fix sam2 hopefully

This commit is contained in:
2025-07-26 08:03:37 -07:00
parent 1bec8113de
commit eeed9ee578
6 changed files with 187 additions and 17 deletions

View File

@@ -14,7 +14,7 @@ matting:
use_disparity_mapping: true
memory_offload: true
fp16: true
sam2_model_cfg: "sam2_hiera_l.yaml"
sam2_model_cfg: "sam2_hiera_l"
sam2_checkpoint: "models/sam2_hiera_large.pt"
output:

View File

@@ -14,8 +14,8 @@ matting:
use_disparity_mapping: true
memory_offload: false # A40 has enough VRAM
fp16: true
sam2_model_cfg: "sam2_hiera_l.yaml"
sam2_checkpoint: "models/sam2_hiera_large.pt"
sam2_model_cfg: "sam2.1_hiera_l"
sam2_checkpoint: "models/sam2.1_hiera_large.pt"
output:
path: "/workspace/output/matted_video.mp4"

View File

@@ -29,12 +29,35 @@ mkdir -p models
# Download YOLOv8 models
python -c "from ultralytics import YOLO; YOLO('yolov8n.pt'); YOLO('yolov8m.pt')"
# Download SAM2 checkpoint
# Download SAM2 checkpoints
cd models
echo "📥 Downloading SAM2 models..."
# Try different SAM2 model versions
if [ ! -f "sam2_hiera_large.pt" ]; then
echo "Downloading SAM2 model weights..."
wget -q --show-progress https://dl.fbaipublicfiles.com/segment_anything_2/sam2_hiera_large.pt
echo "Trying SAM2 checkpoint version 1..."
wget -q --show-progress https://dl.fbaipublicfiles.com/segment_anything_2/sam2_hiera_large.pt || true
fi
if [ ! -f "sam2.1_hiera_large.pt" ]; then
echo "Trying SAM2.1 checkpoint (latest)..."
wget -q --show-progress https://dl.fbaipublicfiles.com/segment_anything_2/092824/sam2.1_hiera_large.pt || true
fi
# Download SAM2 config files
cd ..
mkdir -p sam2_configs
cd sam2_configs
echo "📥 Downloading SAM2 configuration files..."
wget -q --show-progress https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/sam2_configs/sam2_hiera_b+.yaml
wget -q --show-progress https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/sam2_configs/sam2_hiera_l.yaml
wget -q --show-progress https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/sam2_configs/sam2_hiera_s.yaml
wget -q --show-progress https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/sam2_configs/sam2_hiera_t.yaml
wget -q --show-progress https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/sam2_configs/sam2.1_hiera_b+.yaml
wget -q --show-progress https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/sam2_configs/sam2.1_hiera_l.yaml
wget -q --show-progress https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/sam2_configs/sam2.1_hiera_s.yaml
wget -q --show-progress https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/sam2_configs/sam2.1_hiera_t.yaml
cd ..
# Create working directories
@@ -45,6 +68,18 @@ echo ""
echo "🧪 Testing installation..."
python test_installation.py
# Check which SAM2 model is available
echo ""
echo "📊 SAM2 Models available:"
if [ -f "models/sam2_hiera_large.pt" ]; then
echo " ✅ sam2_hiera_large.pt"
echo " Use in config: sam2_checkpoint: 'models/sam2_hiera_large.pt'"
fi
if [ -f "models/sam2.1_hiera_large.pt" ]; then
echo " ✅ sam2.1_hiera_large.pt (recommended)"
echo " Use in config: sam2_checkpoint: 'models/sam2.1_hiera_large.pt'"
fi
echo ""
echo "✅ Setup complete!"
echo ""

View File

@@ -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")

View File

@@ -27,7 +27,7 @@ class MattingConfig:
use_disparity_mapping: bool = True
memory_offload: bool = True
fp16: bool = True
sam2_model_cfg: str = "sam2_hiera_l.yaml"
sam2_model_cfg: str = "sam2_hiera_l"
sam2_checkpoint: str = "sam2_hiera_large.pt"

View File

@@ -19,7 +19,7 @@ class SAM2VideoMatting:
"""SAM2-based video matting with memory optimization"""
def __init__(self,
model_cfg: str = "sam2_hiera_l.yaml",
model_cfg: str = "sam2_hiera_l",
checkpoint_path: str = "sam2_hiera_large.pt",
device: str = "cuda",
memory_offload: bool = True,