1"
+ },
+ "engines": {
+ "node": "^12.22.0 || ^14.17.0 || >=16.0.0"
+ },
+ "funding": {
+ "url": "https://opencollective.com/eslint"
+ }
+ },
+ "node_modules/@eslint/js": {
+ "version": "8.57.1",
+ "resolved": "https://registry.npmjs.org/@eslint/js/-/js-8.57.1.tgz",
+ "integrity": "sha512-d9zaMRSTIKDLhctzH12MtXvJKSSUhaHcjV+2Z+GK+EEY7XKpP5yR4x+N3TAcHTcu963nIr+TMcCb4DBCYX1z6Q==",
+ "dev": true,
+ "engines": {
+ "node": "^12.22.0 || ^14.17.0 || >=16.0.0"
+ }
+ },
+ "node_modules/@humanwhocodes/config-array": {
+ "version": "0.13.0",
+ "resolved": "https://registry.npmjs.org/@humanwhocodes/config-array/-/config-array-0.13.0.tgz",
+ "integrity": "sha512-DZLEEqFWQFiyK6h5YIeynKx7JlvCYWL0cImfSRXZ9l4Sg2efkFGTuFf6vzXjK1cq6IYkU+Eg/JizXw+TD2vRNw==",
+ "deprecated": "Use @eslint/config-array instead",
+ "dev": true,
+ "dependencies": {
+ "@humanwhocodes/object-schema": "^2.0.3",
+ "debug": "^4.3.1",
+ "minimatch": "^3.0.5"
+ },
+ "engines": {
+ "node": ">=10.10.0"
+ }
+ },
+ "node_modules/@humanwhocodes/module-importer": {
+ "version": "1.0.1",
+ "resolved": "https://registry.npmjs.org/@humanwhocodes/module-importer/-/module-importer-1.0.1.tgz",
+ "integrity": "sha512-bxveV4V8v5Yb4ncFTT3rPSgZBOpCkjfK0y4oVVVJwIuDVBRMDXrPyXRL988i5ap9m9bnyEEjWfm5WkBmtffLfA==",
+ "dev": true,
+ "engines": {
+ "node": ">=12.22"
+ },
+ "funding": {
+ "type": "github",
+ "url": "https://github.com/sponsors/nzakas"
+ }
+ },
+ "node_modules/@humanwhocodes/object-schema": {
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diff --git a/demo/virtual-tryon/package.json b/demo/virtual-tryon/package.json
new file mode 100644
index 0000000..fd9c524
--- /dev/null
+++ b/demo/virtual-tryon/package.json
@@ -0,0 +1,32 @@
+{
+ "name": "virtual-tryon-demo",
+ "version": "0.1.0",
+ "private": true,
+ "scripts": {
+ "dev": "next dev",
+ "build": "next build",
+ "start": "next start",
+ "lint": "next lint"
+ },
+ "dependencies": {
+ "react": "^18.3.1",
+ "react-dom": "^18.3.1",
+ "next": "^15.0.0",
+ "react-dropzone": "^14.2.3",
+ "react-icons": "^5.2.1",
+ "clsx": "^2.1.0",
+ "tailwind-merge": "^2.2.1"
+ },
+ "devDependencies": {
+ "typescript": "^5.3.3",
+ "@types/node": "^20.11.0",
+ "@types/react": "^18.2.48",
+ "@types/react-dom": "^18.2.18",
+ "autoprefixer": "^10.4.17",
+ "postcss": "^8.4.33",
+ "tailwindcss": "^3.4.1",
+ "eslint": "^8.56.0",
+ "eslint-config-next": "^15.0.0"
+ }
+}
+
diff --git a/demo/virtual-tryon/postcss.config.js b/demo/virtual-tryon/postcss.config.js
new file mode 100644
index 0000000..2ce518b
--- /dev/null
+++ b/demo/virtual-tryon/postcss.config.js
@@ -0,0 +1,7 @@
+module.exports = {
+ plugins: {
+ tailwindcss: {},
+ autoprefixer: {},
+ },
+}
+
diff --git a/demo/virtual-tryon/pricing_config.json b/demo/virtual-tryon/pricing_config.json
new file mode 100644
index 0000000..516ac36
--- /dev/null
+++ b/demo/virtual-tryon/pricing_config.json
@@ -0,0 +1,125 @@
+{
+ "version": "1.2",
+ "last_updated": "2025-01-27",
+ "models": {
+ "nano-banana": {
+ "pricing_strategy": "flat_rate",
