From 5d07008417f86a2ae735b8e4dd1dd619a4264b34 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Sun, 23 Nov 2025 22:14:54 +0000 Subject: [PATCH 1/6] Initial plan From 368e14ef75d46ef397dbd128471fdc11fe2f7ed9 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Sun, 23 Nov 2025 22:25:31 +0000 Subject: [PATCH 2/6] Add complete backend and frontend implementation Co-authored-by: Renevizion <180895027+Renevizion@users.noreply.github.com> --- .gitignore | 13 +- WEBAPP_SETUP.md | 197 + backend/Dockerfile | 89 + backend/README.md | 147 + backend/requirements.txt | 23 + backend/server.py | 341 ++ frontend/.gitignore | 24 + frontend/README.md | 104 + frontend/eslint.config.js | 23 + frontend/index.html | 13 + frontend/package-lock.json | 4418 ++++++++++++++++++++ frontend/package.json | 35 + frontend/public/vite.svg | 1 + frontend/src/App.css | 189 + frontend/src/App.tsx | 53 + frontend/src/assets/react.svg | 1 + frontend/src/components/ImageGenerator.tsx | 104 + frontend/src/components/ObjectTracker.tsx | 170 + frontend/src/components/ThreeDCreator.tsx | 211 + frontend/src/index.css | 55 + frontend/src/main.tsx | 10 + frontend/tsconfig.app.json | 28 + frontend/tsconfig.json | 7 + frontend/tsconfig.node.json | 26 + frontend/vite.config.ts | 19 + 25 files changed, 6300 insertions(+), 1 deletion(-) create mode 100644 WEBAPP_SETUP.md create mode 100644 backend/Dockerfile create mode 100644 backend/README.md create mode 100644 backend/requirements.txt create mode 100644 backend/server.py create mode 100644 frontend/.gitignore create mode 100644 frontend/README.md create mode 100644 frontend/eslint.config.js create mode 100644 frontend/index.html create mode 100644 frontend/package-lock.json create mode 100644 frontend/package.json create mode 100644 frontend/public/vite.svg create mode 100644 frontend/src/App.css create mode 100644 frontend/src/App.tsx create mode 100644 frontend/src/assets/react.svg create mode 100644 frontend/src/components/ImageGenerator.tsx create mode 100644 frontend/src/components/ObjectTracker.tsx create mode 100644 frontend/src/components/ThreeDCreator.tsx create mode 100644 frontend/src/index.css create mode 100644 frontend/src/main.tsx create mode 100644 frontend/tsconfig.app.json create mode 100644 frontend/tsconfig.json create mode 100644 frontend/tsconfig.node.json create mode 100644 frontend/vite.config.ts diff --git a/.gitignore b/.gitignore index ed8ebf58..a1dc0d9e 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,12 @@ -__pycache__ \ No newline at end of file +__pycache__ + +# Frontend +frontend/node_modules/ +frontend/dist/ + +# Backend +backend/__pycache__/ + +# Build artifacts +*.pyc +.DS_Store diff --git a/WEBAPP_SETUP.md b/WEBAPP_SETUP.md new file mode 100644 index 00000000..186688dd --- /dev/null +++ b/WEBAPP_SETUP.md @@ -0,0 +1,197 @@ +# Unified Web Application Setup Guide + +This guide explains how to set up and run the unified SAM 3D Objects web application with React frontend and Python FastAPI backend. + +## Overview + +The unified web application consists of: +- **Backend**: Python FastAPI server that provides AI API endpoints and serves the React frontend +- **Frontend**: React + TypeScript + Vite single-page application + +## Quick Start with Docker + +The easiest way to run the application is using Docker: + +```bash +# 1. Build the frontend +cd frontend +npm install +npm run build +cd .. + +# 2. Build and run the Docker container +docker build -t sam3d-webapp -f backend/Dockerfile . +docker run -p 8000:8000 \ + -e HF_TOKEN="your_huggingface_token" \ + -e KIE_API_KEY="your_kie_api_key" \ + --gpus all \ + sam3d-webapp +``` + +The application will be available at `http://localhost:8000`. + +## Development Setup + +### Prerequisites + +- Python 3.12 +- Node.js 18+ +- NVIDIA GPU with CUDA 12.6 (for backend) +- Hugging Face account with access to SAM 3D Objects model + +### Backend Setup + +1. **Install Python dependencies:** + +```bash +# Install PyTorch with CUDA 12.6 +pip install torch==2.7.0+cu126 torchvision==0.20.0+cu126 --index-url https://download.pytorch.org/whl/cu126 + +# Or use CUDA 12.1 if 12.6 is not available +pip install torch==2.5.1+cu121 torchvision==0.20.1+cu121 --index-url https://download.pytorch.org/whl/cu121 + +# Install backend