cluster4npu/tests/quick_test_deployment.py

#!/usr/bin/env python3
"""
Quick test script for YOLOv5 pipeline deployment using fixed configuration
"""
import sys
import os

# Add paths
sys.path.append(os.path.join(os.path.dirname(__file__), 'ui', 'dialogs'))
sys.path.append(os.path.join(os.path.dirname(__file__), 'core', 'functions'))

def test_mflow_loading():
    """Test loading and parsing the fixed .mflow file"""
    import json
    
    mflow_files = [
        'multi_series_example.mflow',
        'multi_series_yolov5_fixed.mflow',
        'test.mflow'
    ]
    
    print("=" * 60)
    print("Testing .mflow Configuration Loading")
    print("=" * 60)
    
    for mflow_file in mflow_files:
        if os.path.exists(mflow_file):
            print(f"\n📄 Loading {mflow_file}:")
            try:
                with open(mflow_file, 'r') as f:
                    data = json.load(f)
                
                # Check for postprocess nodes
                postprocess_nodes = [
                    node for node in data.get('nodes', [])
                    if node.get('type') == 'ExactPostprocessNode'
                ]
                
                if postprocess_nodes:
                    for node in postprocess_nodes:
                        props = node.get('properties', {})
                        postprocess_type = props.get('postprocess_type', 'NOT SET')
                        confidence_threshold = props.get('confidence_threshold', 'NOT SET')
                        class_names = props.get('class_names', 'NOT SET')
                        
                        print(f"   ✓ Found PostprocessNode: {node.get('name', 'Unnamed')}")
                        print(f"     - Type: {postprocess_type}")
                        print(f"     - Threshold: {confidence_threshold}")
                        print(f"     - Classes: {len(class_names.split(',')) if isinstance(class_names, str) else 'N/A'} classes")
                        
                        if postprocess_type == 'yolo_v5':
                            print(f"     ✅ Correctly configured for YOLOv5")
                        else:
                            print(f"     ❌ Still using: {postprocess_type}")
                else:
                    print(f"   ⚠ No ExactPostprocessNode found")
                    
            except Exception as e:
                print(f"   ❌ Error loading file: {e}")
        else:
            print(f"\n📄 {mflow_file}: File not found")

def test_deployment_direct():
    """Test deployment using the deployment dialog directly"""
    try:
        from deployment import DeploymentDialog
        from PyQt5.QtWidgets import QApplication
        
        print(f"\n" + "=" * 60)
        print("Testing Direct Pipeline Deployment")
        print("=" * 60)
        
        # Load the fixed configuration
        import json
        config_file = 'multi_series_yolov5_fixed.mflow'
        
        if not os.path.exists(config_file):
            print(f"❌ Configuration file not found: {config_file}")
            return
        
        with open(config_file, 'r') as f:
            pipeline_data = json.load(f)
        
        print(f"✓ Loaded configuration: {pipeline_data.get('project_name', 'Unknown')}")
        print(f"✓ Found {len(pipeline_data.get('nodes', []))} nodes")
        
        # Create minimal Qt app for testing
        app = QApplication.instance()
        if app is None:
            app = QApplication(sys.argv)
        
        # Create deployment dialog
        dialog = DeploymentDialog(pipeline_data)
        print(f"✓ Created deployment dialog")
        
        # Test analysis
        print(f"🔍 Testing pipeline analysis...")
        
        try:
            from core.functions.mflow_converter import MFlowConverter
            converter = MFlowConverter()
            config = converter._convert_mflow_to_config(pipeline_data)
            
            print(f"✓ Pipeline conversion successful")
            print(f"  - Pipeline name: {config.pipeline_name}")
            print(f"  - Total stages: {len(config.stage_configs)}")
            
            # Check stage configurations
            for i, stage_config in enumerate(config.stage_configs, 1):
                print(f"  Stage {i}: {stage_config.stage_id}")
                if hasattr(stage_config, 'postprocessor_options') and stage_config.postprocessor_options:
                    print(f"    - Postprocess type: {stage_config.postprocessor_options.postprocess_type.value}")
                    print(f"    - Threshold: {stage_config.postprocessor_options.threshold}")
                    print(f"    - Classes: {len(stage_config.postprocessor_options.class_names)}")
                    
                    if stage_config.postprocessor_options.postprocess_type.value == 'yolo_v5':
                        print(f"    ✅ YOLOv5 postprocessing configured correctly")
                    else:
                        print(f"    ❌ Postprocessing type: {stage_config.postprocessor_options.postprocess_type.value}")
            
        except Exception as e:
            print(f"❌ Pipeline conversion failed: {e}")
            import traceback
            traceback.print_exc()
        
    except ImportError as e:
        print(f"❌ Cannot import deployment components: {e}")
        print(f"   This is expected if running outside the full application")
    except Exception as e:
        print(f"❌ Direct deployment test failed: {e}")
        import traceback
        traceback.print_exc()

def show_fix_summary():
    """Show summary of the fixes applied"""
    print(f"\n" + "=" * 60)
    print("FIX SUMMARY")
    print("=" * 60)
    
    print(f"\n🔧 Applied Fixes:")
    print(f"1. ✅ Fixed dashboard.py postprocess property loading")
    print(f"   - Added missing 'postprocess_type' property")
    print(f"   - Added all missing postprocess properties")
    print(f"   - Location: ui/windows/dashboard.py:1203-1213")
    
    print(f"\n2. ✅ Enhanced YOLOv5 postprocessing in Multidongle.py")
    print(f"   - Improved _process_yolo_generic method")
    print(f"   - Added proper NMS (Non-Maximum Suppression)")
    print(f"   - Enhanced live view display")
    
    print(f"\n3. ✅ Updated .mflow configurations")
    print(f"   - multi_series_example.mflow: enable_postprocessing = true")
    print(f"   - multi_series_yolov5_fixed.mflow: Complete YOLOv5 setup")
    print(f"   - Added ExactPostprocessNode with yolo_v5 type")
    
    print(f"\n🎯 Expected Results After Fix:")
    print(f"   - ❌ 'No Fire (Prob: -0.39)' → ✅ 'person detected (Conf: 0.85)'")
    print(f"   - ❌ Negative probabilities → ✅ Positive probabilities (0.0-1.0)")
    print(f"   - ❌ No bounding boxes → ✅ Colorful bounding boxes with labels")
    print(f"   - ❌ Fire detection classes → ✅ COCO 80 classes (person, car, etc.)")
    
    print(f"\n💡 Usage Instructions:")
    print(f"   1. Run: python main.py")
    print(f"   2. Login to the dashboard")
    print(f"   3. Load: multi_series_yolov5_fixed.mflow")
    print(f"   4. Deploy the pipeline")
    print(f"   5. Check Live View tab for enhanced bounding boxes")

def main():
    print("Quick YOLOv5 Deployment Test")
    print("=" * 60)
    
    # Test configuration loading
    test_mflow_loading()
    
    # Test direct deployment (if possible)
    test_deployment_direct()
    
    # Show fix summary
    show_fix_summary()
    
    print(f"\n🎉 Quick test completed!")
    print(f"   Now try running: python main.py")
    print(f"   And load: multi_series_yolov5_fixed.mflow")

if __name__ == "__main__":
    main()