cleanup and files added

qt_app_pyside1/setup_vlm_model.py

@@ -0,0 +1,168 @@
+#!/usr/bin/env python3
+"""
+OpenVINO LLaVA Model Setup Script
+Downloads and sets up the llava-v1.6-mistral-7b-hf-int8-ov model for traffic analysis
+"""
+
+import os
+import sys
+import subprocess
+from pathlib import Path
+import shutil
+
+def install_requirements():
+    """Install required packages for OpenVINO GenAI"""
+    print("🚀 Installing OpenVINO GenAI requirements...")
+    
+    requirements = [
+        "--pre",
+        "-U", 
+        "--extra-index-url", "https://storage.openvinotoolkit.org/simple/wheels/pre-release",
+        "openvino",
+        "openvino-tokenizers", 
+        "openvino-genai"
+    ]
+    
+    try:
+        subprocess.check_call([sys.executable, "-m", "pip", "install"] + requirements)
+        print("✅ OpenVINO GenAI installed successfully")
+    except subprocess.CalledProcessError as e:
+        print(f"❌ Failed to install OpenVINO GenAI: {e}")
+        return False
+    
+    # Install huggingface_hub
+    try:
+        subprocess.check_call([sys.executable, "-m", "pip", "install", "huggingface_hub"])
+        print("✅ HuggingFace Hub installed successfully")
+    except subprocess.CalledProcessError as e:
+        print(f"❌ Failed to install HuggingFace Hub: {e}")
+        return False
+    
+    return True
+
+def download_model():
+    """Download the OpenVINO LLaVA model"""
+    print("📥 Downloading OpenVINO LLaVA model...")
+    
+    try:
+        import huggingface_hub as hf_hub
+        
+        model_id = "OpenVINO/llava-v1.6-mistral-7b-hf-int8-ov"
+        
+        # Get the project root directory
+        current_dir = Path(__file__).parent
+        model_path = current_dir / "llava_openvino_model"
+        
+        print(f"📁 Model will be saved to: {model_path}")
+        
+        # Download model
+        hf_hub.snapshot_download(model_id, local_dir=str(model_path))
+        
+        print("✅ Model downloaded successfully")
+        print(f"📁 Model location: {model_path}")
+        
+        # List downloaded files
+        files = list(model_path.glob("*"))
+        print(f"📄 Downloaded files ({len(files)}):")
+        for file in sorted(files):
+            print(f"  - {file.name}")
+        
+        return model_path
+        
+    except ImportError:
+        print("❌ HuggingFace Hub not available. Please install it first.")
+        return None
+    except Exception as e:
+        print(f"❌ Failed to download model: {e}")
+        return None
+
+def setup_model_directory():
+    """Set up the model directory structure"""
+    current_dir = Path(__file__).parent
+    model_path = current_dir / "llava_openvino_model"
+    
+    if model_path.exists():
+        print(f"✅ Model directory already exists: {model_path}")
+        return model_path
+    else:
+        print(f"❌ Model directory not found: {model_path}")
+        return None
+
+def test_model():
+    """Test the downloaded model"""
+    print("🧪 Testing the downloaded model...")
+    
+    try:
+        import openvino_genai as ov_genai
+        import numpy as np
+        from PIL import Image
+        
+        current_dir = Path(__file__).parent
+        model_path = current_dir / "llava_openvino_model"
+        
+        if not model_path.exists():
+            print("❌ Model not found for testing")
+            return False
+        
+        device = "CPU"  # Start with CPU for compatibility
+        
+        print(f"🔧 Loading model from: {model_path}")
+        pipe = ov_genai.VLMPipeline(str(model_path), device)
+        print("✅ Model loaded successfully!")
+        
+        # Create a simple test image
+        test_image = Image.new('RGB', (224, 224), color='red')
+        image_data = np.array(test_image.getdata()).reshape(1, test_image.size[1], test_image.size[0], 3).astype(np.uint8)
+        
+        import openvino as ov
+        image_tensor = ov.Tensor(image_data)
+        
+        print("🧪 Running test inference...")
+        pipe.start_chat()
+        output = pipe.generate("What color is this image?", image=image_tensor, max_new_tokens=10)
+        pipe.finish_chat()
+        
+        print(f"✅ Test successful! Model response: {output}")
+        return True
+        
+    except Exception as e:
+        print(f"❌ Model test failed: {e}")
+        return False
+
+def main():
+    """Main setup function"""
+    print("=" * 60)
+    print("🤖 OpenVINO LLaVA Model Setup for Traffic Analysis")
+    print("=" * 60)
+    
+    # Step 1: Install requirements
+    if not install_requirements():
+        print("❌ Setup failed at requirements installation")
+        return False
+    
+    print("\n" + "=" * 60)
+    
+    # Step 2: Download model
+    model_path = download_model()
+    if not model_path:
+        print("❌ Setup failed at model download")
+        return False
+    
+    print("\n" + "=" * 60)
+    
+    # Step 3: Test model
+    if not test_model():
+        print("⚠️ Model test failed, but setup might still work")
+    
+    print("\n" + "=" * 60)
+    print("✅ OpenVINO LLaVA Model Setup Complete!")
+    print(f"📁 Model location: {model_path}")
+    print("🚀 You can now use the new VLM controller")
+    print("=" * 60)
+    
+    return True
+
+if __name__ == "__main__":
+    success = main()
+    if not success:
+        sys.exit(1)