Implement video processing module with FFmpeg conversion, OpenCV metadata extraction, and file system repository

- Added FFmpegVideoConverter for video format conversion using FFmpeg.
- Implemented NoOpVideoConverter for scenarios where FFmpeg is unavailable.
- Created OpenCVMetadataExtractor for extracting video metadata.
- Developed FileSystemVideoRepository for managing video files in the file system.
- Integrated video services with dependency injection in VideoModule.
- Established API routes for video management and streaming.
- Added request/response schemas for video metadata and streaming information.
- Implemented caching mechanisms for video streaming.
- Included error handling and logging throughout the module.

run_auto_recorder.py

@@ -0,0 +1,36 @@
+#!/usr/bin/env python3
+"""
+Service script to run the standalone auto-recorder
+
+Usage:
+    sudo python run_auto_recorder.py
+"""
+
+import sys
+import os
+from pathlib import Path
+
+# Add the project root to the path
+project_root = Path(__file__).parent
+sys.path.insert(0, str(project_root))
+
+from usda_vision_system.recording.standalone_auto_recorder import StandaloneAutoRecorder
+
+
+def main():
+    """Main entry point"""
+    print("🚀 Starting USDA Vision Auto-Recorder Service")
+    
+    # Check if running as root
+    if os.geteuid() != 0:
+        print("❌ This script must be run as root (use sudo)")
+        print("   sudo python run_auto_recorder.py")
+        sys.exit(1)
+    
+    # Create and run auto-recorder
+    recorder = StandaloneAutoRecorder()
+    recorder.run()
+
+
+if __name__ == "__main__":
+    main()