diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml new file mode 100644 index 0000000..161fb7c --- /dev/null +++ b/.github/workflows/lint.yml @@ -0,0 +1,52 @@ +name: Code Quality (Lint) + +on: + pull_request: + branches: [main, master, develop] + push: + branches: [main, master, develop] + +jobs: + lint: + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.10" + cache: 'pip' + + - name: Install linting tools + run: | + python -m pip install --upgrade pip + pip install ruff black isort + + - name: Run Ruff (linter) + run: | + ruff check . --output-format=github + continue-on-error: true + + - name: Run Black (formatter check) + run: | + black --check --diff . + continue-on-error: true + + - name: Run isort (import sorting check) + run: | + isort --check-only --diff . + continue-on-error: true + + - name: Lint summary + if: always() + run: | + echo "## Code Quality Results" >> $GITHUB_STEP_SUMMARY + echo "" >> $GITHUB_STEP_SUMMARY + echo "✅ Ruff linting completed" >> $GITHUB_STEP_SUMMARY + echo "✅ Black formatting check completed" >> $GITHUB_STEP_SUMMARY + echo "✅ isort import sorting check completed" >> $GITHUB_STEP_SUMMARY + echo "" >> $GITHUB_STEP_SUMMARY + echo "**Note**: Linting errors are not blocking CI (continue-on-error: true)" >> $GITHUB_STEP_SUMMARY diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml new file mode 100644 index 0000000..dd63747 --- /dev/null +++ b/.github/workflows/publish.yml @@ -0,0 +1,29 @@ +name: Publish to Comfy registry + +on: + workflow_dispatch: + push: + branches: + - main + - master + paths: + - "pyproject.toml" + +permissions: + issues: write + +jobs: + publish-node: + name: Publish Custom Node to registry + runs-on: ubuntu-latest + if: ${{ github.repository_owner == 'PozzettiAndrea' }} + steps: + - name: Check out code + uses: actions/checkout@v4 + with: + submodules: true + - name: Publish Custom Node + uses: Comfy-Org/publish-node-action@v1 + with: + ## Add your own personal access token to your Github Repository secrets and reference it here. + personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} diff --git a/.github/workflows/test-real-models.yml b/.github/workflows/test-real-models.yml new file mode 100644 index 0000000..7f7a8ed --- /dev/null +++ b/.github/workflows/test-real-models.yml @@ -0,0 +1,80 @@ +name: Real Model Integration Tests + +on: + # Run on schedule (weekly, every Monday at 3 AM UTC) + schedule: + - cron: '0 3 * * 1' + + # Allow manual trigger + workflow_dispatch: + + # Optionally run on specific branches (commented out to save resources) + # push: + # branches: [main] + +jobs: + test-real-models: + runs-on: ubuntu-latest + timeout-minutes: 60 # Real model tests can take longer + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.10" + cache: 'pip' + + - name: Install system dependencies + run: | + sudo apt-get update + sudo apt-get install -y libgl1-mesa-glx libglib2.0-0 + + - name: Install Python dependencies + run: | + python -m pip install --upgrade pip + pip install pytest pytest-cov pytest-mock pytest-asyncio + pip install -r requirements.txt + pip install -r requirements-dev.txt + + - name: Create model cache directory + run: | + mkdir -p ~/.cache/huggingface + + - name: Cache models + uses: actions/cache@v4 + with: + path: ~/.cache/huggingface + key: ${{ runner.os }}-huggingface-models-${{ hashFiles('tests/integration_real/*.py') }} + restore-keys: | + ${{ runner.os }}-huggingface-models- + + - name: Run real model tests + run: | + pytest tests/integration_real/ -v -m real_model --tb=short + env: + PYTHONPATH: ${{ github.workspace }} + HF_HUB_DISABLE_TELEMETRY: 1 + + - name: Test summary + if: always() + run: | + echo "## Real Model Test Results" >> $GITHUB_STEP_SUMMARY + echo "" >> $GITHUB_STEP_SUMMARY + echo "✅ GroundingDINO SwinT tests completed" >> $GITHUB_STEP_SUMMARY + echo "✅ Florence-2 Base tests completed" >> $GITHUB_STEP_SUMMARY + echo "✅ OWLv2 Base tests completed" >> $GITHUB_STEP_SUMMARY + echo "✅ YOLO-World v2 S tests completed" >> $GITHUB_STEP_SUMMARY + echo "" >> $GITHUB_STEP_SUMMARY + echo "**Note**: SAM2 tests were skipped as requested" >> $GITHUB_STEP_SUMMARY + + - name: Upload test artifacts + if: failure() + uses: actions/upload-artifact@v4 + with: + name: test-failures + path: | + pytest-results/ + *.log diff --git a/.github/workflows/test-unit.yml b/.github/workflows/test-unit.yml new file mode 100644 index 0000000..aa2ef20 --- /dev/null +++ b/.github/workflows/test-unit.yml @@ -0,0 +1,66 @@ +name: Unit and Integration Tests + +on: + push: + branches: [main, master, develop] + pull_request: + branches: [main, master, develop] + +jobs: + test: + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ["3.10", "3.11"] + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v5 + with: + python-version: ${{ matrix.python-version }} + cache: 'pip' + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install pytest pytest-cov pytest-mock pytest-asyncio + pip install -r requirements.txt + pip install -r requirements-dev.txt + + - name: Run unit tests + run: | + pytest tests/unit/ -v --cov=nodes --cov-report=xml --cov-report=term-missing + env: + PYTHONPATH: ${{ github.workspace }} + + - name: Run mocked integration tests + run: | + pytest tests/integration/ -v --cov=nodes --cov-append --cov-report=xml --cov-report=term-missing + env: + PYTHONPATH: ${{ github.workspace }} + + - name: Run workflow validation tests + run: | + pytest tests/workflows/ -v + env: + PYTHONPATH: ${{ github.workspace }} + + - name: Upload coverage reports + uses: codecov/codecov-action@v4 + if: matrix.python-version == '3.10' + with: + file: ./coverage.xml + flags: unittests + name: codecov-umbrella + fail_ci_if_error: false + + - name: Test summary + if: always() + run: | + echo "## Test Results" >> $GITHUB_STEP_SUMMARY + echo "✅ Unit tests completed" >> $GITHUB_STEP_SUMMARY + echo "✅ Mocked integration tests completed" >> $GITHUB_STEP_SUMMARY + echo "✅ Workflow validation tests completed" >> $GITHUB_STEP_SUMMARY diff --git a/__init__.py b/__init__.py index 57d5fef..47bf15b 100644 --- a/__init__.py +++ b/__init__.py @@ -4,20 +4,32 @@ Supports GroundingDINO, MM-GroundingDINO, OWLv2, Florence-2, and YOLO-World Now includes SAM2 segmentation nodes """ -from .grounding_init import init +# Only run initialization and imports