+ "credits_per_image": 5,
+ "description": "Google Gemini 2.5 Flash Image (gemini-2.5-flash-image) - flat rate pricing. Based on official Google Gemini API pricing: approximately $0.039 per image (1,290 tokens for 1024x1024 images).",
+ "source": "https://ai.google.dev/gemini-api/docs/pricing#standard",
+ "pricing_notes": {
+ "cost_per_image": "$0.039 per image (1,290 tokens for 1024x1024 resolution)",
+ "token_consumption": "1,290 tokens per image output up to 1024x1024 pixels",
+ "resolution": "Fixed resolution: 1024x1024 pixels (1 megapixel)"
+ }
+ },
+ "nano-banana-pro": {
+ "pricing_strategy": "resolution_based",
+ "description": "Google Gemini 3 Pro Image Preview (gemini-3-pro-image-preview) - resolution-based pricing. Based on official Google Gemini API pricing: 1K/2K images cost $0.134/image, 4K images cost $0.24/image.",
+ "credits_by_resolution": {
+ "1K": 15,
+ "2K": 15,
+ "4K": 26
+ },
+ "default_resolution": "1K",
+ "source": "https://ai.google.dev/gemini-api/docs/pricing#standard",
+ "pricing_notes": {
+ "1K": "Based on $0.134 per image (1120 tokens at $120/1M tokens output + $0.0011 input)",
+ "2K": "Based on $0.134 per image (1120 tokens at $120/1M tokens output + $0.0011 input)",
+ "4K": "Based on $0.24 per image (2000 tokens at $120/1M tokens output + $0.0011 input)"
+ }
+ },
+ "flux-1-kontext-pro": {
+ "pricing_strategy": "mode_based",
+ "description": "FLUX.1 Kontext Pro - mode-based pricing. Pricing varies by generation mode (text2image, image2image, fusion). Based on BFL/Azure pricing structure.",
+ "source": "https://bfl.ai/pricing",
+ "credits_by_mode": {
+ "text2image": 5,
+ "image2image": 6,
+ "fusion": 7
+ },
+ "default_mode": "text2image",
+ "pricing_notes": {
+ "text2image": "Base text-to-image generation pricing",
+ "image2image": "Single input image editing/composition",
+ "fusion": "Multiple input images composition/fusion"
+ }
+ },
+ "flux-2-pro": {
+ "pricing_strategy": "dynamic",
+ "description": "FLUX.2 [PRO] - dynamic pricing based on output resolution (megapixels) and input images. Pricing scales with megapixels generated. Based on BFL official pricing: text2image starts at $0.03/image, image editing starts at $0.045/edit.",
+ "source": "https://bfl.ai/pricing",
+ "base_credits_by_mode": {
+ "text2image": 4,
+ "image2image": 6,
+ "multi-image": 8
+ },
+ "resolution_multipliers": {
+ "1024x1024": 1.0,
+ "1536x1536": 1.5,
+ "2048x2048": 2.0,
+ "3072x3072": 3.5,
+ "4096x4096": 4.0
+ },
+ "input_image_multipliers": {
+ "0": 1.0,
+ "1": 1.0,
+ "2": 1.2,
+ "3": 1.4,
+ "4": 1.6,
+ "5": 1.8,
+ "6": 2.0,
+ "7": 2.2,
+ "8": 2.4
+ },
+ "default_mode": "text2image",
+ "default_resolution": "1024x1024",
+ "pricing_notes": {
+ "base": "Base pricing: text2image $0.03/image, image editing $0.045/edit. Cost scales with megapixels (width Γ height / 1M).",
+ "resolution": "Resolution multipliers approximate megapixel scaling: 1024Γ1024=1MP, 2048Γ2048=4MP, 4096Γ4096=16MP",
+ "input_images": "Input images increase cost. Multi-image mode uses higher base cost."