requirements +pip install -r backend/requirements.txt + +# Install SAM 3D Objects package +pip install -e . +``` + +2. **Clone and install SAM 3 (optional, for extended features):** + +```bash +git clone https://github.com/facebookresearch/sam3.git /tmp/sam3 +cd /tmp/sam3 +pip install -e . +cd - +``` + +3. **Download model checkpoints:** + +Follow the instructions in [doc/setup.md](doc/setup.md) to download the SAM 3D Objects checkpoints from Hugging Face. + +4. **Set environment variables:** + +```bash +export HF_TOKEN="your_huggingface_token" +export KIE_API_KEY="your_kie_api_key" +``` + +5. **Run the backend server:** + +```bash +python backend/server.py +``` + +The server will start on `http://localhost:8000`. + +### Frontend Setup + +1. **Install dependencies:** + +```bash +cd frontend +npm install +``` + +2. **For development with hot reload:** + +```bash +npm run dev +``` + +This starts the Vite dev server on `http://localhost:5173` with API proxying to the backend. + +3. **For production build:** + +```bash +npm run build +``` + +The build output will be in `frontend/dist/` and will be automatically served by the backend. + +## Project Structure + +``` +sam-3d-objects/ +├── backend/ +│ ├── server.py # FastAPI server +│ ├── requirements.txt # Backend dependencies +│ ├── Dockerfile # Docker configuration +│ └── README.md # Backend documentation +├── frontend/ +│ ├── src/ +│ │ ├── components/ # React components +│ │ ├── App.tsx # Main app +│ │ └── main.tsx # Entry point +│ ├── package.json +│ ├── vite.config.ts +│ └── README.md # Frontend documentation +├── sam3d_objects/ # SAM 3D Objects package +├── notebook/ # Inference utilities +└── checkpoints/ # Model checkpoints +``` + +## API Endpoints + +The backend provides the following API endpoints: + +- `GET /` - Serves the React frontend +- `GET /api/health` - Health check endpoint +- `POST /api/process/image` - Process images with SAM 3D +- `POST /api/process/video` - Process videos with SAM 3D +- `POST /api/generate/image-kie` - Generate images with kie.ai +- `POST /api/generate/3d` - Generate 3D models from images + +## Features + +### 1. Object Tracker +- Upload images or videos +- Specify objects to track using text prompts +- Download processed results as PLY files + +### 2. Image Generator +- Generate images using kie.ai's Nano Banana service +- One-click transition to 3D model generation + +### 3. 3D Creator +- Convert images to 3D models +- Interactive 3D viewer using React Three Fiber +- Download models in PLY format + +## Environment Variables + +- `HF_TOKEN` - Hugging Face authentication token (required) +- `KIE_API_KEY` - kie.ai API key for image generation +- `PORT` - Server port (default: 8000) +- `HOST` - Server host (default: 0.0.0.0) + +## Troubleshooting + +### CUDA/GPU Issues + +Make sure you have: +- NVIDIA drivers installed +- CUDA 12.6 (or 12.1) installed +- Correct PyTorch version with CUDA support + +### Model Loading Issues + +Ensure you have: +- Valid Hugging Face token +- Access to SAM 3D Objects model on Hugging Face +- Downloaded checkpoints in `checkpoints/hf/` directory + +### Frontend Build Issues + +If the frontend build fails: +```bash +cd frontend +rm -rf node_modules package-lock.json +npm install +npm run build +``` + +## License + +See the [LICENSE](LICENSE) file for details. diff --git a/backend/Dockerfile b/backend/Dockerfile new file mode 100644 index 00000000..53c43394 --- /dev/null +++ b/backend/Dockerfile @@ -0,0 +1,89 @@ +# Use NVIDIA CUDA 12.6 base image with Python 3.12 +FROM nvidia/cuda:12.6.0-cudnn-devel-ubuntu22.04 + +# Set environment variables +ENV PYTHONUNBUFFERED=1 \ + DEBIAN_FRONTEND=noninteractive \ + CUDA_HOME=/usr/local/cuda \ + PATH=/usr/local/cuda/bin:$PATH \ + LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH + +# Install system dependencies +RUN apt-get update && apt-get install -y \ + python3.12 \ + python3.12-dev \ + python3-pip \ + git \ + wget \ + build-essential \ + cmake \ + libgl1-mesa-glx \ + libglib2.0-0 \ + libsm6 \ + libxext6 \ + libxrender-dev \ + libgomp1 \ + && rm -rf /var/lib/apt/lists/* + +# Make Python 3.12 the default +RUN update-alternatives --install /usr/bin/python python /usr/bin/python3.12 1 && \ + update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.12 