when loaded by ComfyUI, not during pytest +# This prevents relative import errors when pytest collects test modules +import sys +if 'pytest' not in sys.modules: + from .grounding_init import init + # Initialize web extensions for compatibility with older ComfyUI versions + init() -# Initialize web extensions for compatibility with older ComfyUI versions -init() - -from .nodes import ( - GroundingModelLoader, - GroundingDetector, - BboxVisualizer, - DownloadAndLoadSAM2Model, - Sam2Segmentation, - GroundingMaskModelLoader, - GroundingMaskDetector, -) + from .nodes import ( + GroundingModelLoader, + GroundingDetector, + BboxVisualizer, + DownloadAndLoadSAM2Model, + Sam2Segmentation, + GroundingMaskModelLoader, + GroundingMaskDetector, + ) +else: + # During testing, set dummy values + GroundingModelLoader = None + GroundingDetector = None + BboxVisualizer = None + DownloadAndLoadSAM2Model = None + Sam2Segmentation = None + GroundingMaskModelLoader = None + GroundingMaskDetector = None NODE_CLASS_MAPPINGS = { "GroundingModelLoader": GroundingModelLoader, @@ -35,7 +47,7 @@ NODE_DISPLAY_NAME_MAPPINGS = { "BboxVisualizer": "Bounding Box Visualizer", "DownloadAndLoadSAM2Model": "(Down)Load SAM2Model", "Sam2Segmentation": "Sam2 Segmentation", - "GroundingMaskModelLoader": "Grounding Mask Loader", + "GroundingMaskModelLoader": "Grounding Mask Model Loader", "GroundingMaskDetector": "Grounding Mask Detector", } diff --git a/assets/plantpot.png b/assets/plantpot.png new file mode 100644 index 0000000..0e84da3 Binary files /dev/null and b/assets/plantpot.png differ diff --git a/docs/tobatch/1.jpg b/assets/tobatch/1.jpg similarity index 100% rename from docs/tobatch/1.jpg rename to assets/tobatch/1.jpg diff --git a/docs/tobatch/2.jpg b/assets/tobatch/2.jpg similarity index 100% rename from docs/tobatch/2.jpg rename to assets/tobatch/2.jpg diff --git a/docs/tobatch/3.jpg b/assets/tobatch/3.jpg similarity index 100% rename from docs/tobatch/3.jpg rename to assets/tobatch/3.jpg diff --git a/docs/tobatch/4.jpg b/assets/tobatch/4.jpg similarity index 100% rename from docs/tobatch/4.jpg rename to assets/tobatch/4.jpg diff --git a/nodes/sam2/load_model.py b/nodes/sam2/load_model.py index 03d6e05..e621889 100644 --- a/nodes/sam2/load_model.py +++ b/nodes/sam2/load_model.py @@ -1,16 +1,16 @@ import yaml -from .sam2.modeling.sam2_base import SAM2Base -from .sam2.modeling.backbones.image_encoder import ImageEncoder -from .sam2.modeling.backbones.hieradet import Hiera -from .sam2.modeling.backbones.image_encoder import FpnNeck -from .sam2.modeling.position_encoding import PositionEmbeddingSine -from .sam2.modeling.memory_attention import MemoryAttention, MemoryAttentionLayer -from .sam2.modeling.sam.transformer import RoPEAttention -from .sam2.modeling.memory_encoder import MemoryEncoder, MaskDownSampler, Fuser, CXBlock +from .modeling.sam2.modeling.sam2_base import SAM2Base +from .modeling.sam2.modeling.backbones.image_encoder import ImageEncoder +from .modeling.sam2.modeling.backbones.hieradet import Hiera +from .modeling.sam2.modeling.backbones.image_encoder import FpnNeck +from .modeling.sam2.modeling.position_encoding import PositionEmbeddingSine +from .modeling.sam2.modeling.memory_attention import MemoryAttention, MemoryAttentionLayer +from .modeling.sam2.modeling.sam.transformer import RoPEAttention +from .modeling.sam2.modeling.memory_encoder import MemoryEncoder, MaskDownSampler, Fuser, CXBlock -from .sam2.sam2_image_predictor import SAM2ImagePredictor -from .sam2.sam2_video_predictor import SAM2VideoPredictor -from .sam2.automatic_mask_generator import SAM2AutomaticMaskGenerator +from .modeling.sam2.sam2_image_predictor import SAM2ImagePredictor +from .modeling.sam2.sam2_video_predictor import SAM2VideoPredictor +from .modeling.sam2.automatic_mask_generator import SAM2AutomaticMaskGenerator from comfy.utils import load_torch_file def load_model(model_path, model_cfg_path, segmentor, dtype, device): diff --git a/nodes/sam2/loader.py b/nodes/sam2/loader.py index 69587fb..4686f95 100644 --- a/nodes/sam2/loader.py +++ b/nodes/sam2/loader.py @@ -74,7 +74,7 @@ def load_sam2(model, segmentor, device, precision, script_directory): version = "2.1" if "2.1" in model else "2.0" model_cfg_path = next( - (os.path.join(script_directory, "nodes", "sam2", "configs", cfg) + (os.path.join(script_directory, "nodes", "sam2", "configs", "sam2_configs", cfg) for key, cfg in model_mapping[version].items() if key in model), None ) diff --git a/nodes/sam2/segmentation.py b/nodes/sam2/segmentation.py index f60ab51..f3b7b05 100644 --- a/nodes/sam2/segmentation.py +++ b/nodes/sam2/segmentation.py @@ -162,9 +162,20 @@ def segment_sam2(image, sam2_model, keep_model_loaded, coordinates_positive=None else: input_box = final_box[i] if i < len(final_box) else final_box[0] + # Handle point coordinates based on individual_objects mode + if individual_objects and coordinates_positive is not None: + point_coords = final_coords[i] if i < len(final_coords) else final_coords[0] + point_labels = final_labels[i] if i < len(final_labels) else final_labels[0] + elif coordinates_positive is not None: + point_coords = final_coords + point_labels = final_labels + else: + point_coords = None + point_labels = None + out_masks, scores, logits = model.predict( - point_coords=final_coords if coordinates_positive is not None else None, - point_labels=final_labels if coordinates_positive is not None else None, + point_coords=point_coords, + point_labels=point_labels, box=input_box, multimask_output=True if not individual_objects else False, mask_input=input_mask[i].unsqueeze(0) if mask is not None else None, diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..dc4a95f --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,43 @@ +[project] +name = "comfyui-grounding" +description = "Object grounding / detection and segmentation nodes for ComfyUI with GroundingDINO, OWLv2, Florence-2, YOLO-World, SAM2, and SA2VA support" +version = "1.0.0" +license = {file = "LICENSE"} +requires-python = ">=3.10" + +# Core dependencies for ComfyUI-Grounding +dependencies = [ + # For GroundingDINO, MM-GroundingDINO, and OWLv2 (HuggingFace transformers) + "transformers>=4.30.0", + "timm>=0.9.0", + + # For YOLO-World + "ultralytics>=8.2.0", + + # For model downloads and SAM2 + "hf_transfer", + "huggingface_hub>=0.20.0", + + # For fine-tuning and flash attention + "peft", + "flash_attn", + + # Configuration and utilities + "pyyaml>=6.0", + "tqdm>=4.65.0", + + # Core PyTorch (usually already installed with ComfyUI) + "torch>=2.0.0", + "torchvision", +] + +[project.urls] +Repository = "https://github.com/PozzettiAndrea/ComfyUI-Grounding" +Documentation = "https://github.com/PozzettiAndrea/ComfyUI-Grounding/wiki" +"Bug Tracker" = "https://github.com/PozzettiAndrea/ComfyUI-Grounding/issues" + +# Comfy Registry configuration +[tool.comfy] +PublisherId = "pozzettiandrea" +DisplayName = "ComfyUI-Grounding" +Icon = "" diff --git a/pytest.ini b/pytest.ini new file mode 100644 index 0000000..5b88bc0 --- /dev/null +++ b/pytest.ini @@ -0,0 +1,23 @@ +[pytest] +testpaths = tests +python_files = test_*.py +python_classes = Test* +python_functions = test_* + +# Prevent pytest from recursing into these directories +norecursedirs = .git .github nodes workflows .eggs *.egg-info dist build web + +markers = + unit: Unit tests (fast, no model loading) + real_model: Tests that download and use real models (slow) + +addopts = + -v + --strict-markers + --tb=short + --import-mode=importlib + +# Ignore warnings from dependencies +filterwarnings = + ignore::DeprecationWarning + ignore::PendingDeprecationWarning diff --git a/requirements-dev.txt b/requirements-dev.txt new file mode 100644 index 0000000..d554843 --- /dev/null +++ b/requirements-dev.txt @@ -0,0 +1,12 @@ +# Testing dependencies +pytest>=8.0.0 +pytest-mock>=3.12.0 +pytest-asyncio>=0.23.0 + +# Code quality tools +ruff>=0.2.0 +black>=24.0.0 +isort>=5.13.0 + +# Pre-commit hooks (optional) +pre-commit>=3.6.0 diff --git a/tests/README.md b/tests/README.md new file mode 100644 index 0000000..38bc4e6 --- /dev/null +++ b/tests/README.md @@ -0,0 +1,54 @@ +# ComfyUI-Grounding Tests + +## Running Tests + +**Unit tests (fast):** +```bash +pytest tests/unit/ -v +``` + +**Real model tests (slow, downloads models):** +```bash +pytest tests/integration_real/ -v -m real_model +``` + +**Real model tests with GPU:** +```bash +pytest tests/integration_real/ -v -m real_model --use-gpu +``` + +## Test List + +### Unit Tests (6 tests) +- `test_node_registration.py` - Node class registration +- `test_model_registry.py` - Model registry validation +- `test_input_validation.py` - Input validation +- `test_cache.py` - Model caching +- `test_conversions.py` - Format conversions +- `test_drawing.py` - Bounding box drawing + +### Real Model Tests (16 tests) + +**Florence-2** (7 tests) +- Load with eager attention +- Load with SDPA attention +- Detection +- Model caching +- Attention implementations comparison +- Mask generation +- Different prompts + +**GroundingDINO** (3 tests) +- Load SwinT model +- Detection +- Model caching + +**OWLv2** (3 tests) +- Load Base Patch16 model +- Detection +- Model caching + +**YOLO-World** (3 tests) +- Load v8s model +- Detection +- Model caching diff --git a/tests/conftest.py b/tests/conftest.py new file mode 100644 index 0000000..f17e1d3 --- /dev/null +++ b/tests/conftest.py @@ -0,0 +1,133 @@ +""" +Pytest configuration and fixtures for ComfyUI-Grounding tests +""" +import sys +import os +from pathlib import Path +import pytest +import torch +from unittest.mock import MagicMock + + +def pytest_addoption(parser): + """Add custom command line options""" + parser.addoption( + "--use-gpu", + action="store_true", + default=False, + help="Run tests on GPU instead of CPU (much faster for real model tests)" + ) + + +# Add the custom node directory to Python path so we can import nodes package +custom_nodes_dir = Path(__file__).parent.parent +sys.path.insert(0, str(custom_nodes_dir)) + +# Mock ComfyUI modules at module level BEFORE pytest starts +# This prevents import errors when pytest tries to load __init__.py files +mock_folder_paths = type("folder_paths", (), {})() +mock_folder_paths.models_dir = "/tmp/test_models" +mock_folder_paths.get_folder_paths = lambda x: ["/tmp/test_models"] +sys.modules["folder_paths"] = mock_folder_paths + +mock_comfy = type("comfy", (), {})() +mock_comfy_utils = type("utils", (), {})() +mock_comfy_utils.load_torch_file = lambda x: {} +mock_comfy_utils.ProgressBar = MagicMock() +mock_comfy_utils.common_upscale = MagicMock() +mock_comfy.utils = mock_comfy_utils + +mock_comfy_mm = type("model_management", (), {})() + +# Device selection: Check environment variable set by session fixture +def _get_test_device(): + """Get device for testing - GPU if --use-gpu flag is set, else CPU""" + use_gpu = os.environ.get("PYTEST_USE_GPU", "0") == "1" + if use_gpu and torch.cuda.is_available(): + return torch.device("cuda") + return torch.device("cpu") + +mock_comfy_mm.get_torch_device = _get_test_device +mock_comfy_mm.soft_empty_cache = lambda: None +mock_comfy_mm.load_models_gpu = lambda x: None +mock_comfy.model_management = mock_comfy_mm + +sys.modules["comfy"] = mock_comfy +sys.modules["comfy.utils"] = mock_comfy_utils +sys.modules["comfy.model_management"] = mock_comfy_mm + +# Mock grounding_init module that __init__.py tries to import +mock_grounding_init = type("grounding_init", (), {})() +mock_grounding_init.init = lambda: None +sys.modules["grounding_init"] = mock_grounding_init + + +def pytest_ignore_collect(collection_path, path, config): + """Ignore __init__.py files during collection""" + if collection_path.name == "__init__.py": + return True + return False + + +@pytest.fixture(scope="session", autouse=True) +def setup_test_device(request): + """Configure test device based on --use-gpu flag""" + use_gpu = request.config.getoption("--use-gpu") + if use_gpu: + os.environ["PYTEST_USE_GPU"] = "1" + if torch.cuda.is_available(): + print(f"\n🚀 Using GPU: {torch.cuda.get_device_name(0)}") + else: + print("\n⚠️ --use-gpu specified but CUDA not available, using CPU") + else: + os.environ["PYTEST_USE_GPU"] = "0" + print("\n💻 Using CPU (use --use-gpu for GPU acceleration)") + + yield + + # Cleanup + os.environ.pop("PYTEST_USE_GPU", None) + + +@pytest.fixture(scope="session", autouse=True) +def setup_mock_comfy(): + """Set up mock ComfyUI modules for testing - runs once per session""" + # Ensure mocks persist throughout test session + return True + + +@pytest.fixture +def mock_comfy_environment(): + """Provide access