+ }
+ },
+ "flux-2-flex": {
+ "pricing_strategy": "dynamic",
+ "description": "FLUX.2 [FLEX] - dynamic pricing based on output resolution (megapixels) and input images. Pricing scales with megapixels generated. Based on BFL official pricing: text2image starts at $0.06/image, image editing starts at $0.12/edit.",
+ "source": "https://bfl.ai/pricing",
+ "base_credits_by_mode": {
+ "text2image": 7,
+ "image2image": 13,
+ "multi-image": 20
+ },
+ "resolution_multipliers": {
+ "1024x1024": 1.0,
+ "1536x1536": 1.5,
+ "2048x2048": 2.0,
+ "3072x3072": 3.5,
+ "4096x4096": 4.0
+ },
+ "input_image_multipliers": {
+ "0": 1.0,
+ "1": 1.0,
+ "2": 1.2,
+ "3": 1.4,
+ "4": 1.6,
+ "5": 1.8,
+ "6": 2.0,
+ "7": 2.2,
+ "8": 2.4
+ },
+ "default_mode": "text2image",
+ "default_resolution": "1024x1024",
+ "pricing_notes": {
+ "base": "Base pricing: text2image $0.06/image, image editing $0.12/edit. Cost scales with megapixels (width Γ height / 1M).",
+ "resolution": "Resolution multipliers approximate megapixel scaling: 1024Γ1024=1MP, 2048Γ2048=4MP, 4096Γ4096=16MP",
+ "input_images": "Input images increase cost. Multi-image mode uses higher base cost."
+ }
+ }
+ },
+ "fallback": {
+ "default_credits_per_image": 5,
+ "description": "Default fallback pricing for unknown models"
+ }
+ }
+
+
\ No newline at end of file
diff --git a/demo/virtual-tryon/tailwind.config.js b/demo/virtual-tryon/tailwind.config.js
new file mode 100644
index 0000000..9179a9d
--- /dev/null
+++ b/demo/virtual-tryon/tailwind.config.js
@@ -0,0 +1,66 @@
+/** @type {import('tailwindcss').Config} */
+module.exports = {
+ content: [
+ './pages/**/*.{js,ts,jsx,tsx,mdx}',
+ './components/**/*.{js,ts,jsx,tsx,mdx}',
+ './app/**/*.{js,ts,jsx,tsx,mdx}',
+ ],
+ theme: {
+ extend: {
+ colors: {
+ primary: {
+ 50: '#fef2f2',
+ 100: '#fee2e2',
+ 200: '#fecaca',
+ 300: '#fca5a5',
+ 400: '#f87171',
+ 500: '#ef4444',
+ 600: '#dc2626',
+ 700: '#b91c1c',
+ 800: '#991b1b',
+ 900: '#7f1d1d',
+ },
+ neutral: {
+ 50: '#fafafa',
+ 100: '#f5f5f5',
+ 200: '#e5e5e5',
+ 300: '#d4d4d4',
+ 400: '#a3a3a3',
+ 500: '#737373',
+ 600: '#525252',
+ 700: '#404040',
+ 800: '#262626',
+ 900: '#171717',
+ },
+ },
+ fontFamily: {
+ sans: ['Inter', 'ui-sans-serif', 'system-ui', 'sans-serif'],
+ },
+ spacing: {
+ '18': '4.5rem',
+ '88': '22rem',
+ '128': '32rem',
+ },
+ fontSize: {
+ 'xs': ['0.75rem', { lineHeight: '1rem' }],
+ 'sm': ['0.875rem', { lineHeight: '1.25rem' }],
+ 'base': ['1rem', { lineHeight: '1.5rem' }],
+ 'lg': ['1.125rem', { lineHeight: '1.75rem' }],
+ 'xl': ['1.25rem', { lineHeight: '1.75rem' }],
+ '2xl': ['1.5rem', { lineHeight: '2rem' }],
+ '3xl': ['1.875rem', { lineHeight: '2.25rem' }],
+ '4xl': ['2.25rem', { lineHeight: '2.5rem' }],
+ },
+ boxShadow: {
+ 'sm': '0 1px 2px 0 rgb(0 0 0 / 0.05)',
+ 'md': '0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1)',
+ 'lg': '0 10px 15px -3px rgb(0 0 0 / 0.1), 0 4px 6px -4px rgb(0 0 0 / 0.1)',
+ 'xl': '0 20px 25px -5px rgb(0 0 0 / 0.1), 0 8px 10px -6px rgb(0 0 0 / 0.1)',
+ 'card': '0 1px 3px 0 rgb(0 0 0 / 0.1), 0 1px 2px -1px rgb(0 0 0 / 0.1)',
+ 'card-hover': '0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1)',
+ },
+ },
+ },
+ plugins: [],
+}
+
diff --git a/demo/virtual-tryon/tsconfig.json b/demo/virtual-tryon/tsconfig.json
