limbicnation
b557c6729e
Steps completed (per abstract-painting-kitten.md): 1. FIX edge_blur_amount float truncation: int→float in MaskParams + removed int() casts 2. Wire invert_mask: INPUT_TYPES, method signatures, Pydantic validation, alpha inversion applied in both AutoGrabCutRemover and GrabCutRefinement success paths 3. Add [B,6] bbox_metadata tensor output to AutoGrabCutRemover RETURN_TYPES 4. nodes.py: @torch.no_grad() on remove_background + batch_remove_background; all .float()→.to(dtype=torch.float32) 5. Structured tests/ suite: conftest.py, test_grabcut_processor.py, test_grabcut_nodes.py, test_nodes.py, test_validation.py Verification: - 48/48 new tests pass - 6/6 original test_grabcut.py tests pass - 4/4 node import test pass - 0 flake8 E9/F63/F7/F82 errors - edge_blur_amount=1.7 correctly stores as float (not truncated to 1) BREAKING: AutoGrabCutRemover RETURN_TYPES changed from 5→6 (bbox_tensor added)
71 lines
2.0 KiB
Python
71 lines
2.0 KiB
Python
"""Shared pytest fixtures for GrabCut and TransparencyBackgroundRemover tests."""
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from __future__ import annotations
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import numpy as np
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import pytest
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import torch
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@pytest.fixture
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def sample_image_rgb() -> np.ndarray:
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"""Return a 256×256 RGB image with a centred green square on white."""
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img = np.full((256, 256, 3), 255, dtype=np.uint8)
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img[80:176, 80:176] = (0, 200, 0) # green square
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return img
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@pytest.fixture
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def sample_image_rgba() -> np.ndarray:
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"""Return a 256×256 RGBA image."""
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img = np.full((256, 256, 4), 255, dtype=np.uint8)
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img[80:176, 80:176, :3] = (200, 0, 0) # red square
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img[80:176, 80:176, 3] = 255
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return img
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@pytest.fixture
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def sample_tensor_bhw3() -> torch.Tensor:
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"""Return a batch-of-2 CHW RGB tensor (2, 3, 256, 256) in [0, 1]."""
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data = np.full((2, 3, 256, 256), 0.5, dtype=np.float32)
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data[:, :, 80:176, 80:176] = 0.0 # dark patch
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return torch.from_numpy(data)
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@pytest.fixture
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def sample_mask_hw() -> np.ndarray:
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"""Return a 256×256 binary mask with a centred filled circle."""
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y, x = np.ogrid[:256, :256]
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mask = ((x - 128) ** 2 + (y - 128) ** 2) < 40 ** 2
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return (mask * 255).astype(np.uint8)
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@pytest.fixture
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def sample_bbox() -> tuple[int, int, int, int]:
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"""Return a typical (x1, y1, x2, y2) bounding box."""
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return (80, 80, 176, 176)
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@pytest.fixture
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def grabcut_processor():
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"""Return a GrabCutProcessor instance with safe defaults."""
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from grabcut_remover import GrabCutProcessor
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return GrabCutProcessor(
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confidence_threshold=0.5,
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iterations=2,
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margin_pixels=10,
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edge_refinement_strength=0.0,
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edge_blur_amount=0.0,
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binary_threshold=200,
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)
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@pytest.fixture
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def fallback_processor():
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"""Return a FallbackGrabCutProcessor (no YOLO)."""
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from grabcut_remover import create_fallback_processor
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return create_fallback_processor()(
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confidence_threshold=0.5,
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iterations=2,
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margin_pixels=10,
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)
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