Delete validation_examples

validation_examples/all_epochs_metrics.json

@@ -1,26 +0,0 @@
-{
-  "2": {
-    "epoch": 2,
-    "num_samples": 5,
-    "psnr": {
-      "mean": 8.42457007356943,
-      "std": 2.0490775580319913,
-      "min": 5.580395004140195,
-      "max": 10.949018083124695
-    },
-    "ssim": {
-      "mean": 0.19272444483279338,
-      "std": 0.06094948968742925,
-      "min": 0.13446655088904022,
-      "max": 0.27528859925476507
-    },
-    "lpips": {
-      "mean": 0.7371994853019714,
-      "std": 0.040124533781707016
-    },
-    "clip_similarity": {
-      "mean": 0.29375,
-      "std": 0.019739128114254125
-    }
-  }
-}

validation_examples/epoch_2/metrics.json

@@ -1,24 +0,0 @@
-{
-  "epoch": 2,
-  "num_samples": 5,
-  "psnr": {
-    "mean": 8.42457007356943,
-    "std": 2.0490775580319913,
-    "min": 5.580395004140195,
-    "max": 10.949018083124695
-  },
-  "ssim": {
-    "mean": 0.19272444483279338,
-    "std": 0.06094948968742925,
-    "min": 0.13446655088904022,
-    "max": 0.27528859925476507
-  },
-  "lpips": {
-    "mean": 0.7371994853019714,
-    "std": 0.040124533781707016
-  },
-  "clip_similarity": {
-    "mean": 0.29375,
-    "std": 0.019739128114254125
-  }
-}

validation_examples/test_epoch_validation.py

@@ -1,134 +0,0 @@
-#!/usr/bin/env python3
-"""
-Quick test for validate_epochs.py
-
-Tests basic functionality without full validation:
-1. Import check
-2. Config loading
-3. Dataset loading
-4. Checkpoint detection
-"""
-
-import sys
-from pathlib import Path
-
-print("=" * 70)
-print("🧪 Testing Epoch Validation Pipeline")
-print("=" * 70)
-
-# Test 1: Import check
-print("\n[1/4] Testing imports...")
-try:
-    sys.path.insert(0, str(Path(__file__).parent))
-    sys.path.insert(0, str(Path(__file__).parent / "src"))
-    
-    from validate_epochs import EpochValidator
-    from configs.config import get_default_config
-    from datasets.sketchy_dataset import SketchyDataset
-    print("   ✅ All imports successful")
-except Exception as e:
-    print(f"   ❌ Import failed: {e}")
-    sys.exit(1)
-
-# Test 2: Config loading
-print("\n[2/4] Testing config...")
-try:
-    config = get_default_config()
-    print(f"   ✅ Config loaded")
-    print(f"   - Image size: {config['data'].image_size}")
-    print(f"   - Pretrained model: {config['model'].pretrained_model_name}")
-except Exception as e:
-    print(f"   ❌ Config failed: {e}")
-    sys.exit(1)
-
-# Test 3: Dataset check
-print("\n[3/4] Testing dataset...")
-try:
-    import os
-    dataset_root = "/workspace/sketchy"
-    
-    if not os.path.exists(dataset_root):
-        print(f"   ⚠️  Dataset not found at {dataset_root}")
-        dataset_root = "/root/Dual-Stage-Controllable-Diffusion-with-Adaptive-Modality-Fusion/sketchy"
-    
-    if os.path.exists(dataset_root):
-        dataset = SketchyDataset(
-            root_dir=dataset_root,
-            split='test',
-            image_size=config['data'].image_size,
-            augment=False
-        )
-        print(f"   ✅ Dataset loaded: {len(dataset)} samples")
-    else:
-        print(f"   ⚠️  Dataset not available (will be needed for actual validation)")
-except Exception as e:
-    print(f"   ⚠️  Dataset check skipped: {e}")
-
-# Test 4: Checkpoint detection
-print("\n[4/4] Testing checkpoint detection...")
-try:
-    # Check local checkpoints
-    local_checkpoint_dir = Path("/root/checkpoints/stage1")
-    if local_checkpoint_dir.exists():
-        checkpoints = list(local_checkpoint_dir.glob("epoch_*.pt"))
-        if checkpoints:
-            print(f"   ✅ Found {len(checkpoints)} local checkpoints:")
-            for cp in sorted(checkpoints)[:5]:  # Show first 5
-                print(f"      - {cp.name}")
-            if len(checkpoints) > 5:
-                print(f"      ... and {len(checkpoints) - 5} more")
-        else:
-            print(f"   ⚠️  No epoch checkpoints found locally")
-    else:
-        print(f"   ⚠️  Local checkpoint directory not found")
-    
-    # Try HuggingFace detection
-    print("\n   Testing HuggingFace checkpoint detection...")
-    try:
-        from huggingface_hub import list_repo_files
-        
-        # Replace with actual repo ID
-        hf_repo_id = "DrRORAL/ragaf-diffusion-checkpoints"
-        
-        files = list_repo_files(hf_repo_id)
-        epoch_files = [f for f in files if 'epoch' in f.lower() and f.endswith('.pt')]
-        
-        if epoch_files:
-            print(f"   ✅ Found {len(epoch_files)} checkpoint files on HuggingFace:")
-            for f in sorted(epoch_files)[:5]:
-                print(f"      - {f}")
-            if len(epoch_files) > 5:
-                print(f"      ... and {len(epoch_files) - 5} more")
-        else:
-            print(f"   ⚠️  No epoch checkpoints found on HuggingFace")
-            
-    except Exception as e:
-        print(f"   ⚠️  HuggingFace check skipped: {e}")
-        
-except Exception as e:
-    print(f"   ⚠️  Checkpoint detection failed: {e}")
-
-# Summary
-print("\n" + "=" * 70)
-print("📊 Test Summary")
-print("=" * 70)
-print("""
-✅ Basic functionality working!
-
-To run actual validation:
-  python validate_epochs.py --num_samples 20
-
-Options:
-  --hf_repo         HuggingFace repo ID (default: DrRORAL/ragaf-diffusion-checkpoints)
-  --dataset_root    Path to Sketchy dataset (default: /workspace/sketchy)
-  --epochs          Specific epochs to validate (default: all)
-  --num_samples     Samples per epoch (default: 50)
-  --output_dir      Output directory (default: validation_results)
-  --guidance_scale  Guidance scale (default: 2.5)
-
-Quick start:
-  python validate_epochs.py --num_samples 10  # Quick test
-
-See docs/EPOCH_VALIDATION_GUIDE.md for complete documentation.
-""")
-print("=" * 70)

