fix sam2 hopefully

test_installation.py

@@ -5,12 +5,19 @@ import sys
 import torch
 import cv2
 import numpy as np
+from pathlib import Path
+import os
 
 print("VR180 Matting Installation Test")
 print("=" * 50)
 
+# Track all issues
+issues = []
+
 # Check Python version
 print(f"Python version: {sys.version}")
+if sys.version_info < (3, 8):
+    issues.append("Python 3.8+ required")
 
 # Check PyTorch and CUDA
 print(f"\nPyTorch version: {torch.__version__}")
@@ -19,16 +26,29 @@ if torch.cuda.is_available():
     print(f"CUDA version: {torch.version.cuda}")
     print(f"GPU: {torch.cuda.get_device_name(0)}")
     print(f"GPU Memory: {torch.cuda.get_device_properties(0).total_memory / 1024**3:.1f} GB")
+else:
+    issues.append("No CUDA GPU detected - will run slowly on CPU")
 
 # Check OpenCV
 print(f"\nOpenCV version: {cv2.__version__}")
 
 # Test imports
+print("\n🔍 Testing imports...")
 try:
     from ultralytics import YOLO
-    print("\n✅ YOLO import successful")
+    print("✅ YOLO import successful")
+    
+    # Check if YOLO models exist
+    yolo_models = ["yolov8n.pt", "yolov8s.pt", "yolov8m.pt"]
+    available_yolo = [m for m in yolo_models if Path(m).exists()]
+    if available_yolo:
+        print(f"   Found YOLO models: {', '.join(available_yolo)}")
+    else:
+        issues.append("No YOLO models found - will download on first run")
+        
 except ImportError as e:
-    print(f"\n❌ YOLO import failed: {e}")
+    print(f"❌ YOLO import failed: {e}")
+    issues.append("Ultralytics YOLO not installed")
 
 try:
     from sam2.build_sam import build_sam2_video_predictor
@@ -36,6 +56,7 @@ try:
 except ImportError as e:
     print(f"❌ SAM2 import failed: {e}")
     print("   Install with: pip install git+https://github.com/facebookresearch/segment-anything-2.git")
+    issues.append("SAM2 not installed")
 