new file mode 100644
index 0000000..8f37f26
--- /dev/null
+++ b/demo/virtual-tryon/tsconfig.json
@@ -0,0 +1,28 @@
+{
+ "compilerOptions": {
+ "target": "ES2017",
+ "lib": ["dom", "dom.iterable", "esnext"],
+ "allowJs": true,
+ "skipLibCheck": true,
+ "strict": true,
+ "noEmit": true,
+ "esModuleInterop": true,
+ "module": "esnext",
+ "moduleResolution": "bundler",
+ "resolveJsonModule": true,
+ "isolatedModules": true,
+ "jsx": "preserve",
+ "incremental": true,
+ "plugins": [
+ {
+ "name": "next"
+ }
+ ],
+ "paths": {
+ "@/*": ["./*"]
+ }
+ },
+ "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"],
+ "exclude": ["node_modules"]
+}
+
diff --git a/docs/docs/demos/overview.md b/docs/docs/demos/overview.md
index 18e1a50..76c9e0e 100644
--- a/docs/docs/demos/overview.md
+++ b/docs/docs/demos/overview.md
@@ -1,26 +1,78 @@
# Demos
-OpenTryOn includes interactive Gradio demos for easy experimentation.
+OpenTryOn includes interactive demos for easy experimentation and testing.
## Available Demos
-### Extract Garment Demo
+### Virtual Try-On Demo (Full-Stack Web App) β NEW
+
+A modern, production-ready virtual try-on web application with FastAPI backend and Next.js frontend.
+
+**Features**:
+- Support for 4 AI models (Nano Banana, Nano Banana Pro, FLUX 2 Pro, FLUX 2 Flex)
+- Multi-image upload with drag & drop
+- Real-time credit estimation
+- Modern, responsive UI
+- RESTful API
+
+**Quick Start**:
+
+1. Start the backend:
+```bash
+python api_server.py
+```
+
+2. In a new terminal, start the frontend:
+```bash
+cd demo/virtual-tryon
+npm install
+npm run dev
+```
+
+3. Open `http://localhost:3000` in your browser
+
+**[Read Full Documentation β](./virtual-tryon)**
+
+---
+
+### Extract Garment Demo (Gradio)
+
+Interactive Gradio demo for garment extraction.
```bash
python run_demo.py --name extract_garment
```
-### Model Swap Demo
+**[Read More β](./extract-garment)**
+
+### Model Swap Demo (Gradio)
+
+Interactive Gradio demo for swapping garments between models.
```bash
python run_demo.py --name model_swap
```
-### Outfit Generator Demo
+**[Read More β](./model-swap)**
+
+### Outfit Generator Demo (Gradio)
+
+Interactive Gradio demo for generating outfits from text prompts.
```bash
python run_demo.py --name outfit_generator
```
-Each demo launches a web interface for interactive use.
+**[Read More β](./outfit-generator)**
+
+---
+
+## Demo Comparison
+
+| Demo | Type | Tech Stack | Use Case |
+|------|------|------------|----------|
+| **Virtual Try-On** | Full-stack Web App | Next.js + FastAPI | Production-ready virtual try-on with multiple AI models |
+| **Extract Garment** | Gradio | Python + Gradio | Quick garment extraction testing |
+| **Model Swap** | Gradio | Python + Gradio | Garment swapping experiments |
+| **Outfit Generator** | Gradio | Python + Gradio | Text-to-outfit generation |
diff --git a/docs/docs/demos/virtual-tryon.md b/docs/docs/demos/virtual-tryon.md
new file mode 100644
index 0000000..726ea0e
--- /dev/null
+++ b/docs/docs/demos/virtual-tryon.md
@@ -0,0 +1,318 @@
+# Virtual Try-On Demo
+
+A modern, full-stack virtual try-on web application featuring a Next.js frontend and FastAPI backend. Generate realistic virtual try-on images using state-of-the-art AI models.