validation_examples/test_validation_quick.py

@@ -1,122 +0,0 @@
-#!/usr/bin/env python3
-"""
-Quick validation test - simplified version for debugging
-"""
-
-import torch
-import sys
-from pathlib import Path
-
-sys.path.insert(0, str(Path(__file__).parent))
-sys.path.insert(0, str(Path(__file__).parent / "src"))
-
-from models.stage1_diffusion import Stage1SketchGuidedDiffusion, Stage1DiffusionPipeline
-from datasets.sketchy_dataset import SketchyDataset
-from configs.config import get_default_config
-
-print("=" * 80)
-print("Quick Validation Test")
-print("=" * 80)
-
-# Load config
-print("\n1. Loading config...")
-config = get_default_config()
-print(f"   Dataset root: {config['data'].sketchy_root}")
-print(f"   Image size: {config['data'].image_size}")
-
-# Load dataset
-print("\n2. Loading dataset...")
-dataset = SketchyDataset(
-    root_dir=config['data'].sketchy_root,
-    split='test',
-    image_size=config['data'].image_size,
-    augment=False
-)
-print(f"   Total samples: {len(dataset)}")
-
-# Test loading one sample
-print("\n3. Loading one sample...")
-data = dataset[0]
-print(f"   Sketch shape: {data['sketch'].shape}")
-print(f"   Photo shape: {data['photo'].shape}")
-print(f"   Prompt: {data['text_prompt']}")
-print(f"   Category: {data['category']}")
-
-# Load model
-print("\n4. Loading model...")
-device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-print(f"   Device: {device}")
-
-model_config = config['model']
-print(f"   Model name: {model_config.pretrained_model_name}")
-print(f"   Sketch encoder channels: {model_config.sketch_encoder_channels}")
-
-try:
-    model = Stage1SketchGuidedDiffusion(
-        pretrained_model_name=model_config.pretrained_model_name,
-        sketch_encoder_channels=model_config.sketch_encoder_channels,
-        freeze_base_unet=model_config.freeze_stage1_unet,
-        use_lora=model_config.use_lora,
-        lora_rank=model_config.lora_rank
-    ).to(device)
-    print("   ✅ Model created successfully")
-except Exception as e:
-    print(f"   ❌ Model creation failed: {e}")
-    sys.exit(1)
-
-# Load checkpoint
-print("\n5. Loading checkpoint...")
-checkpoint_path = "/root/checkpoints/stage1/final.pt"
-try:
-    checkpoint = torch.load(checkpoint_path, map_location=device)
-    model.load_state_dict(checkpoint['model_state_dict'])
-    model.eval()
-    print(f"   ✅ Checkpoint loaded")
-except Exception as e:
-    print(f"   ❌ Checkpoint loading failed: {e}")
-    sys.exit(1)
-
-# Create pipeline
-print("\n6. Creating pipeline...")
-try:
-    pipeline = Stage1DiffusionPipeline(
-        model=model,
-        num_inference_steps=20,  # Reduced for testing
-        guidance_scale=2.5,
-        device=device
-    )
-    print("   ✅ Pipeline created")
-except Exception as e:
-    print(f"   ❌ Pipeline creation failed: {e}")
-    sys.exit(1)
-
-# Test generation
-print("\n7. Testing generation...")
-sketch = data['sketch'].unsqueeze(0)  # Add batch dimension
-prompt = data['text_prompt']
-img_size = config['data'].image_size  # Use configured image size
-
-print(f"   Sketch input shape: {sketch.shape}")
-print(f"   Prompt: {prompt}")
-print(f"   Image size: {img_size}")
-
-try:
-    with torch.no_grad():
-        generated = pipeline.generate(
-            sketch=sketch,
-            text_prompt=prompt,
-            height=img_size,  # Use dataset image size
-            width=img_size,   # Use dataset image size
-            seed=42
-        )
-    print(f"   ✅ Generation successful!")
-    print(f"   Generated shape: {generated.shape}")
-except Exception as e:
-    print(f"   ❌ Generation failed: {e}")
-    import traceback
-    traceback.print_exc()
-    sys.exit(1)
-
-print("\n" + "=" * 80)
-print("✅ All tests passed!")
-print("=" * 80)