 try:
     from vr180_matting.config import VR180Config
@@ -46,6 +67,102 @@ try:
 except ImportError as e:
     print(f"❌ VR180 matting import failed: {e}")
     print("   Make sure to run: pip install -e .")
+    issues.append("VR180 matting package not installed")
+
+# Check SAM2 models
+print("\n🔍 Checking SAM2 models...")
+models_dir = Path("models")
+sam2_models = {
+    "sam2_hiera_large.pt": "Original SAM2 Large",
+    "sam2.1_hiera_large.pt": "SAM2.1 Large (recommended)",
+    "sam2_hiera_base.pt": "SAM2 Base",
+    "sam2.1_hiera_base.pt": "SAM2.1 Base"
+}
+
+found_models = []
+for model_file, model_name in sam2_models.items():
+    model_path = models_dir / model_file
+    if model_path.exists():
+        size_mb = model_path.stat().st_size / (1024 * 1024)
+        print(f"✅ {model_name}: {model_file} ({size_mb:.1f} MB)")
+        found_models.append(model_file)
+    
+if not found_models:
+    print("❌ No SAM2 models found!")
+    issues.append("No SAM2 models found - run setup script or download manually")
+else:
+    print(f"\n💡 Recommended config for best model found:")
+    if "sam2.1_hiera_large.pt" in found_models:
+        print("   sam2_model_cfg: 'sam2.1_hiera_l'")
+        print("   sam2_checkpoint: 'models/sam2.1_hiera_large.pt'")
+    elif "sam2_hiera_large.pt" in found_models:
+        print("   sam2_model_cfg: 'sam2_hiera_l'")
+        print("   sam2_checkpoint: 'models/sam2_hiera_large.pt'")
+
+# Check SAM2 configs
+print("\n🔍 Checking SAM2 config files...")
+configs_dir = Path("sam2_configs")
+if configs_dir.exists():
+    config_files = list(configs_dir.glob("*.yaml"))
+    if config_files:
+        print(f"✅ Found {len(config_files)} SAM2 config files")
+    else:
+        print("❌ No SAM2 config files found")
+        issues.append("SAM2 config files missing - may cause model loading errors")
+else:
+    print("❌ sam2_configs directory not found")
+    issues.append("SAM2 configs directory missing")
+
+# Test model loading if possible
+if not any("SAM2 not installed" in issue for issue in issues):
+    print("\n🧪 Testing SAM2 model loading...")
+    try:
+        # Try to load the default model config
+        from vr180_matting.config import VR180Config
+        config = VR180Config(
+            input=type('obj', (object,), {'video_path': 'test.mp4'})(),
+            processing=type('obj', (object,), {'scale_factor': 0.5, 'chunk_size': 900, 'overlap_frames': 60})(),
+            detection=type('obj', (object,), {'confidence_threshold': 0.7, 'model': 'yolov8n'})(),
+            matting=type('obj', (object,), {
+                'use_disparity_mapping': True,
+                'memory_offload': True,
+                'fp16': True,
+                'sam2_model_cfg': 'sam2.1_hiera_l' if Path('models/sam2.1_hiera_large.pt').exists() else 'sam2_hiera_l',
+                'sam2_checkpoint': 'models/sam2.1_hiera_large.pt' if Path('models/sam2.1_hiera_large.pt').exists() else 'models/sam2_hiera_large.pt'
+            })(),
+            output=type('obj', (object,), {'path': 'output/', 'format': 'alpha', 'background_color': [0, 255, 0], 'maintain_sbs': True})(),
+            hardware=type('obj', (object,), {'device': 'cuda' if torch.cuda.is_available() else 'cpu', 'max_vram_gb': 10})()
+        )
+        
+        # Try loading just the model config check
+        model_path = Path(config.matting.sam2_checkpoint)
+        if model_path.exists():
+            print(f"✅ Found checkpoint: {model_path}")
+            # Quick check of checkpoint structure
+            checkpoint = torch.load(model_path, map_location='cpu')
+            if 'model' in checkpoint:
+                print(f"   Model has {len(checkpoint['model'])} parameters")
+        else:
+            print(f"❌ Checkpoint not found: {model_path}")
+            issues.append(f"SAM2 checkpoint missing: {model_path}")
+            
+    except Exception as e:
+        print(f"⚠️  Could not test model loading: {e}")
+
+# Check ffmpeg
+print("\n🔍 Checking ffmpeg...")
+import subprocess
+try:
+    result = subprocess.run(['ffmpeg', '-version'], capture_output=True, text=True)
+    if result.returncode == 0:
+        version_line = result.stdout.split('\n')[0]
+        print(f"✅ {version_line}")
+    else:
+        print("❌ ffmpeg error")
+        issues.append("ffmpeg not working properly")
+except FileNotFoundError:
+    print("❌ ffmpeg not found")
+    issues.append("ffmpeg not installed - required for video processing")
 
 # Memory check
 if torch.cuda.is_available():
@@ -54,11 +171,29 @@ if torch.cuda.is_available():
     print(f"   Reserved:  {torch.cuda.memory_reserved() / 1024**3:.2f} GB")
     print(f"   Free:      {(torch.cuda.get_device_properties(0).total_memory - torch.cuda.memory_reserved()) / 1024**3:.2f} GB")
 
+# Check example config
+print("\n🔍 Checking configuration files...")
+example_configs = ["config_example.yaml", "config_runpod.yaml", "config.yaml"]
+found_configs = [c for c in example_configs if Path(c).exists()]
+if found_configs:
+    print(f"✅ Found configs: {', '.join(found_configs)}")
+else:
+    print("❌ No config files found")
+    issues.append("No configuration files found - generate with: vr180-matting --generate-config config.yaml")
+
+# Summary
 print("\n" + "=" * 50)
-print("Installation test complete!")
-print("\nNext steps:")
-print("1. If any imports failed, install missing dependencies")
-print("2. Download SAM2 model weights if needed")
-print("3. Run: vr180-matting --generate-config config.yaml")
-print("4. Edit config.yaml with your video path")
-print("5. Run: vr180-matting config.yaml")
+if issues:
+    print("❌ Issues found:")
+    for i, issue in enumerate(issues, 1):
+        print(f"   {i}. {issue}")
+    print("\n📋 To fix issues:")
+    print("   1. Run: ./runpod_setup.sh")
+    print("   2. Make sure SAM2 is installed: pip install git+https://github.com/facebookresearch/segment-anything-2.git")
+    print("   3. Install package: pip install -e .")
+else:
+    print("✅ All checks passed! Ready to process videos.")
+    print("\n📋 Quick start:")
+    print("   1. Copy example config: cp config_runpod.yaml config.yaml")
+    print("   2. Edit config.yaml with your video path")
+    print("   3. Run: vr180-matting config.yaml")