to mocked ComfyUI environment (already set up at module level)""" + return sys.modules["folder_paths"] + + +@pytest.fixture +def small_image(): + """Create a small test image tensor for faster tests""" + return torch.rand(1, 224, 224, 3) + + +@pytest.fixture(autouse=True) +def reset_model_cache(): + """Clear model cache between tests""" + from nodes.utils.cache import MODEL_CACHE + MODEL_CACHE.clear() + yield + MODEL_CACHE.clear() + + +def pytest_configure(config): + """Configure pytest with custom markers""" + config.addinivalue_line( + "markers", "unit: Unit tests (fast, no model loading)" + ) + config.addinivalue_line( + "markers", "integration: Integration tests with mocked models" + ) + config.addinivalue_line( + "markers", "real_model: Tests that download and use real models (slow)" + ) + config.addinivalue_line( + "markers", "workflow: Workflow validation tests" + ) diff --git a/tests/integration_real/__init__.py b/tests/integration_real/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/integration_real/test_florence2_real.py b/tests/integration_real/test_florence2_real.py new file mode 100644 index 0000000..f978d9c --- /dev/null +++ b/tests/integration_real/test_florence2_real.py @@ -0,0 +1,211 @@ +""" +Real model integration tests for Florence2 +These tests download and use actual models - marked as slow +""" +import pytest +import torch + + +@pytest.mark.real_model +def test_florence2_base_load_eager(mock_comfy_environment): + """Test loading real Florence-2 Base model with eager attention""" + from nodes import GroundingModelLoader + + loader = GroundingModelLoader() + + # Load Florence-2 Base with eager attention + model_dict = loader.load_model( + model="Florence-2: Base (0.23B params)", + florence2_attn="eager" + )[0] + + assert model_dict is not None + assert "type" in model_dict + assert model_dict["type"] == "florence2" + assert "model" in model_dict + assert "processor" in model_dict + + +@pytest.mark.real_model +def test_florence2_base_load_sdpa(mock_comfy_environment): + """Test loading real Florence-2 Base model with SDPA attention""" + from nodes import GroundingModelLoader + + loader = GroundingModelLoader() + + # Load Florence-2 Base with SDPA attention + model_dict = loader.load_model( + model="Florence-2: Base (0.23B params)", + florence2_attn="sdpa" + )[0] + + assert model_dict is not None + assert "type" in model_dict + assert model_dict["type"] == "florence2" + + +@pytest.mark.real_model +def test_florence2_base_detection(mock_comfy_environment, small_image): + """Test real detection with Florence-2 Base model""" + from nodes import GroundingModelLoader, GroundingDetector + + # Load model + loader = GroundingModelLoader() + model_dict = loader.load_model( + model="Florence-2: Base (0.23B params)", + florence2_attn="eager" + )[0] + + # Run detection + detector = GroundingDetector() + bboxes, annotated_img, labels, masks = detector.detect( + model=model_dict, + image=small_image, + prompt="person", + confidence_threshold=0.3, + bbox_output_format="dict_with_data", + output_masks=False + ) + + # Verify outputs structure + assert bboxes is not None + assert annotated_img is not None + assert annotated_img.shape == small_image.shape + assert isinstance(labels, str) + + +@pytest.mark.real_model +def test_florence2_model_caching(mock_comfy_environment, reset_model_cache): + """Test that Florence-2 models are properly cached""" + from nodes import GroundingModelLoader + from nodes.utils.cache import MODEL_CACHE + + loader = GroundingModelLoader() + + # First load + model1 = loader.load_model( + model="Florence-2: Base (0.23B params)", + florence2_attn="eager" + )[0] + + cache_size_after_first = len(MODEL_CACHE) + + # Second load (should use cache) + model2 = loader.load_model( + model="Florence-2: Base (0.23B params)", + florence2_attn="eager" + )[0] + + cache_size_after_second = len(MODEL_CACHE) + + # Cache should have model + assert cache_size_after_first > 0 + # Cache shouldn't grow on second load + assert cache_size_after_second == cache_size_after_first + + +@pytest.mark.real_model +def test_florence2_attention_implementations_equivalent(mock_comfy_environment, small_image): + """Test that different attention implementations produce similar results""" + from nodes import GroundingModelLoader, GroundingDetector + + loader = GroundingModelLoader() + detector = GroundingDetector() + + # Load with eager + model_eager = loader.load_model( + model="Florence-2: Base (0.23B params)", + florence2_attn="eager" + )[0] + + bboxes_eager, _, _, _ = detector.detect( + model=model_eager, + image=small_image, + prompt="object", + confidence_threshold=0.3, + bbox_output_format="dict_with_data", + output_masks=False + ) + + # Load with SDPA + model_sdpa = loader.load_model( + model="Florence-2: Base (0.23B params)", + florence2_attn="sdpa" + )[0] + + bboxes_sdpa, _, _, _ = detector.detect( + model=model_sdpa, + image=small_image, + prompt="object", + confidence_threshold=0.3, + bbox_output_format="dict_with_data", + output_masks=False + ) + + # Both should produce valid outputs (results may vary slightly) + assert bboxes_eager is not None + assert bboxes_sdpa is not None + + +@pytest.mark.real_model +def test_florence2_mask_generation(mock_comfy_environment, small_image): + """Test Florence-2 mask generation capability (from bounding boxes)""" + from nodes import GroundingModelLoader, GroundingDetector + + # Load regular bbox detection model + loader = GroundingModelLoader() + model_dict = loader.load_model( + model="Florence-2: Base (0.23B params)", + florence2_attn="eager" + )[0] + + # Run detection with output_masks=True + detector = GroundingDetector() + bboxes, annotated_img, labels, masks = detector.detect( + model=model_dict, + image=small_image, + prompt="object", + confidence_threshold=0.3, + bbox_output_format="dict_with_data", + output_masks=True + ) + + # Verify outputs structure + assert bboxes is not None + assert masks is not None + assert annotated_img is not None + assert isinstance(labels, str) + + +@pytest.mark.real_model +def test_florence2_different_prompts(mock_comfy_environment, small_image): + """Test Florence-2 with different prompt formats""" + from nodes import GroundingModelLoader, GroundingDetector + + loader = GroundingModelLoader() + model_dict = loader.load_model( + model="Florence-2: Base (0.23B params)", + florence2_attn="eager" + )[0] + + detector = GroundingDetector() + + prompts = [ + "person", + "person and dog", + "Locate person", + "Find the person in the image" + ] + + for prompt in prompts: + bboxes, _, _, _ = detector.detect( + model=model_dict, + image=small_image, + prompt=prompt, + confidence_threshold=0.3, + bbox_output_format="dict_with_data", + output_masks=False + ) + + # Each prompt should produce valid output + assert bboxes is not None diff --git a/tests/integration_real/test_grounding_dino_real.py b/tests/integration_real/test_grounding_dino_real.py new file mode 100644 index 0000000..c0e507f --- /dev/null +++ b/tests/integration_real/test_grounding_dino_real.py @@ -0,0 +1,86 @@ +""" +Real model integration tests for GroundingDINO +These tests download and use actual models - marked as slow +""" +import pytest +import torch + + +@pytest.mark.real_model +def test_grounding_dino_swint_load(mock_comfy_environment): + """Test loading real GroundingDINO SwinT model""" + from nodes import GroundingModelLoader + + loader = GroundingModelLoader() + + # Load smallest GroundingDINO model + model_dict = loader.load_model( + model="GroundingDINO: SwinT OGC (694MB)", + florence2_attn="eager" + )[0] + + assert model_dict is not None + assert "type" in model_dict + assert model_dict["type"] == "grounding_dino" + assert "model" in model_dict + assert "processor" in model_dict + + +@pytest.mark.real_model +def test_grounding_dino_swint_detection(mock_comfy_environment, small_image): + """Test real detection with GroundingDINO SwinT model""" + from nodes import GroundingModelLoader, GroundingDetector + + # Load model + loader = GroundingModelLoader() + model_dict = loader.load_model( + model="GroundingDINO: SwinT OGC (694MB)", + florence2_attn="eager" + )[0] + + # Run detection + detector = GroundingDetector() + bboxes, annotated_img, labels, masks = detector.detect( + model=model_dict, + image=small_image, + prompt="person . dog .", + confidence_threshold=0.3, + bbox_output_format="dict_with_data", + output_masks=False + ) + + # Verify outputs structure (may or may not find objects in random image) + assert bboxes is not None + assert annotated_img is not None + assert annotated_img.shape == small_image.shape + assert isinstance(labels, str) + + +@pytest.mark.real_model +def test_grounding_dino_model_caching(mock_comfy_environment, reset_model_cache): + """Test that GroundingDINO models are properly cached""" + from nodes import GroundingModelLoader + from nodes.utils.cache import MODEL_CACHE + + loader = GroundingModelLoader() + + # First load + model1 = loader.load_model( + model="GroundingDINO: SwinT OGC (694MB)", + florence2_attn="eager" + )[0] + + cache_size_after_first = len(MODEL_CACHE) + + # Second load (should use cache) + model2 = loader.load_model( + model="GroundingDINO: SwinT OGC (694MB)", + florence2_attn="eager" + )[0] + + cache_size_after_second = len(MODEL_CACHE) + + # Cache should have model + assert cache_size_after_first > 0 + # Cache shouldn't grow on second load + assert cache_size_after_second == cache_size_after_first diff --git a/tests/integration_real/test_owlv2_real.py b/tests/integration_real/test_owlv2_real.py new file mode 100644 index 0000000..2b7b8ad --- /dev/null +++ b/tests/integration_real/test_owlv2_real.py @@ -0,0 +1,86 @@ +""" +Real model integration tests for OWLv2 +These tests download and use actual models - marked as slow +""" +import pytest +import torch + + +@pytest.mark.real_model +def test_owlv2_base_load(mock_comfy_environment): + """Test loading real OWLv2 Base Patch16 model""" + from nodes import GroundingModelLoader + + loader = GroundingModelLoader() + + # Load smallest OWLv2 model + model_dict = loader.load_model( + model="OWLv2: Base Patch16", + florence2_attn="eager" + )[0] + + assert model_dict is not None + assert "type" in model_dict + assert model_dict["type"] == "owlv2" + assert "model" in model_dict + assert "processor" in model_dict + + +@pytest.mark.real_model +def test_owlv2_base_detection(mock_comfy_environment, small_image): + """Test real detection with OWLv2 Base model""" + from nodes import GroundingModelLoader, GroundingDetector + + # Load model + loader = GroundingModelLoader() + model_dict = loader.load_model( + model="OWLv2: Base Patch16", + florence2_attn="eager" + )[0] + + # Run detection + detector = GroundingDetector() + bboxes, annotated_img, labels, masks = detector.detect( + model=model_dict, + image=small_image, + prompt="person", + confidence_threshold=0.3, + bbox_output_format="dict_with_data", + output_masks=False + ) + + # Verify outputs structure + assert bboxes is not None + assert annotated_img is not None + assert annotated_img.shape == small_image.shape + assert isinstance(labels, str) + + +@pytest.mark.real_model +def test_owlv2_model_caching(mock_comfy_environment, reset_model_cache): + """Test that OWLv2 models are properly cached""" + from nodes import GroundingModelLoader + from nodes.utils.cache import MODEL_CACHE + + loader = GroundingModelLoader() + + # First load + model1 = loader.load_model( + model="OWLv2: Base Patch16", + florence2_attn="eager" + )[0] + + cache_size_after_first = len(MODEL_CACHE) + + # Second load (should use cache) + model2 = loader.load_model( + model="OWLv2: Base Patch16", + florence2_attn="eager" + )[0] + + cache_size_after_second = len(MODEL_CACHE) + + # Cache should have model + assert cache_size_after_first > 0 + # Cache shouldn't grow on second load + assert cache_size_after_second == cache_size_after_first diff --git a/tests/integration_real/test_yolo_world_real.py b/tests/integration_real/test_yolo_world_real.py new file mode 100644 index 0000000..c98c2a7 --- /dev/null +++ b/tests/integration_real/test_yolo_world_real.py @@ -0,0 +1,85 @@ +""" +Real model integration tests for YOLO-World +These tests download and use actual models - marked as slow +""" +import pytest +import torch + + +@pytest.mark.real_model +def test_yolo_world_v2_s_load(mock_comfy_environment): + """Test loading real YOLO-World v2 S (small) model""" + from nodes import GroundingModelLoader + + loader = GroundingModelLoader() + + # Load smallest YOLO-World model + model_dict = loader.load_model( + model="YOLO-World: v8s (Small)", + florence2_attn="eager" + )[0] + + assert model_dict is not None + assert "type" in model_dict + assert model_dict["type"] == "yolo_world" + assert "model" in model_dict + + +@pytest.mark.real_model +def test_yolo_world_v2_s_detection(mock_comfy_environment, small_image): + """Test real detection with YOLO-World v2 S model""" + from nodes import GroundingModelLoader, GroundingDetector + + # Load model + loader = GroundingModelLoader() + model_dict = loader.load_model( + model="YOLO-World: v8s (Small)", + florence2_attn="eager" + )[0] + + # Run detection + detector = GroundingDetector() + bboxes, annotated_img, labels, masks = detector.detect( + model=model_dict, + image=small_image, + prompt="person", + confidence_threshold=0.3, + bbox_output_format="dict_with_data", + output_masks=False + ) + + # Verify outputs structure + assert bboxes is not None + assert annotated_img is not None + assert annotated_img.shape == small_image.shape + assert isinstance(labels, str) + + +@pytest.mark.real_model +def test_yolo_world_model_caching(mock_comfy_environment, reset_model_cache): + """Test that YOLO-World models are properly cached""" + from nodes import GroundingModelLoader + from nodes.utils.cache import MODEL_CACHE + + loader = GroundingModelLoader() + + # First load + model1 = loader.load_model( + model="YOLO-World: v8s (Small)", + florence2_attn="eager" + )[0] + + cache_size_after_first = len(MODEL_CACHE) + + # Second load (should use cache) + model2 = loader.load_model( + model="YOLO-World: v8s (Small)", + florence2_attn="eager" + )[0] + + cache_size_after_second = len(MODEL_CACHE) + + # Cache should have model + assert cache_size_after_first > 0 + # Cache shouldn't grow on second load + assert cache_size_after_second == cache_size_after_first diff --git a/tests/unit/test_cache.py b/tests/unit/test_cache.py new file mode 100644 index 0000000..172a71e --- /dev/null +++ b/tests/unit/test_cache.py @@ -0,0 +1,20 @@ +""" +Unit tests for model caching in ComfyUI-Grounding +""" +import pytest + + +@pytest.mark.unit +def test_model_cache_can_store_and_retrieve(mock_comfy_environment, reset_model_cache): + """Test that MODEL_CACHE can store and retrieve models""" + from nodes.utils.cache import MODEL_CACHE + + # Test storing a value + test_key = "test_model_key" + test_value = {"model": "test", "type": "grounding_dino"} + + MODEL_CACHE[test_key] = test_value + + # Test retrieving the value + assert test_key in MODEL_CACHE + assert MODEL_CACHE[test_key] == test_value diff --git a/tests/unit/test_conversions.py b/tests/unit/test_conversions.py new file mode 100644 index 0000000..3f6d149 --- /dev/null +++ b/tests/unit/test_conversions.py @@ -0,0 +1,26 @@ +""" +Unit tests for conversion utilities in ComfyUI-Grounding +""" +import pytest +import torch + + +@pytest.mark.unit +def test_boxes_to_masks_basic(mock_comfy_environment): + """Test basic boxes_to_masks conversion""" + import numpy as np + from nodes.utils.conversions import boxes_to_masks + + # Create test boxes as numpy arrays: [[x1, y1, x2, y2]] + boxes = [[np.array([10, 10, 50, 50]), np.array([60, 60, 100, 100])]] + image_shape = (1, 128, 128, 3) + + masks = boxes_to_masks(boxes, image_shape) + + # Check output shape: (num_boxes, height, width) + assert masks.shape[0] == 2, "Should have 2 masks" + assert masks.shape[1] == 128, "Mask height should match image height" + assert masks.shape[2] == 128, "Mask width should match image width" + + # Check dtype + assert masks.dtype == torch.float32 or masks.dtype == torch.bool diff --git a/tests/unit/test_input_validation.py b/tests/unit/test_input_validation.py new file mode 100644 index 0000000..43834e0 --- /dev/null +++ b/tests/unit/test_input_validation.py @@ -0,0 +1,25 @@ +""" +Unit tests for input validation in ComfyUI-Grounding nodes +""" +import pytest + + +@pytest.mark.unit +def test_grounding_detector_input_types(mock_comfy_environment): + """Test GroundingDetector INPUT_TYPES""" + from nodes import GroundingDetector + + input_types = GroundingDetector.INPUT_TYPES() + + # Check required inputs + required = input_types["required"] + assert "model" in required + assert "image" in required + assert "prompt" in required + assert "confidence_threshold" in required + + # Check optional inputs + optional = input_types["optional"] + assert "single_box_mode" in optional + assert "bbox_output_format" in optional + assert "output_masks" in optional diff --git a/tests/unit/test_model_registry.py b/tests/unit/test_model_registry.py new file mode 100644 index 0000000..29296d1 --- /dev/null +++ b/tests/unit/test_model_registry.py @@ -0,0 +1,12 @@ +""" +Unit tests for model registry in ComfyUI-Grounding +""" +import pytest + + +@pytest.mark.unit +def test_model_registry_count(mock_comfy_environment): + """Test that we have exactly 19 models registered""" + from nodes.config.bbox_models import MODEL_REGISTRY + + assert len(MODEL_REGISTRY) == 19, f"Expected 19 models, found {len(MODEL_REGISTRY)}" diff --git a/tests/unit/test_node_registration.py b/tests/unit/test_node_registration.py new file mode 100644 index 0000000..84725f0 --- /dev/null +++ b/tests/unit/test_node_registration.py @@ -0,0 +1,26 @@ +""" +Unit tests for node registration in ComfyUI-Grounding +""" +import pytest + + +@pytest.mark.unit +def test_node_class_mappings_exists(mock_comfy_environment): + """Test that NODE_CLASS_MAPPINGS is defined and contains all expected nodes""" + from nodes import NODE_CLASS_MAPPINGS + + expected_nodes = [ + "GroundingModelLoader", + "GroundingDetector", + "BboxVisualizer", + "DownloadAndLoadSAM2Model", + "Sam2Segmentation", + "GroundingMaskModelLoader", + "GroundingMaskDetector" + ] + + assert NODE_CLASS_MAPPINGS is not None, "NODE_CLASS_MAPPINGS is not defined" + + for node_name in expected_nodes: + assert node_name in NODE_CLASS_MAPPINGS, f"{node_name} not found in NODE_CLASS_MAPPINGS" + assert NODE_CLASS_MAPPINGS[node_name] is not None, f"{node_name} maps to None" diff --git a/workflows/batch_processing_sam2.json b/workflows/batch_normal_grounding.json similarity index 66% rename from workflows/batch_processing_sam2.json rename to workflows/batch_normal_grounding.json index 3c8190a..1fe2421 100644 --- a/workflows/batch_processing_sam2.json +++ b/workflows/batch_normal_grounding.json @@ -1,19 +1,19 @@ { - "id": "b29971c7-6074-4707-895e-9f2360e11e2d", + "id": "605c8e58-85ce-480e-ae26-54cf0f1d8ce7", "revision": 0, - "last_node_id": 35, - "last_link_id": 48, + "last_node_id": 17, + "last_link_id": 19, "nodes": [ { - "id": 18, + "id": 3, "type": "GroundingModelLoader", "pos": [ - 761.1567094157901, - 37.11377863503034 + -324.99609375, + -3.8984375 ], "size": [ - 272.064453125, - 106 + 270, + 82 ], "flags": {}, "order": 0, @@ -24,43 +24,298 @@ "name": "model", "type": "GROUNDING_MODEL", "links": [ - 27 + 1 ] } ], "properties": { "aux_id": "PozzettiAndrea/ComfyUI-Grounding", - "ver": "c9c72642cd7affb18d5aa54f21ee7d3acf7412eb", + "ver": "a947f4961c39cc150a98738fa83a0494e52f3de0", "Node name for S&R": "GroundingModelLoader" }, "widgets_values": [ "Florence-2: Large (0.77B params)", - true, "eager" ] }, { - "id": 31, - "type": "LoadImagesFromFolderKJ", + "id": 12, + "type": "DownloadAndLoadSAM2Model", "pos": [ - 681.3852212888811, - 257.2916550578389 + 134.1244248881893, + -152.4815917189195 ], "size": [ - 290.5201171875, - 262 + 270, + 130 ], "flags": {}, "order": 1, "mode": 0, "inputs": [], + "outputs": [ + { + "name": "sam2_model", + "type": "SAM2MODEL", + "links": [ + 10 + ] + } + ], + "properties": { + "aux_id": "PozzettiAndrea/ComfyUI-Grounding", + "ver": "a947f4961c39cc150a98738fa83a0494e52f3de0", + "Node name for S&R": "DownloadAndLoadSAM2Model" + }, + "widgets_values": [ + "sam2.1_hiera_large.safetensors", + "single_image", + "cuda", + "fp16" + ] + }, + { + "id": 14, + "type": "JoinImageWithAlpha", + "pos": [ + 806.4560194385198, + 47.17325913006609 + ], + "size": [ + 176.86484375, + 46 + ], + "flags": {}, + "order": 6, + "mode": 0, + "inputs": [ + { + "name": "image", + "type": "IMAGE", + "link": 13 + }, + { + "name": "alpha", + "type": "MASK", + "link": 17 + } + ], + "outputs": [ + { + "name": "IMAGE", + "type": "IMAGE", + "links": [ + 19 + ] + } + ], + "properties": { + "cnr_id": "comfy-core", + "ver": "0.3.67", + "Node name for S&R": "JoinImageWithAlpha" + }, + "widgets_values": [] + }, + { + "id": 11, + "type": "Sam2Segmentation", + "pos": [ + 507.4435292430558, + 34.683721146105555 + ], + "size": [ + 272.087890625, + 254 + ], + "flags": {}, + "order": 4, + "mode": 0, + "inputs": [ + { + "name": "sam2_model", + "type": "SAM2MODEL", + "link": 10 + }, + { + "name": "image", + "type": "IMAGE", + "link": 11 + }, + { + "name": "coordinates_positive", + "shape": 7, + "type": "STRING", + "link": null + }, + { + "name": "coordinates_negative", + "shape": 7, + "type": "STRING", + "link": null + }, + { + "name": "bboxes", + "shape": 7, + "type": "BBOX", + "link": 12 + }, + { + "name": "mask", + "shape": 7, + "type": "MASK", + "link": null + } + ], + "outputs": [ + { + "name": "mask", + "type": "MASK", + "links": [ + 16 + ] + } + ], + "properties": { + "aux_id": "PozzettiAndrea/ComfyUI-Grounding", + "ver": "a947f4961c39cc150a98738fa83a0494e52f3de0", + "Node name for S&R": "Sam2Segmentation" + }, + "widgets_values": [ + false, + false, + 0, + 0, + 0 + ] + }, + { + "id": 1, + "type": "GroundingDetector", + "pos": [ + 68.70780892432435, + 37.906621234841865 + ], + "size": [ + 400, + 364 + ], + "flags": {}, + "order": 3, + "mode": 0, + "inputs": [ + { + "name": "model", + "type": "GROUNDING_MODEL", + "link": 1 + }, + { + "name": "image", + "type": "IMAGE", + "link": 8 + } + ], + "outputs": [ + { + "name": "bboxes", + "type": "BBOX", + "links": [ + 12 + ] + }, + { + "name": "annotated_image", + "type": "IMAGE", + "links": [] + }, + { + "name": "labels", + "type": "STRING", + "links": null + }, + { + "name": "masks", + "type": "MASK", + "links": null + } + ], + "properties": { + "aux_id": "PozzettiAndrea/ComfyUI-Grounding", + "ver": "a947f4961c39cc150a98738fa83a0494e52f3de0", + "Node name for S&R": "GroundingDetector" + }, + "widgets_values": [ + "main object", + 0.3, + false, + true, + "list_only", + false, + 42, + 42, + 42, + "randomize" + ] + }, + { + "id": 15, + "type": "InvertMask", + "pos": [ + 634.4085072101292, + -31.37835895949953 + ], + "size": [ + 140, + 26 + ], + "flags": {}, + "order": 5, + "mode": 0, + "inputs": [ + { + "name": "mask", + "type": "MASK", + "link": 16 + } + ], + "outputs": [ + { + "name": "MASK", + "type": "MASK", + "links": [ + 17 + ] + } + ], + "properties": { + "cnr_id": "comfy-core", + "ver": "0.3.67", + "Node name for S&R": "InvertMask" + }, + "widgets_values": [] + }, + { + "id": 9, + "type": "LoadImagesFromFolderKJ", + "pos": [ + -319.8692780804565, + 159.9365003928532 + ], + "size": [ + 290.5201171875, + 262 + ], + "flags": {}, + "order": 2, + "mode": 0, + "inputs": [], "outputs": [ { "name": "image", "type": "IMAGE", "links": [ - 41, - 43 + 8, + 11, + 13 ] }, { @@ -81,13 +336,13 @@ ], "properties": { "cnr_id": "comfyui-kjnodes", - "ver": "1.1.8", + "ver": "1.1.9", "Node name for S&R": "LoadImagesFromFolderKJ" }, "widgets_values": [ - "/workspace/depthy/ComfyUI/custom_nodes/ComfyUI-Grounding/docs/tobatch/", - 1200, - 1200, + "/workspace/groundingnode/ComfyUI/custom_nodes/ComfyUI-Grounding/assets/tobatch/", + 1024, + 1024, "pad", 0, 0, @@ -95,314 +350,117 @@ ] }, { - "id": 34, - "type": "MaskPreview", + "id": 17, + "type": "PreviewImage", "pos": [ - 2238.8322620750596, - -304.2753331354774 + 1001.6651677560029, + 55.417983277011885 ], "size": [ - 140, - 246 + 330.90445054815405, + 258 ], "flags": {}, - "order": 6, + "order": 7, "mode": 0, "inputs": [ { - "name": "mask", - "type": "MASK", - "link": 45 + "name": "images", + "type": "IMAGE", + "link": 19 } ], "outputs": [], "properties": { "cnr_id": "comfy-core", "ver": "0.3.67", - "Node name for S&R": "MaskPreview" - }, - "widgets_values": [] - }, - { - "id": 32, - "type": "DownloadAndLoadSAM2Model", - "pos": [ - 1361.2896454187016, - -358.19085905073246 - ], - "size": [ - 270, - 130 - ], - "flags": {}, - "order": 2, - "mode": 0, - "inputs": [], - "outputs": [ - { - "name": "sam2_model", - "type": "SAM2MODEL", - "links": [ - 42 - ] - } - ], - "properties": { - "aux_id": "PozzettiAndrea/ComfyUI-Grounding", - "ver": "7bfc6241cba9a88ffc5ec2b837fd30d2af73d95c", - "Node name for S&R": "DownloadAndLoadSAM2Model" - }, - "widgets_values": [ - "sam2_hiera_large.safetensors", - "single_image", - "cuda", - "fp16" - ] - }, - { - "id": 30, - "type": "PreviewImage", - "pos": [ - 1717.3721807161592, - -103.37955289789586 - ], - "size": [ - 140, - 246 - ], - "flags": {}, - "order": 4, - "mode": 0, - "inputs": [ - { - "name": "images", - "type": "IMAGE", - "link": 39 - } - ], - "outputs": [], - "properties": { - "cnr_id": "comfy-core", - "ver": "0.3.65", "Node name for S&R": "PreviewImage" }, "widgets_values": [] - }, - { - "id": 19, - "type": "GroundingDetector", - "pos": [ - 1147.1057310247927, - -143.3627616665786 - ], - "size": [ - 400, - 268 - ], - "flags": {}, - "order": 3, - "mode": 0, - "inputs": [ - { - "name": "model", - "type": "GROUNDING_MODEL", - "link": 27 - }, - { - "name": "image", - "type": "IMAGE", - "link": 41 - } - ], - "outputs": [ - { - "name": "bboxes", - "type": "BBOX", - "links": [ - 48 - ] - }, - { - "name": "annotated_image", - "type": "IMAGE", - "links": [ - 39 - ] - }, - { - "name": "labels", - "type": "STRING", - "links": null - }, - { - "name": "masks", - "type": "MASK", - "links": [ - 47 - ] - } - ], - "properties": { - "aux_id": "PozzettiAndrea/ComfyUI-Grounding", - "ver": "c9c72642cd7affb18d5aa54f21ee7d3acf7412eb", - "Node name for S&R": "GroundingDetector" - }, - "widgets_values": [ - "main object", - 0.35, - 0.35, - true, - "list_only", - true - ] - }, - { - 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1, + 3, 0, - 19, + 1, 0, "GROUNDING_MODEL" ], [ - 39, - 19, + 8, + 9, + 0, 1, - 30, - 0, - "IMAGE" - ], - [ - 41, - 31, - 0, - 19, 1, "IMAGE" ], [ - 42, - 32, + 10, + 12, 0, - 33, + 11, 0, "SAM2MODEL" ], [ - 43, - 31, + 11, + 9, 0, - 33, + 11, 1, "IMAGE" ], [ - 45, - 33, + 12, + 1, 0, - 34, - 0, - "MASK" - ], - [ - 47, - 19, - 3, - 33, - 5, - "MASK" - ], - [ - 48, - 19, - 0, - 33, + 11, 4, "BBOX" + ], + [ + 13, + 9, + 0, + 14, + 0, + "IMAGE" + ], + [ + 16, + 11, + 0, + 15, + 0, + "MASK" + ], + [ + 17, + 15, + 0, + 14, + 1, + "MASK" + ], + [ + 19, + 14, + 0, + 17, + 0, + "IMAGE" ] ], "groups": [], "config": {}, "extra": { "ds": { - "scale": 0.9483253215897468, + "scale": 0.9278994587027772, "offset": [ - -802.6149662434965, - 550.1068245397717 + 508.01216790085954, + 282.0476732486773 ] }, "frontendVersion": "1.28.8" diff --git a/workflows/Example.json b/workflows/mask_grounding.json similarity index 54% rename from workflows/Example.json rename to workflows/mask_grounding.json index 2aea663..b29768b 100644 --- a/workflows/Example.json +++ b/workflows/mask_grounding.json @@ -1,117 +1,84 @@ { - "id": "b29971c7-6074-4707-895e-9f2360e11e2d", + "id": "38945c5c-4e77-4d6c-b916-6a2f0a1b6a89", "revision": 0, - "last_node_id": 30, - "last_link_id": 40, + "last_node_id": 32, + "last_link_id": 39, "nodes": [ { - "id": 29, - "type": "LoadImage", + "id": 28, + "type": "InvertMask", "pos": [ - 691.3480657963805, - 244.71705551823334 + 98.71468314873522, + -76.55255233775446 ], "size": [ - 274.080078125, - 314 + 140, + 26 ], "flags": {}, - "order": 0, + "order": 3, "mode": 0, - "inputs": [], - "outputs": [ + "inputs": [ { - "name": "IMAGE", - "type": "IMAGE", - "links": [ - 38, - 40 - ] - }, + "name": "mask", + "type": "MASK", + "link": 33 + } + ], + "outputs": [ { "name": "MASK", "type": "MASK", - "links": null + "links": [ + 34 + ] } ], "properties": { "cnr_id": "comfy-core", - "ver": "0.3.65", - "Node name for S&R": "LoadImage" - }, - "widgets_values": [ - "example.png", - 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"GroundingDINO: SwinB (938MB)", - true, - "eager" - ] + "cnr_id": "comfy-core", + "ver": "0.3.67", + "Node name for S&R": "JoinImageWithAlpha" + } }, { "id": 19, - "type": "GroundingDetector", + "type": "GroundingMaskDetector", "pos": [ - 1147.1057310247927, - -143.3627616665786 + 106.9620845129382, + -14.471635853967237 ], "size": [ 400, - 268 + 248 ], "flags": {}, "order": 2, @@ -227,8 +240,8 @@ "inputs": [ { "name": "model", - "type": "GROUNDING_MODEL", - "link": 27 + "type": "MASK_MODEL", + "link": 21 }, { "name": "image", @@ -237,28 +250,23 @@ } ], "outputs": [ - { - "name": "bboxes", - "type": "BBOX", - "links": [ - 31 - ] - }, - { - "name": "annotated_image", - "type": "IMAGE", - "links": [ - 39 - ] - }, - { - "name": "labels", - "type": "STRING", - "links": null - }, { "name": "masks", "type": "MASK", + "links": [ + 33 + ] + }, + { + "name": "overlaid_mask", + "type": "IMAGE", + "links": [ + 35 + ] + }, + { + "name": "text", + "type": "STRING", "links": [ 37 ] @@ -266,55 +274,105 @@ ], "properties": { "aux_id": "PozzettiAndrea/ComfyUI-Grounding", - "ver": "c9c72642cd7affb18d5aa54f21ee7d3acf7412eb", - "Node name for S&R": "GroundingDetector" + "ver": "a947f4961c39cc150a98738fa83a0494e52f3de0", + "Node name for S&R": "GroundingMaskDetector" }, "widgets_values": [ - "character", - 0.1, - 0.01, - true, - "dict_with_data", - true + "segment the main object in the image.", + 0.3, + 3, + 2048, + 1644266233, + "randomize" + ] + }, + { + "id": 18, + "type": "GroundingMaskModelLoader", + "pos": [ + -299.81672209985305, + -40.87788547709978 + ], + "size": [ + 270, + 82 + ], + "flags": {}, + "order": 1, + "mode": 0, + "inputs": [], + "outputs": [ + { + "name": "model", + "type": "MASK_MODEL", + "links": [ + 21 + ] + } + ], + "properties": { + "aux_id": "PozzettiAndrea/ComfyUI-Grounding", + "ver": "a947f4961c39cc150a98738fa83a0494e52f3de0", + "Node name for S&R": "GroundingMaskModelLoader" + }, + "widgets_values": [ + "SA2VA: 1B", + "bf16" ] } ], "links": [ [ - 27, + 21, 18, 0, 19, 0, - "GROUNDING_MODEL" + "MASK_MODEL" ], [ - 31, + 33, 19, 0, - 21, - 1, - "BBOX" + 28, + 0, + "MASK" ], [ - 32, - 21, + 34, + 28, 0, - 22, + 26, + 1, + "MASK" + ], + [ + 35, + 19, + 1, + 29, + 0, + "IMAGE" + ], + [ + 36, + 26, + 0, + 30, 0, "IMAGE" ], [ 37, 19, - 3, - 28, + 2, + 31, 0, - "MASK" + "*" ], [ 38, - 29, + 32, 0, 19, 1, @@ -322,17 +380,9 @@ ], [ 39, - 19, - 1, - 30, + 32, 0, - "IMAGE" - ], - [ - 40, - 29, - 0, - 21, + 26, 0, "IMAGE" ] @@ -341,13 +391,13 @@ "config": {}, "extra": { "ds": { - "scale": 0.8390550503631276, + "scale": 1.2894499156462411, "offset": [ - -372.4858306734141, - 284.24946587737446 + 386.94731260454324, + 226.3186553038392 ] }, - "frontendVersion": "1.28.7" + "frontendVersion": "1.28.8" }, "version": 0.4 } \ No newline at end of file diff --git a/workflows/normal_grounding.json b/workflows/normal_grounding.json new file mode 100644 index 0000000..2b770cd --- /dev/null +++ b/workflows/normal_grounding.json @@ -0,0 +1,469 @@ +{ + "id": 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