Clean push: Removed heavy files & added only latest snapshot

convert_yolo11n.py

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+#!/usr/bin/env python3
+
+import os
+import sys
+import time
+import shutil
+from pathlib import Path
+
+# Add current directory to path
+current_dir = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(current_dir)
+
+# Import the conversion function from detection_openvino.py
+from detection_openvino import convert_yolo_to_openvino
+
+def main():
+    """
+    Convert yolo11n.pt model to OpenVINO IR format.
+    Usage: python convert_yolo11n.py
+    """
+    print("\n" + "="*80)
+    print("YOLO11n Model Converter - PyTorch to OpenVINO IR")
+    print("="*80)
+      # Check if the model exists
+    model_path = Path("yolo11n.pt")
+    if not model_path.exists():
+        print(f"❌ Error: Model file {model_path} not found!")
+        print(f"   Please ensure '{model_path}' is in the current directory.")
+        return
+    
+    print(f"✅ Found model: {model_path}")
+    
+    # Check for OpenVINO and other dependencies
+    try:
+        import openvino as ov
+        print(f"✅ OpenVINO version: {ov.__version__}")
+    except ImportError:
+        print("⚠️ OpenVINO not installed. Installing now...")
+        os.system('pip install --quiet "openvino>=2024.0.0"')
+        import openvino as ov
+        print(f"✅ OpenVINO installed: {ov.__version__}")
+    
+    try:
+        from ultralytics import YOLO
+    except ImportError:
+        print("⚠️ Ultralytics not installed. Installing now...")
+        os.system('pip install --quiet "ultralytics>=8.0.0"')
+        from ultralytics import YOLO
+        print("✅ Ultralytics installed")
+    
+    # Create destination directory for the models
+    openvino_dir = Path("openvino_models")
+    if not openvino_dir.exists():
+        openvino_dir.mkdir(exist_ok=True)
+        print(f"✅ Created directory: {openvino_dir}")
+    
+    try:
+        # Convert model to OpenVINO IR format
+        print("\n📦 Converting model to OpenVINO IR format...")
+        start_time = time.time()
+        output_path = convert_yolo_to_openvino("yolo11n", half=True)
+        conversion_time = time.time() - start_time
+        
+        print(f"✅ Conversion completed in {conversion_time:.2f} seconds!")
+        print(f"✅ Output model: {output_path}")
+        
+        # Verify output files
+        if output_path and Path(output_path).exists():
+            xml_path = Path(output_path)
+            bin_path = xml_path.with_suffix('.bin')
+            xml_size = xml_path.stat().st_size / (1024 * 1024)  # in MB
+            bin_size = bin_path.stat().st_size / (1024 * 1024)  # in MB
+            
+            print(f"✅ XML file: {xml_path} ({xml_size:.2f} MB)")
+            print(f"✅ BIN file: {bin_path} ({bin_size:.2f} MB)")
+            
+            # Copy to openvino_models directory for easier access by the Qt app
+            dst_xml = openvino_dir / xml_path.name
+            dst_bin = openvino_dir / bin_path.name
+            
+            shutil.copy2(xml_path, dst_xml)
+            shutil.copy2(bin_path, dst_bin)
+            
+            print(f"✅ Copied models to: {openvino_dir}")
+            print("\n🚀 Model conversion and setup complete!")
+            print("\n📋 Instructions:")
+            print(f"   1. The model files are available at: {openvino_dir}")
+            print("   2. In the Qt app, you can now select this model from the dropdown")
+            print("   3. Use the device selection dropdown to choose between CPU and GPU")
+        else:
+            print("❌ Failed to verify output files.")
+    
+    except Exception as e:
+        print(f"❌ Error converting model: {e}")
+        import traceback
+        traceback.print_exc()
+
+if __name__ == "__main__":
+    main()