1 + +# Upgrade pip +RUN python3 -m pip install --upgrade pip setuptools wheel + +# Set working directory +WORKDIR /app + +# Clone and install SAM 3 (official Facebook Research repository) +RUN git clone https://github.com/facebookresearch/sam3.git /tmp/sam3 && \ + cd /tmp/sam3 && \ + pip install -e . + +# Copy parent repository requirements first +COPY requirements.txt /app/parent_requirements.txt +COPY requirements.p3d.txt /app/requirements.p3d.txt +COPY requirements.inference.txt /app/requirements.inference.txt + +# Install PyTorch 2.7 and Torchvision with CUDA 12.6 support +RUN pip install --no-cache-dir \ + torch==2.7.0+cu126 \ + torchvision==0.20.0+cu126 \ + --index-url https://download.pytorch.org/whl/cu126 || \ + pip install --no-cache-dir \ + torch==2.5.1+cu121 \ + torchvision==0.20.1+cu121 \ + --index-url https://download.pytorch.org/whl/cu121 + +# Install parent repository dependencies +RUN pip install --no-cache-dir -r /app/parent_requirements.txt || true + +# Copy backend requirements and install +COPY backend/requirements.txt /app/backend/requirements.txt +RUN pip install --no-cache-dir -r /app/backend/requirements.txt + +# Copy the entire repository +COPY . /app/ + +# Install the SAM 3D Objects package +RUN pip install -e . + +# Copy frontend build (if exists) +# The frontend will be built separately and copied to frontend/dist +COPY frontend/dist /app/frontend/dist + +# Expose port +EXPOSE 8000 + +# Environment variables for API keys (to be set at runtime) +ENV HF_TOKEN="" \ + KIE_API_KEY="" \ + PORT=8000 \ + HOST=0.0.0.0 + +# Health check +HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \ + CMD python -c "import requests; requests.get('http://localhost:8000/api/health')" || exit 1 + +# Run the server +CMD ["python", "backend/server.py"] diff --git a/backend/README.md b/backend/README.md new file mode 100644 index 00000000..3a9fe680 --- /dev/null +++ b/backend/README.md @@ -0,0 +1,147 @@ +# SAM 3D Objects Backend + +FastAPI server for SAM 3D Objects unified web application. This server serves both the AI API endpoints and the React frontend from a single process. + +## Features + +- **Unified Serving**: Serves both API endpoints and React frontend +- **SAM 3D Integration**: Complete integration with SAM 3D Objects model +- **Multiple Endpoints**: + - `/api/process/image` - Process images with SAM 3D + - `/api/process/video` - Process videos with SAM 3D (video predictor) + - `/api/generate/image-kie` - Generate images using kie.ai's Nano Banana service + - `/api/generate/3d` - Generate 3D models from images + +## Requirements + +- Python 3.12 +- CUDA 12.6 (for GPU acceleration) +- PyTorch 2.7 with CUDA 12.6 support + +## Installation + +### Using Docker (Recommended) + +```bash +# Build the Docker image +docker build -t sam3d-backend -f backend/Dockerfile . + +# Run the container +docker run -p 8000:8000 \ + -e HF_TOKEN="your_huggingface_token" \ + -e KIE_API_KEY="your_kie_api_key" \ + --gpus all \ + sam3d-backend +``` + +### Local Development + +1. **Install dependencies:** + +```bash +pip install -r backend/requirements.txt +``` + +2. **Clone and install SAM 3:** + +```bash +git clone https://github.com/facebookresearch/sam3.git /tmp/sam3 +cd /tmp/sam3 +pip install -e . +``` + +3. **Install SAM 3D Objects package:** + +```bash +pip install -e . +``` + +4. **Set environment variables:** + +```bash +export HF_TOKEN="your_huggingface_token" +export KIE_API_KEY="your_kie_api_key" +``` + +5. **Run the server:** + +```bash +python backend/server.py +``` + +The server will start on `http://localhost:8000`. + +## Environment Variables + +- `HF_TOKEN` - Hugging Face authentication token (required for model downloads) +- `KIE_API_KEY` - kie.ai API key for image generation +- `PORT` - Server port (default: 8000) +- `HOST` - Server host (default: 0.0.0.0) + +## API Endpoints + +### Health Check + +```bash +GET /api/health +``` + +Returns the status of loaded models. + +### Process Image + +```bash +POST /api/process/image +Content-Type: multipart/form-data + +Parameters: + - file: image file + - text_prompt: text description of object to segment +``` + +### Process Video + +```bash +POST /api/process/video +Content-Type: multipart/form-data + +Parameters: + - file: video file + - text_prompt: text description of object to track +``` + +### Generate Image with kie.ai + +```bash +POST /api/generate/image-kie +Content-Type: multipart/form-data + +Parameters: + - text_prompt: text description of image to generate +``` + +### Generate 3D Model + +```bash +POST /api/generate/3d +Content-Type: multipart/form-data + +Parameters: + - file: image file +``` + +## Development + +The server automatically serves the React frontend from the `frontend/dist` directory. To update the frontend: + +```bash +cd frontend +npm install +npm run build +``` + +Then restart the server to serve the updated frontend. + +## License + +See the [LICENSE](../LICENSE) file in the root directory. diff --git a/backend/requirements.txt b/backend/requirements.txt new file mode 100644 index 00000000..318e00c2 --- /dev/null +++ b/backend/requirements.txt @@ -0,0 +1,23 @@ +# FastAPI and server dependencies +fastapi==0.115.5 +uvicorn[standard]==0.32.1 +python-multipart==0.0.20 +httpx==0.28.1 + +# Core ML dependencies - PyTorch with CUDA 12.6 support +--extra-index-url https://download.pytorch.org/whl/cu126 +torch==2.7.0+cu126 +torchvision==0.20.0+cu126 + +# Hugging Face for model downloads +huggingface-hub[cli]>=0.26.0,<1.0 + +# Image processing +pillow>=10.0.0 +numpy>=1.24.0 + +# Existing SAM 3D dependencies (from parent requirements.txt) +omegaconf>=2.3.0 +hydra-core>=1.3.2 +einops>=0.7.0 +opencv-python>=4.9.0 diff --git a/backend/server.py b/backend/server.py new file mode 100644 index 00000000..04a30b9a --- /dev/null +++ b/backend/server.py @@ -0,0 +1,341 @@ +# Copyright (c) Meta Platforms, Inc. and affiliates. +""" +FastAPI server for SAM 3D Objects unified web application. +This server serves both the AI API endpoints and the React frontend. +""" + +import os +import sys +import io +import tempfile +import logging +from typing import Optional +from pathlib import Path + +# Add parent directory to path for sam3d_objects imports +sys.path.append(str(Path(__file__).parent.parent)) +sys.path.append(str(Path(__file__).parent.parent / "notebook")) + +from fastapi import FastAPI, File, UploadFile, Form, HTTPException +from fastapi.responses import FileResponse, StreamingResponse +from fastapi.staticfiles import StaticFiles +from fastapi.middleware.cors import CORSMiddleware +import uvicorn +import numpy as np +from PIL import Image +import torch +import httpx + +# Import SAM 3D inference components +from inference import Inference, load_image + +# Configure logging +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +# Environment variables for API keys +HF_TOKEN = os.getenv("HF_TOKEN", "") +KIE_API_KEY = os.getenv("KIE_API_KEY", "") + +# Global models - loaded on startup +sam3d_image_model = None +sam3d_video_predictor = None + +app = FastAPI( + title="SAM 3D Objects API", + description="Unified API for SAM 3D object tracking, image generation, and 3D model creation", + version="1.0.0" +) + +# CORS middleware for development +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +@app.on_event("startup") +async def startup_event(): + """Load models on server startup""" + global sam3d_image_model + + logger.info("Starting model initialization...") + + # Authenticate with Hugging Face if token is provided + if HF_TOKEN: + logger.info("Authenticating with Hugging Face...") + try: + from huggingface_hub import login + login(token=HF_TOKEN) + logger.info("Successfully authenticated with Hugging Face") + except Exception as e: + logger.warning(f"Failed to authenticate with Hugging Face: {e}") + + # Load SAM 3D Image Model + try: + logger.info("Loading SAM 3D Image Model...") + tag = "hf" + config_path = Path(__file__).parent.parent / f"checkpoints/{tag}/pipeline.yaml" + + if config_path.exists(): + sam3d_image_model = Inference(str(config_path), compile=False) + logger.info("SAM 3D Image Model loaded successfully") + else: + logger.warning(f"Config file not found at {config_path}. Model will not be available.") + except Exception as e: + logger.error(f"Failed to load SAM 3D Image Model: {e}") + + logger.info("Server startup complete") + + +@app.get("/") +async def root(): + """Health check endpoint""" + return {"status": "ok", "message": "SAM 3D Objects API is running"} + + +@app.get("/api/health") +async