streaming part1

README.md

@@ -1,16 +1,18 @@
 # VR180 Human Matting with Det-SAM2
 
-A proof-of-concept implementation for automated human matting on VR180 3D side-by-side equirectangular video using Det-SAM2 and YOLOv8 detection.
+Automated human matting for VR180 3D side-by-side video using SAM2 and YOLOv8. Now with two processing approaches: chunked (original) and streaming (optimized).
 
 ## Features
 
 - **Automatic Person Detection**: Uses YOLOv8 to eliminate manual point selection
-- **VRAM Optimization**: Memory management for RTX 3080 (10GB) compatibility  
-- **VR180-Specific Processing**: Side-by-side stereo handling with disparity mapping
-- **Flexible Scaling**: 25%, 50%, or 100% processing resolution with AI upscaling
+- **Two Processing Modes**:
+  - **Chunked**: Original stable implementation with higher memory usage
+  - **Streaming**: New 2-3x faster implementation with constant memory usage
+- **VRAM Optimization**: Memory management for consumer GPUs (10GB+)
+- **VR180-Specific Processing**: Stereo consistency with master-slave eye processing
+- **Flexible Scaling**: 25%, 50%, or 100% processing resolution
 - **Multiple Output Formats**: Alpha channel or green screen background
-- **Chunked Processing**: Handles long videos with memory-efficient chunking
-- **Cloud GPU Ready**: Docker containerization for RunPod, Vast.ai deployment
+- **Cloud GPU Ready**: Optimized for RunPod, Vast.ai deployment
 
 ## Installation
 
@@ -48,9 +50,60 @@ output:
 
 3. **Process video:**
 ```bash
+# Chunked approach (original)
 vr180-matting config.yaml
+
+# Streaming approach (optimized, 2-3x faster)
+python -m vr180_streaming config-streaming.yaml
 ```
 
+## Processing Approaches
+
+### Streaming Approach (Recommended)
+- **Memory**: Constant ~50GB usage
+- **Speed**: 2-3x faster than chunked
+- **GPU**: 70%+ utilization
+- **Best for**: Long videos, limited RAM
+
+```bash
+python -m vr180_streaming --generate-config config-streaming.yaml
+python -m vr180_streaming config-streaming.yaml
+```
+
+### Chunked Approach (Original)
+- **Memory**: 100GB+ peak usage
+- **Speed**: Slower due to chunking overhead
+- **GPU**: Lower utilization (~2.5%)
+- **Best for**: Maximum stability, testing
+
+```bash
+vr180-matting --generate-config config-chunked.yaml
+vr180-matting config-chunked.yaml
+```
+
+See [STREAMING_VS_CHUNKED.md](STREAMING_VS_CHUNKED.md) for detailed comparison.
+
+## RunPod Quick Setup
+
+For cloud GPU processing on RunPod:
+
+```bash
+# After connecting to your RunPod instance
+git clone <repository-url>
+cd sam2e
+./runpod_setup.sh
+
+# Then use the convenience scripts:
+./run_streaming.sh   # For streaming approach (recommended)
+./run_chunked.sh     # For chunked approach
+```
+
+The setup script will:
+- Install all dependencies
+- Download SAM2 models
+- Create example configs
+- Set up convenience scripts
+
 ## Configuration
 
 ### Input Settings
@@ -172,14 +225,24 @@ VRAM Utilization: 82%
 
 ### Project Structure
 ```
-vr180_matting/
+vr180_matting/          # Chunked approach (original)
 ├── config.py          # Configuration management
 ├── detector.py        # YOLOv8 person detection
-├── sam2_wrapper.py     # SAM2 integration
-├── memory_manager.py   # VRAM optimization
-├── video_processor.py  # Base video processing
-├── vr180_processor.py  # VR180-specific processing
-└── main.py            # CLI entry point
+├── sam2_wrapper.py    # SAM2 integration
+├── memory_manager.py  # VRAM optimization
+├── video_processor.py # Base video processing
+├── vr180_processor.py # VR180-specific processing
+└── main.py           # CLI entry point
+
+vr180_streaming/       # Streaming approach (optimized)
+├── frame_reader.py   # Streaming frame reader
+├── frame_writer.py   # Direct ffmpeg pipe writer
+├── stereo_manager.py # Stereo consistency management
+├── sam2_streaming.py # SAM2 streaming integration
+├── detector.py       # YOLO person detection
+├── streaming_processor.py # Main processor
+├── config.py         # Configuration
+└── main.py          # CLI entry point
 ```
 
 ### Contributing