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Aplikasi web untuk deteksi kelapa sawit menggunakan AI YOLO11 dengan estimasi produksi briket karbon.
Frontend: Nuxt 3, Bootstrap 5, Chart.js
Backend: Flask, YOLO5, OpenCV, PyTorch
- Node.js 18+
- Python 3.9+
- ffmpeg
Frontend:
npm installBackend:
cd backend
python -m venv venv
venv\Scripts\activate # Windows
# source venv/bin/activate # Linux/Mac
pip install -r requirements.txtBuat file .env:
NUXT_PUBLIC_API_URL=http://localhost:5000npm run dev:allAkses: http://localhost:3000
backend/requirements.txt:
Flask==3.0.0
Flask-CORS==4.0.0
ultralytics==8.1.0
opencv-python==4.8.1.78
torch==2.1.0
torchvision==0.16.0
Pillow==10.1.0
numpy==1.24.3
ffmpeg-python==0.2.0
python-dotenv==1.0.0- Run
npm run dev:all - Buka
http://localhost:3000 - Upload gambar/video kelapa sawit
- Klik Mulai Deteksi
- Lihat hasil deteksi dan estimasi briket
npm run dev # Frontend only
npm run dev:backend # Backend only
npm run dev:all # Run both (Frontend + Backend)
npm run build # Build for production
npm run preview # Preview production buildTambahkan scripts:
{
"scripts": {
"dev": "nuxt dev",
"dev:backend": "cd backend && python app.py",
"dev:all": "concurrently \"npm run dev\" \"npm run dev:backend\"",
"build": "nuxt build",
"preview": "nuxt preview"
},
"devDependencies": {
"concurrently": "^8.2.2"
}
}Install concurrently:
npm install -D concurrentlyapp-sawit/
├── components/ # Vue components
├── pages/ # Nuxt pages
├── public/ # Static files
├── backend/ # Flask API
│ ├── app.py
│ └── requirements.txt
├── .env
├── package.json
└── README.md
Backend error:
cd backend
pip install -r requirements.txt
python app.pyChart.js error:
npm install chart.js vue-chartjs=======
Project YOLO Sawit
a3ab37bb7c551654eb75257b7bfb204a55ca9c8e