+
+## Overview
+
+The Virtual Try-On Demo is a production-ready web application that showcases OpenTryOn's capabilities with a beautiful, user-friendly interface. Unlike the Gradio demos, this is a complete full-stack application suitable for production deployment.
+
+### Key Features
+
+- **π€ Multiple AI Models**: Choose from 4 powerful image generation models
+ - **Nano Banana** (Gemini 2.5 Flash) - Fast, efficient, 1024px
+ - **Nano Banana Pro** (Gemini 3 Pro) - Advanced, up to 4K with search grounding
+ - **FLUX 2 Pro** - High-quality professional results
+ - **FLUX 2 Flex** - Flexible with advanced controls
+
+- **πΌοΈ Modern UI**: Beautiful, responsive Next.js interface
+- **π€ Multi-Image Upload**: Drag & drop support for model and garment images
+- **π° Real-Time Cost Estimation**: Dynamic credit calculation based on resolution and image count
+- **π Live Processing**: View generation progress and results
+- **π± Responsive Design**: Works on desktop, tablet, and mobile
+
+## Architecture
+
+### Frontend (Next.js 15)
+- Modern React/TypeScript application
+- Tailwind CSS for styling
+- Real-time API communication
+- Located in `demo/virtual-tryon/`
+
+### Backend (FastAPI)
+- RESTful API server
+- Uses OpenTryOn SDK (`tryon.api`)
+- Supports 4 model providers
+- Automatic image processing and storage
+- Located in project root: `api_server.py`
+
+## Quick Start
+
+### Prerequisites
+
+**Backend Requirements**:
+- Python 3.10+
+- FastAPI 0.124.0
+- Uvicorn 0.38.0
+- OpenTryOn installed
+
+**Frontend Requirements**:
+- Node.js 18+
+- npm or yarn
+
+**API Keys** (at least one required):
+- `GEMINI_API_KEY` for Nano Banana models
+- `BFL_API_KEY` for FLUX 2 models
+
+### Step 1: Set Up Environment
+
+Create a `.env` file in the project root:
+
+```bash
+# Google Gemini (for Nano Banana models)
+GEMINI_API_KEY=your_gemini_api_key
+
+# Black Forest Labs (for FLUX 2 models)
+BFL_API_KEY=your_bfl_api_key
+```
+
+### Step 2: Start the Backend
+
+From the project root:
+
+```bash
+# Activate your environment
+conda activate opentryon
+
+# Start the FastAPI server
+python api_server.py
+```
+
+The API server will start at `http://localhost:8000`
+
+**Verify it's running**:
+```bash
+curl http://localhost:8000/health
+```
+
+### Step 3: Start the Frontend
+
+In a new terminal:
+
+```bash
+cd demo/virtual-tryon
+npm install
+npm run dev
+```
+
+The frontend will start at `http://localhost:3000`
+
+### Step 4: Try It Out!
+
+1. Open `http://localhost:3000` in your browser
+2. Select a model (Nano Banana, Nano Banana Pro, FLUX 2 Pro, or FLUX 2 Flex)
+3. Upload a model/person image
+4. Upload garment images (shirts, pants, accessories, etc.)
+5. Click "Generate" and wait for the AI-generated result!
+
+## API Reference
+
+### Endpoints
+
+#### `POST /api/v1/virtual-tryon`
+
+Generate virtual try-on images.