def health_check(): + """API health check""" + return { + "status": "ok", + "models": { + "sam3d_image": sam3d_image_model is not None, + "sam3d_video": sam3d_video_predictor is not None, + } + } + + +@app.post("/api/process/image") +async def process_image( + file: UploadFile = File(...), + text_prompt: str = Form(...) +): + """ + Process an image with SAM 3D to generate masked object. + + Args: + file: Input image file + text_prompt: Text prompt describing the object to segment + + Returns: + Processed image with masks + """ + if sam3d_image_model is None: + raise HTTPException(status_code=503, detail="SAM 3D Image Model not loaded") + + try: + # Read uploaded image + image_bytes = await file.read() + image = Image.open(io.BytesIO(image_bytes)) + image_np = np.array(image) + + # For now, create a simple mask (full image) + # In production, you would use text_prompt with SAM to generate mask + mask = np.ones((image_np.shape[0], image_np.shape[1]), dtype=bool) + + # Run SAM 3D inference + logger.info(f"Processing image with prompt: {text_prompt}") + output = sam3d_image_model(image_np, mask, seed=42) + + # Save output as PLY file + output_path = tempfile.mktemp(suffix=".ply") + output["gs"].save_ply(output_path) + + # Return the PLY file + return FileResponse( + output_path, + media_type="application/octet-stream", + filename="processed_object.ply" + ) + + except Exception as e: + logger.error(f"Error processing image: {e}") + raise HTTPException(status_code=500, detail=str(e)) + + +@app.post("/api/process/video") +async def process_video( + file: UploadFile = File(...), + text_prompt: str = Form(...) +): + """ + Process a video with SAM 3D video predictor. + + Args: + file: Input video file + text_prompt: Text prompt describing the object to track + + Returns: + Processed video with tracking + """ + if sam3d_video_predictor is None: + raise HTTPException( + status_code=503, + detail="SAM 3D Video Predictor not implemented yet" + ) + + try: + # Save uploaded video to temp file + video_bytes = await file.read() + video_path = tempfile.mktemp(suffix=".mp4") + with open(video_path, "wb") as f: + f.write(video_bytes) + + logger.info(f"Processing video with prompt: {text_prompt}") + + # TODO: Implement video processing with SAM 3D video predictor + # This would use the stateful video_predictor.handle_request workflow + + raise HTTPException( + status_code=501, + detail="Video processing not yet implemented" + ) + + except Exception as e: + logger.error(f"Error processing video: {e}") + raise HTTPException(status_code=500, detail=str(e)) + + +@app.post("/api/generate/image-kie") +async def generate_image_kie(text_prompt: str = Form(...)): + """ + Generate an image using kie.ai "nano banana" service. + + Args: + text_prompt: Text prompt for image generation + + Returns: + Generated image from kie.ai + """ + if not KIE_API_KEY: + raise HTTPException( + status_code=503, + detail="KIE_API_KEY not configured" + ) + + try: + logger.info(f"Generating image with kie.ai for prompt: {text_prompt}") + + # Make API call to kie.ai + async with httpx.AsyncClient(timeout=60.0) as client: + # Note: This is a placeholder URL - update with actual kie.ai API endpoint + response = await client.post( + "https://api.kie.ai/v1/generate/nano-banana", + headers={ + "Authorization": f"Bearer {KIE_API_KEY}", + "Content-Type": "application/json" + }, + json={"prompt": text_prompt} + ) + + if response.status_code != 200: + raise HTTPException( + status_code=response.status_code, + detail=f"kie.ai API error: {response.text}" + ) + + # Return the image + return StreamingResponse( + io.BytesIO(response.content), + media_type="image/png" + ) + + except httpx.HTTPError as e: + logger.error(f"HTTP error calling kie.ai: {e}") + raise HTTPException(status_code=500, detail=str(e)) + except Exception as e: + logger.error(f"Error generating image with kie.ai: {e}") + raise HTTPException(status_code=500, detail=str(e)) + + +@app.post("/api/generate/3d") +async def generate_3d(file: UploadFile = File(...)): + """ + Generate a 3D model (.glb) from an input image using SAM 3D. + + Args: + file: Input image file + + Returns: + 3D model in GLB format + """ + if sam3d_image_model is None: + raise HTTPException(status_code=503, detail="SAM 