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+# Video Object Segmentation with SAM2 - Setup Guide
+
+## Quick Start (macOS/Linux)
+
+### 1. Install uv
+
+```bash
+pip install uv
+```
+
+### 2. Create virtual environment and install dependencies
+
+```bash
+uv venv .venv
+source .venv/bin/activate
+uv pip install -r requirements.txt
+```
+
+### 3. Install SAM manually
+
+```bash
+# Clone the segment-anything repository
+git clone https://github.com/facebookresearch/segment-anything.git
+cd segment-anything
+
+# Install SAM in development mode
+pip install -e .
+
+# Download the ViT-B model checkpoint (recommended)
+wget https://dl.fbaipublicfiles.com/segment_anything/sam_vit_b_01ec64.pth
+mv sam_vit_b_01ec64.pth ..
+cd ..
+
+# Clean up
+rm -rf segment-anything
+```
+
+### 4. Create directories
+
+```bash
+mkdir -p uploads segmented
+```
+
+### 5. Run the application
+
+```bash
+python app.py
+```
+
+## Project Structure
+
+```
+video-segmentation-sam2/
+├── app.py                  # Main Flask application
+├── requirements.txt        # Python dependencies
+├── .env                    # Configuration
+├── templates/
+│   └── index.html          # Web interface
+├── uploads/                # Uploaded videos (created automatically)
+├── segmented/              # Processed videos (created automatically)
+└── sam_vit_b_01ec64.pth    # SAM2 model checkpoint
+```
+
+## Configuration
+
+Edit `.env` file to customize:
+
+```env
+FLASK_ENV=development
+UPLOAD_FOLDER=uploads
+SEGMENTED_FOLDER=segmented
+ALLOWED_EXTENSIONS=.mp4,.avi,.mov,.mkv
+SAM_MODEL_SIZE=vit_b  # Options: vit_b, vit_l, vit_h
+```
+
+## Troubleshooting
+
+### NumPy compatibility issues
+
+If you see errors about NumPy 2.x compatibility:
+```
+A module that was compiled using NumPy 1.x cannot be run in NumPy 2.3.5
+```
+
+**Solution:** The requirements.txt already specifies `numpy<2.0` to avoid this issue. Make sure you:
+1. Delete your virtual environment: `rm -rf .venv`
+2. Recreate it: `uv venv .venv`
+3. Reinstall dependencies: `uv pip install -r requirements.txt`
+
+### SAM2 not found
+
+If you get `ImportError: SAM2 is not installed`, make sure you:
+1. Cloned the segment-anything repository
+2. Ran `pip install -e .` from the segment-anything directory
+3. Have the checkpoint file in the root directory
+
+### CUDA not available
+
+If you don't have a GPU, the app will use CPU (slower). For better performance:
+1. Install CUDA toolkit
+2. Install cuDNN
+3. Make sure `torch.cuda.is_available()` returns True
+
+### Port already in use
+
+If port 5000 is busy:
+1. Change the port in `app.py` (last line)
+2. Or kill the process using port 5000:
+   ```bash
+   lsof -i :5000
+   kill -9 <PID>
+   ```
+
+## Model Options
+
+| Model | Checkpoint File | Size | Speed | Accuracy | Best For |
+|-------|----------------|------|-------|----------|----------|
+| **ViT-B** | `sam_vit_b_01ec64.pth` | Smallest | Fastest | Good | Testing, quick results, lower-end hardware |
+| **ViT-L** | `sam_vit_l_0b3195.pth` | Medium | Medium | Better | Balanced performance/quality |
+| **ViT-H** | `sam_vit_h_4b8939.pth` | Largest | Slowest | Best | High-quality results, powerful hardware |
+
+To change models:
+1. Download the desired checkpoint
+2. Update `SAM_MODEL_SIZE` in `.env`
+3. Restart the application
+
+## Using the Application
+
+1. **Upload**: Select a video file (MP4, AVI, MOV, MKV)
+2. **Preview**: See the first frame of your video
+3. **Select**: Click on the object you want to segment
+4. **Process**: Click "Segment Object" to start processing
+5. **Download**: Get your segmented video
+
+## Performance Tips
+
+- **GPU Acceleration**: SAM2 runs much faster with CUDA
+- **Video Length**: Shorter videos process faster
+- **Resolution**: Lower resolutions are quicker to process
+- **Points**: 3-5 well-placed points usually work best