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Main detection script\n├── requirements.txt     # Dependencies\n└── README.md            # Documentation\n```\n\n---\n\n## ⚙️ Setup Instructions\n\n### 1️⃣ Create \u0026 Activate Virtual Environment\n```bash\npython -m venv .venv\n.venv\\Scripts\\activate       # On Windows\nsource .venv/bin/activate    # On Linux/macOS\n```\n\n### 2️⃣ Install Dependencies\n\nEnsure your **PyTorch** build supports CUDA:\n```bash\npip uninstall torch torchvision torchaudio -y\npip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121\n```\n\nThen install the rest:\n```bash\npip install -r requirements.txt\n```\n\n---\n\n## ⚡ Run the Detector\n\n### ▶️ Webcam Mode\n```bash\npython main.py\n```\n\n### ▶️ Video File Mode\n(If you add a `--source` parameter in code)\n```bash\npython main.py --source path/to/video.mp4\n```\n\nPress **ESC** to close the window.\n\n---\n\n## 🧠 How It Works\n\n1. Loads the **latest YOLO model** (`yolov8l.pt` or higher) on your **GPU**.  \n2. Detects all visible objects per frame.  \n3. Automatically **ignores humans (person class)**.  \n4. Draws **color-coded boxes** for all other products/objects with confidence scores.\n\nExample output:\n```\nbottle 0.89\ncell phone 0.91\nlaptop 0.84\n```\n\n---\n\n## 🧰 Requirements\n\n```\nultralytics\u003e=8.3.223\nopencv-python\ntorch\u003e=2.3.0\ntorchvision\ntorchaudio\n```\n\n---\n\n## 🖥️ Tested Hardware\n\n| Component | Example |\n|------------|----------|\n| GPU | NVIDIA RTX 3060 12GB |\n| CUDA | 12.1 |\n| Python | 3.12 |\n| OS | Windows 10 / 11 |\n\n---\n\n## 🧩 Model Options\n\n| Model | Size | Speed | Accuracy |\n|--------|------|--------|-----------|\n| `yolov8n.pt` | Nano | ⚡⚡⚡ | Basic |\n| `yolov8s.pt` | Small | ⚡⚡ | Medium |\n| `yolov8m.pt` | Medium | ⚡ | Balanced |\n| `yolov8l.pt` | Large | ⚡ | High Accuracy |\n| `yolov8x.pt` | X-Large | 🚀 | Best Accuracy |\n\nFor **segmentation masks**, use `yolov8n-seg.pt`.\n\n---\n\n## 🔮 Stay Advanced — Upgrade to YOLOv10\n\nUltralytics recently released **YOLOv10**, offering better accuracy and faster performance.  \nTo upgrade:\n```bash\npip install -U ultralytics\n```\n\nThen in your code, replace:\n```python\nmodel = YOLO(\"yolov8l.pt\")\n```\nwith:\n```python\nmodel = YOLO(\"yolov10l.pt\")\n```\n\nYOLOv10 is fully backward-compatible and uses the same API — your project will continue working with no code changes.\n\n---\n\n## 🧪 Tips\n\n- Adjust confidence threshold in `main.py` (e.g., `if box.conf \u003e 0.4:`).  \n- For faster FPS, reduce webcam resolution or use `yolov8n.pt`.  \n- Add custom product filters easily if you want to exclude certain categories.  \n\n---\nCreated with ❤️ using **Python**, **Ultralytics YOLO**, and **OpenCV**,  \n\npowered by **NVIDIA GPU**.\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnothing-dot-exe%2Fadvanced-product-detection-gpu-powered","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnothing-dot-exe%2Fadvanced-product-detection-gpu-powered","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnothing-dot-exe%2Fadvanced-product-detection-gpu-powered/lists"}