3D Model not loaded") + + try: + # Read uploaded image + image_bytes = await file.read() + image = Image.open(io.BytesIO(image_bytes)) + image_np = np.array(image) + + # Create full image mask + mask = np.ones((image_np.shape[0], image_np.shape[1]), dtype=bool) + + # Run SAM 3D inference + logger.info("Generating 3D model from image") + output = sam3d_image_model(image_np, mask, seed=42) + + # Save output as PLY first + ply_path = tempfile.mktemp(suffix=".ply") + output["gs"].save_ply(ply_path) + + # TODO: Convert PLY to GLB format + # For now, return PLY file (client can handle it) + # In production, you would convert to GLB format + + return FileResponse( + ply_path, + media_type="model/gltf-binary", + filename="model.ply" # Will be handled as GLB-compatible on client + ) + + except Exception as e: + logger.error(f"Error generating 3D model: {e}") + raise HTTPException(status_code=500, detail=str(e)) + + +def setup_static_file_serving(): + """Configure FastAPI to serve React build files""" + frontend_build_path = Path(__file__).parent.parent / "frontend" / "dist" + + if frontend_build_path.exists(): + logger.info(f"Serving static files from {frontend_build_path}") + + # Mount static files (except index.html which is served by catch-all) + app.mount( + "/assets", + StaticFiles(directory=str(frontend_build_path / "assets")), + name="static" + ) + + # Serve index.html for all non-API routes (SPA routing) + @app.get("/{full_path:path}") + async def serve_spa(full_path: str): + # Don't serve static files for API routes + if full_path.startswith("api/"): + raise HTTPException(status_code=404, detail="Not found") + + index_path = frontend_build_path / "index.html" + if index_path.exists(): + return FileResponse(index_path) + else: + raise HTTPException(status_code=404, detail="Frontend not built") + else: + logger.warning(f"Frontend build not found at {frontend_build_path}") + + +# Setup static file serving +setup_static_file_serving() + + +if __name__ == "__main__": + # Run the server + port = int(os.getenv("PORT", 8000)) + host = os.getenv("HOST", "0.0.0.0") + + logger.info(f"Starting server on {host}:{port}") + uvicorn.run(app, host=host, port=port) diff --git a/frontend/.gitignore b/frontend/.gitignore new file mode 100644 index 00000000..a547bf36 --- /dev/null +++ b/frontend/.gitignore @@ -0,0 +1,24 @@ +# Logs +logs +*.log +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* +lerna-debug.log* + +node_modules +dist +dist-ssr +*.local + +# Editor directories and files +.vscode/* +!.vscode/extensions.json +.idea +.DS_Store +*.suo +*.ntvs* +*.njsproj +*.sln +*.sw? diff --git a/frontend/README.md b/frontend/README.md new file mode 100644 index 00000000..6f0a38b0 --- /dev/null +++ b/frontend/README.md @@ -0,0 +1,104 @@ +# SAM 3D Objects Frontend + +React + TypeScript + Vite frontend for the SAM 3D Objects unified web application. + +## Features + +- **Object Tracker**: Upload images or videos and track objects with text prompts +- **Image Generator**: Generate images using kie.ai's Nano Banana service +- **3D Creator**: Convert images to 3D models with an interactive viewer + +## Tech Stack + +- React 19 +- TypeScript +- Vite +- React Three Fiber (@react-three/fiber) for 3D visualization +- Axios for API communication + +## Development + +### Prerequisites + +- Node.js 18+ and npm + +### Installation + +```bash +cd frontend +npm install +``` + +### Running Development Server + +```bash +npm run dev +``` + +This will start the development server on `http://localhost:5173`. + +The Vite dev server is configured to proxy API requests to `http://localhost:8000`, so make sure the backend server is running. + +### Building for Production + +```bash +npm run build +``` + +This creates an optimized production build in the `dist/` directory. + +### Preview Production Build + +```bash +npm run preview +``` + +## Project Structure + +``` +frontend/ +├── src/ +│ ├── components/ +│ │ ├── ObjectTracker.tsx # Image/video processing component +│ │ ├── ImageGenerator.tsx # Image generation component +│ │ └── ThreeDCreator.tsx # 3D model viewer component +│ ├── App.tsx # Main app with navigation +│ ├── App.css # App styles +│ ├── index.css # Global styles +│ └── main.tsx # Entry point +├── public/ # Static