validation_examples/upload_summary.json

@@ -1,40 +0,0 @@
-{
-  "timestamp": "2026-03-12T21:51:05.217893",
-  "repo_id": "DrRORAL/ragaf-diffusion-checkpoints",
-  "subfolder": "validation_examples",
-  "local_source": "/root/Dual-Stage-Controllable-Diffusion-with-Adaptive-Modality-Fusion/test_validation",
-  "files": [
-    {
-      "path": "all_epochs_metrics.json",
-      "size_mb": 0.0
-    },
-    {
-      "path": "epoch_2/metrics.json",
-      "size_mb": 0.0
-    },
-    {
-      "path": "epoch_2/sample_0000.png",
-      "size_mb": 1.07
-    },
-    {
-      "path": "metrics_across_epochs.png",
-      "size_mb": 0.31
-    },
-    {
-      "path": "test_epoch_validation.py",
-      "size_mb": 0.0
-    },
-    {
-      "path": "test_validation_quick.py",
-      "size_mb": 0.0
-    },
-    {
-      "path": "upload_summary.json",
-      "size_mb": 0.0
-    },
-    {
-      "path": "validation_report.html",
-      "size_mb": 0.0
-    }
-  ]
-}

validation_examples/validation_report.html

@@ -1,62 +0,0 @@
-
-        <!DOCTYPE html>
-        <html>
-        <head>
-            <title>Stage-1 Validation Report</title>
-            <style>
-                body { font-family: Arial, sans-serif; margin: 40px; background: #f5f5f5; }
-                h1 { color: #333; border-bottom: 3px solid #4CAF50; padding-bottom: 10px; }
-                h2 { color: #555; margin-top: 30px; }
-                table { border-collapse: collapse; width: 100%; margin: 20px 0; background: white; }
-                th, td { border: 1px solid #ddd; padding: 12px; text-align: left; }
-                th { background-color: #4CAF50; color: white; }
-                tr:nth-child(even) { background-color: #f2f2f2; }
-                .best { background-color: #90EE90 !important; font-weight: bold; }
-                .metric-card { background: white; padding: 20px; margin: 20px 0; 
-                              border-radius: 8px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); }
-                .images { display: flex; flex-wrap: wrap; gap: 10px; }
-                .images img { max-width: 300px; border: 1px solid #ddd; border-radius: 4px; }
-            </style>
-        </head>
-        <body>
-            <h1>🎨 Stage-1 Sketch-Guided Diffusion - Validation Report</h1>
-            <div class="metric-card">
-                <h2>📊 Metrics Across Epochs</h2>
-                <table>
-                    <tr>
-                        <th>Epoch</th>
-                        <th>PSNR (dB)</th>
-                        <th>SSIM</th>
-                        <th>LPIPS</th>
-                        <th>FID</th>
-                        <th>CLIP Sim</th>
-                        <th>Samples</th>
-                    </tr>
-        
-                    <tr>
-                        <td><strong>Epoch 2</strong></td>
-                        <td class="best">8.42 ± 2.05</td>
-                        <td class="best">0.1927 ± 0.0609</td>
-                        <td>0.7371994853019714</td>
-                        <td>N/A</td>
-                        <td>0.29375</td>
-                        <td>5</td>
-                    </tr>
-            
-                </table>
-            </div>
-            
-            <div class="metric-card">
-                <h2>📈 Visualization</h2>
-                <img src="metrics_across_epochs.png" style="max-width: 100%;">
-            </div>
-            
-            <div class="metric-card">
-                <h2>🎯 Recommendations</h2>
-                <ul>
-        <li>⚠️ SSIM is low (&lt;0.5). Consider training for more epochs.</li>
-                </ul>
-            </div>
-        </body>
-        </html>
-