+
+**Parameters**:
+- `model_image` (file, required): Model/person image
+- `garment_images` (files, required): One or more garment images
+- `provider` (string, optional): Model to use
+ - `nano-banana` (default) - Fast, 1024px
+ - `nano-banana-pro` - Advanced, up to 4K
+ - `flux-2-pro` - High quality
+ - `flux-2-flex` - Advanced controls
+- `prompt` (string, optional): Custom generation prompt
+- `resolution` (string, optional): For nano-banana-pro: `1K`, `2K`, or `4K`
+- `aspect_ratio` (string, optional): e.g., `16:9`, `1:1`
+- Additional FLUX 2 parameters: `width`, `height`, `seed`, `guidance`, `steps`, `safety_tolerance`
+
+**Response**:
+```json
+{
+ "success": true,
+ "image": "data:image/png;base64,...",
+ "provider": "nano-banana",
+ "num_garments": 2,
+ "saved_path": "outputs/virtual_tryon/tryon_nano-banana_20250119_143022.png",
+ "filename": "tryon_nano-banana_20250119_143022.png",
+ "model_dimensions": {"width": 838, "height": 1176}
+}
+```
+
+#### `GET /health`
+
+Health check endpoint.
+
+**Response**:
+```json
+{
+ "status": "healthy"
+}
+```
+
+## Model Comparison
+
+| Model | Speed | Quality | Max Resolution | Special Features |
+|-------|-------|---------|----------------|------------------|
+| **Nano Banana** | β‘β‘β‘ Fast | βββ Good | 1024px | Efficient, low cost |
+| **Nano Banana Pro** | β‘β‘ Medium | ββββ Great | 4K | Search grounding, high resolution |
+| **FLUX 2 Pro** | β‘ Slow | βββββ Excellent | Custom | Professional quality |
+| **FLUX 2 Flex** | β‘ Slow | βββββ Excellent | Custom | Advanced controls, fine-tuning |
+
+## Usage Examples
+
+### Using curl
+
+```bash
+curl -X POST "http://localhost:8000/api/v1/virtual-tryon" \
+ -F "model_image=@person.jpg" \
+ -F "garment_images=@shirt.jpg" \
+ -F "garment_images=@jeans.jpg" \
+ -F "provider=nano-banana-pro" \
+ -F "resolution=2K"
+```
+
+### Using Python
+
+```python
+import requests
+
+url = "http://localhost:8000/api/v1/virtual-tryon"
+
+files = {
+ 'model_image': open('person.jpg', 'rb'),
+ 'garment_images': [
+ open('shirt.jpg', 'rb'),
+ open('jeans.jpg', 'rb')
+ ]
+}
+
+data = {
+ 'provider': 'flux-2-pro'
+}
+
+response = requests.post(url, files=files, data=data)
+result = response.json()
+
+if result['success']:
+ print(f"Image saved to: {result['saved_path']}")
+```
+
+## Troubleshooting
+
+### "Failed to fetch" Error
+
+**Cause**: Frontend cannot connect to backend
+
+**Solutions**:
+1. Ensure API server is running: `python api_server.py`
+2. Check if port 8000 is available: `lsof -i :8000`
+3. Verify API URL in frontend (should be `http://localhost:8000`)
+4. Check browser console (F12) for detailed errors
+
+### API Key Errors
+
+**Error**: `No API key provided` or `Invalid API key`
+
+**Solution**:
+1. Add API keys to `.env` file in project root
+2. Restart the API server to load new environment variables
+
+### Import Errors
+
+**Error**: `ModuleNotFoundError: No module named 'tryon'`
+
+**Solution**: Install OpenTryOn in development mode:
+```bash
+pip install -e .
+```
+
+## Production Deployment
+
+### Backend (API Server)
+
+Deploy using uvicorn or gunicorn:
+
+```bash
+# Using uvicorn
+uvicorn api_server:app --host 0.0.0.0 --port 8000 --workers 4
+
+# Using gunicorn with uvicorn workers
+gunicorn api_server:app \
+ --workers 4 \
+ --worker-class uvicorn.workers.UvicornWorker \
+ --bind 0.0.0.0:8000
+```
+
+### Frontend (Next.js)
+
+Build and deploy:
+
+```bash
+cd demo/virtual-tryon
+npm run build
+npm start
+```
+
+Or deploy to Vercel:
+
+```bash
+vercel deploy
+```
+
+**Important**: Set `NEXT_PUBLIC_API_URL` environment variable to your production API URL.