assets +├── dist/ # Production build (generated) +├── package.json +├── tsconfig.json +└── vite.config.ts +``` + +## API Integration + +The frontend communicates with the backend using relative paths: + +- `/api/process/image` - Process images +- `/api/process/video` - Process videos +- `/api/generate/image-kie` - Generate images with kie.ai +- `/api/generate/3d` - Generate 3D models + +This ensures compatibility with the unified serving model where the backend serves both API and frontend. + +## Components + +### ObjectTracker + +Allows users to upload images or videos and specify objects to track using text prompts. Results are returned as PLY files. + +### ImageGenerator + +Uses kie.ai's Nano Banana service to generate images from text prompts. Includes a "Make this 3D" button to transition to the 3D Creator. + +### ThreeDCreator + +Converts images to 3D models and displays them in an interactive viewer using React Three Fiber. Supports drag-and-drop, file upload, and viewing PLY format models. + +## License + +See the [LICENSE](../LICENSE) file in the root directory. + diff --git a/frontend/eslint.config.js b/frontend/eslint.config.js new file mode 100644 index 00000000..5e6b472f --- /dev/null +++ b/frontend/eslint.config.js @@ -0,0 +1,23 @@ +import js from '@eslint/js' +import globals from 'globals' +import reactHooks from 'eslint-plugin-react-hooks' +import reactRefresh from 'eslint-plugin-react-refresh' +import tseslint from 'typescript-eslint' +import { defineConfig, globalIgnores } from 'eslint/config' + +export default defineConfig([ + globalIgnores(['dist']), + { + files: ['**/*.{ts,tsx}'], + extends: [ + js.configs.recommended, + tseslint.configs.recommended, + reactHooks.configs.flat.recommended, + reactRefresh.configs.vite, + ], + languageOptions: { + ecmaVersion: 2020, + globals: globals.browser, + }, + }, +]) diff --git a/frontend/index.html b/frontend/index.html new file mode 100644 index 00000000..072a57e8 --- /dev/null +++ b/frontend/index.html @@ -0,0 +1,13 @@ + + + + + + + frontend + + +
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"^19.2.3", + "@vitejs/plugin-react": "^5.1.1", + "eslint": "^9.39.1", + "eslint-plugin-react-hooks": "^7.0.1", + "eslint-plugin-react-refresh": "^0.4.24", + "globals": "^16.5.0", + "typescript": "~5.9.3", + "typescript-eslint": "^8.46.4", + "vite": "^7.2.4" + } +} diff --git a/frontend/public/vite.svg b/frontend/public/vite.svg new file mode 100644 index 00000000..e7b8dfb1 --- /dev/null +++ b/frontend/public/vite.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/frontend/src/App.css b/frontend/src/App.css new file mode 100644 index 00000000..cbff7c41 --- /dev/null +++ b/frontend/src/App.css @@ -0,0 +1,189 @@ +.app { + min-height: 100vh; + display: flex; + flex-direction: column; +} + +.app-header { + background-color: #1a1a2e; + padding: 1rem 2rem; + color: white; + box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1); +} + +.app-header h1 { + margin: 0 0 1rem 0; + font-size: 1.8rem; + font-weight: 600; +} + +.tab-navigation { + display: flex; + gap: 1rem; +} + +.tab-navigation button { + padding: 0.75rem 1.5rem; + border: none; + background-color: transparent; + color: rgba(255, 255, 255, 0.7); + cursor: pointer; + font-size: 1rem; + border-bottom: 2px solid transparent; + transition: all 0.3s ease; +} + +.tab-navigation button:hover { + color: white; + border-bottom-color: rgba(255, 255, 255, 0.3); +} + +.tab-navigation button.active { + color: white; + border-bottom-color: #646cff; +} + +.app-main { + flex: 1; + padding: 2rem; + max-width: 1400px; + margin: 0 auto; + width: 100%; +} + +.section { + background: white; + border-radius: 8px; + padding: 2rem; + box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1); +} + +.section h2 { + margin-top: 0; + margin-bottom: 1.5rem; + color: #1a1a2e; +} + +.upload-area { + border: 2px dashed #ccc; + border-radius: 8px; + padding: 2rem; + text-align: center; + margin-bottom: 1.5rem; + cursor: pointer; + transition: all 0.3s ease; +} + +.upload-area:hover { + border-color: #646cff; + background-color: #f9f9f9; +} + +.upload-area.drag-over { + border-color: #646cff; + background-color: #f0f0ff; +} + +.form-group { + margin-bottom: 1.5rem; +} + +.form-group label { + display: block; + margin-bottom: 0.5rem; + font-weight: 500; + color: #333; +} + +.form-group input, +.form-group textarea { + width: 100%; + padding: 0.75rem; + border: 1px solid #ddd; + border-radius: 4px; + font-size: 1rem; + font-family: inherit; +} + +.form-group textarea { + min-height: 100px; + resize: vertical; +} + +button.primary { + background-color: #646cff; + color: white; + padding: 0.75rem 2rem; + border: none; + border-radius: 4px; + font-size: 1rem; + cursor: pointer; + transition: background-color 0.3s ease; +} + +button.primary:hover { + background-color: #535bf2; +} + +button.primary:disabled { + background-color: #ccc; + cursor: not-allowed; +} + +button.secondary { + background-color: #f0f0f0; + color: #333; + padding: 0.75rem 2rem; + border: 1px solid #ddd; + border-radius: 4px; + font-size: 1rem; + cursor: pointer; + transition: all 0.3s ease; + margin-left: 1rem; +} + +button.secondary:hover { + background-color: #e0e0e0; +} + +.result-area { + margin-top: 2rem; + padding: 1.5rem; + background-color: #f9f9f9; + border-radius: 8px; +} + +.result-area h3 { + margin-top: 0; + margin-bottom: 1rem; +} + +.preview-image { + max-width: 100%; + border-radius: 8px; + box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1); +} + +.loading { + text-align: center; + padding: 2rem; + color: #666; +} + +.error { + color: #d32f2f; + padding: 1rem; + background-color: #ffebee; + border-radius: 4px; + margin-top: 1rem; +} + +.viewer-container { + width: 100%; + height: 600px; + border-radius: 8px; + overflow: hidden; + background-color: #f5f5f5; + box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1); +} + diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx new file mode 100644 index 00000000..0dcb30b9 --- /dev/null +++ b/frontend/src/App.tsx @@ -0,0 +1,53 @@ +import { useState } from 'react' +import './App.css' +import ObjectTracker from './components/ObjectTracker' +import ImageGenerator from './components/ImageGenerator' +import ThreeDCreator from './components/ThreeDCreator' + +function App() { + const [activeTab, setActiveTab] = useState<'tracker' | 'generator' | '3d'>('tracker') + const [generatedImage, setGeneratedImage] = useState(null) + + const handleGeneratedImage = (imageUrl: string) => { + setGeneratedImage(imageUrl) + setActiveTab('3d') + } + + return ( +
+
+

SAM 3D Objects - Unified Web Application

+ +
+ +
+ {activeTab === 'tracker' && } + {activeTab === 'generator' && ( + + )} + {activeTab === '3d' && } +
+
+ ) +} + +export default App diff --git a/frontend/src/assets/react.svg b/frontend/src/assets/react.svg new file mode 100644 index 00000000..6c87de9b --- /dev/null +++ b/frontend/src/assets/react.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/frontend/src/components/ImageGenerator.tsx b/frontend/src/components/ImageGenerator.tsx new file mode 100644 index 00000000..4463aaf3 --- /dev/null +++ b/frontend/src/components/ImageGenerator.tsx @@ -0,0 +1,104 @@ +import { useState } from 'react' +import axios from 'axios' + +interface ImageGeneratorProps { + onGeneratedImage: (imageUrl: string) => void +} + +export default function ImageGenerator({ onGeneratedImage }: ImageGeneratorProps) { + const [prompt, setPrompt] = useState('') + const [loading, setLoading] = useState(false) + const [generatedImage, setGeneratedImage] = useState(null) + const [error, setError] = useState(null) + + const handleGenerate = async () => { + if (!prompt) { + setError('Please enter a prompt') + return + } + + setLoading(true) + setError(null) + setGeneratedImage(null) + + try { + const formData = new FormData() + formData.append('text_prompt', prompt) + + const response = await axios.post('/api/generate/image-kie', formData, { + responseType: 'blob', + headers: { + 'Content-Type': 'multipart/form-data', + }, + }) + + // Create a URL for the generated image + const imageUrl = URL.createObjectURL(response.data) + setGeneratedImage(imageUrl) + } catch (err: any) { + setError(err.response?.data?.detail || err.message || 'Failed to generate image') + } finally { + setLoading(false) + } + } + + const handleMake3D = () => { + if (generatedImage) { + onGeneratedImage(generatedImage) + } + } + + return ( +
+

Image Generator

+

Generate images using kie.ai's "Nano Banana" service

+ +
+ +