+
+## Configuration
+
+### Pricing Configuration
+
+Edit `demo/virtual-tryon/pricing_config.json` to customize credit pricing for each model:
+
+```json
+{
+ "models": {
+ "nano-banana": {
+ "pricing_strategy": "flat_rate",
+ "credits_per_image": 10
+ },
+ "nano-banana-pro": {
+ "pricing_strategy": "resolution_based",
+ "credits_by_resolution": {
+ "1K": 10,
+ "2K": 20,
+ "4K": 40
+ }
+ }
+ }
+}
+```
+
+### CORS Configuration
+
+Modify `api_server.py` to add more allowed origins:
+
+```python
+app.add_middleware(
+ CORSMiddleware,
+ allow_origins=[
+ "http://localhost:3000",
+ "http://127.0.0.1:3000",
+ "https://your-production-domain.com" # Add your domain
+ ],
+ allow_credentials=True,
+ allow_methods=["*"],
+ allow_headers=["*"],
+)
+```
+
+## Learn More
+
+- **[API Reference](../api-reference/overview)** - OpenTryOn API adapters
+- **[Nano Banana](../api-reference/nano-banana)** - Nano Banana documentation
+
+## Related Demos
+
+- **[Extract Garment Demo](./extract-garment)** - Garment extraction with Gradio
+- **[Model Swap Demo](./model-swap)** - Model swapping with Gradio
+- **[Outfit Generator Demo](./outfit-generator)** - Outfit generation with Gradio
+
+
diff --git a/docs/sidebars.ts b/docs/sidebars.ts
index bc1e750..452ca4c 100644
--- a/docs/sidebars.ts
+++ b/docs/sidebars.ts
@@ -75,6 +75,7 @@ const sidebars: SidebarsConfig = {
label: 'Demos',
items: [
'demos/overview',
+ 'demos/virtual-tryon',
'demos/extract-garment',
'demos/model-swap',
'demos/outfit-generator',
diff --git a/environment.yml b/environment.yml
index 0d524c7..c63db79 100644
--- a/environment.yml
+++ b/environment.yml
@@ -65,7 +65,7 @@ dependencies:
- decorator==5.1.1
- exceptiongroup==1.1.3
- executing==1.2.0
- - fastapi==0.108.0
+ - fastapi==0.124.0
- ffmpy==0.3.3
- filelock==3.12.4
- flatbuffers==23.5.26
@@ -124,7 +124,7 @@ dependencies:
- pygments==2.16.1
- pyparsing==3.1.1
- python-dotenv==1.0.1
- - python-multipart==0.0.9
+ - python-multipart==0.0.20
- pyyaml==6.0.1
- pyzmq==25.1.1
- regex==2024.5.15
@@ -162,7 +162,7 @@ dependencies:
- typing==3.7.4.3
- typing-extensions==4.8.0
- urllib3==2.0.5
- - uvicorn==0.25.0
+ - uvicorn==0.38.0
- wcwidth==0.2.6
- websockets==11.0.3
- werkzeug==3.0.0
diff --git a/requirements.txt b/requirements.txt
index 3c1c711..9ab7781 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -12,4 +12,7 @@ boto3==1.40.64
requests>=2.31.0
PyJWT>=2.10.1
google-genai>=1.52.0
-lumaai>=1.18.1
\ No newline at end of file
+fastapi==0.124.0
+uvicorn[standard]==0.38.0
+python-multipart==0.0.20
+lumaai>=1.18.1
diff --git a/setup.py b/setup.py
index 4e3e02a..aec09a1 100644
--- a/setup.py
+++ b/setup.py
@@ -31,6 +31,9 @@
"requests>=2.31.0",
"PyJWT>=2.10.1",
"google-genai>=1.52.0",
+ "fastapi==0.124.0",
+ "uvicorn[standard]==0.38.0",
+ "python-multipart==0.0.20",
],
keywords=[
"virtual try-on",
diff --git a/tryon/api/flux2.py b/tryon/api/flux2.py
index fb07f7c..c753db0 100644
--- a/tryon/api/flux2.py
+++ b/tryon/api/flux2.py
@@ -1201,4 +1201,3 @@ def generate_multi_image(
decoded_images.append(image)
return decoded_images
-