ykcheungab
ad7b0d3e26
錯位模組畫面有 6x3 共 18 格，原本只能靠過渡門檻碰巧湊到 15 格且選錯格。stitcher.exclude_x 只篩選格子，box 設定為 [0, 240]，可依感測器改寫；合成畫面測試與實機連續開啟 6 次全數成功。 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
211 lines
6.8 KiB
Python
211 lines
6.8 KiB
Python
"""Unit tests for orisys.stitch (synthetic tiles, no camera)."""
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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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from orisys.frame_processors import CompoundEyeFrameProcessor
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from orisys.stitch import (
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StitchStatus,
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get_blend_backend,
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paste_tile_clipped,
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resolve_blend_mode,
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tile_weight_map,
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)
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from orisys.stitch.backends.numpy_backend import blend_kernel_numpy
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from orisys.stitch.config import numba_blend_available, validate_box_grid
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from orisys.stitch.ops import compute_final_crop_rect, coverage_ratio
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from orisys.Stitcher import Stitcher
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def _solid_tile(val: int, h=32, w=32):
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return np.full((h, w, 3), val, dtype=np.uint8)
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def test_tile_weight_map_edges_are_low():
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wmap = tile_weight_map(32, 32, margin=4)
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assert wmap.shape == (32, 32)
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assert wmap.dtype == np.float32
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assert float(wmap[0, 0]) < float(wmap[16, 16])
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assert float(wmap[16, 16]) == pytest.approx(1.0)
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def test_paste_tile_clipped_and_coverage():
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canvas = np.zeros((40, 40, 3), dtype=np.uint8)
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cov = np.zeros((40, 40), dtype=np.uint8)
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tile = _solid_tile(200, 10, 10)
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paste_tile_clipped(canvas, tile, 5, 5, cov=cov)
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assert int(canvas[5, 5, 0]) == 200
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assert int(cov[5, 5]) == 1
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assert int(cov[0, 0]) == 0
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def test_blend_kernel_numpy_first_paint():
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blend = np.zeros((4, 4, 3), dtype=np.float32)
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wsum = np.zeros((4, 4), dtype=np.float32)
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cov = np.zeros((4, 4), dtype=np.uint8)
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src = np.ones((4, 4, 3), dtype=np.float32) * 50
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weight = np.ones((4, 4), dtype=np.float32)
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blend_kernel_numpy(blend, wsum, cov, src, weight)
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assert np.allclose(blend, 50)
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assert np.all(cov == 1)
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def test_numpy_backend_blend_tile():
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backend = get_blend_backend("numpy")
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blend = np.zeros((20, 20, 3), dtype=np.float32)
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wsum = np.zeros((20, 20), dtype=np.float32)
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cov = np.zeros((20, 20), dtype=np.uint8)
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src = np.full((8, 8, 3), 40, dtype=np.uint8)
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weight = tile_weight_map(8, 8, margin=2)
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backend.blend_tile_inplace(blend, wsum, cov, src, weight, 2, 3)
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assert float(blend[4, 5, 0]) > 0
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assert coverage_ratio(cov) > 0
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@pytest.mark.skipif(not numba_blend_available(), reason="numba blend unavailable")
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def test_numba_numpy_backend_parity():
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numpy_b = get_blend_backend("numpy")
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numba_b = get_blend_backend("numba")
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shape = (16, 16)
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src = np.random.randint(0, 255, (*shape, 3), dtype=np.uint8)
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weight = tile_weight_map(*shape, margin=3)
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def run(backend):
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blend = np.zeros((*shape, 3), dtype=np.float32)
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wsum = np.zeros(shape, dtype=np.float32)
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cov = np.zeros(shape, dtype=np.uint8)
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backend.blend_tile_inplace(blend, wsum, cov, src, weight, 0, 0)
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return blend, cov
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b0, c0 = run(numpy_b)
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b1, c1 = run(numba_b)
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assert np.allclose(b0, b1, atol=1e-2)
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assert np.array_equal(c0, c1)
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def test_resolve_blend_mode_default(monkeypatch):
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monkeypatch.delenv("ORISYS_STITCH_BLEND", raising=False)
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monkeypatch.delenv("ORISYS_STITCH_BLEND_BACKEND", raising=False)
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mode, fell = resolve_blend_mode({})
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assert mode == "none"
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assert fell is False
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def test_validate_box_grid():
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assert validate_box_grid([(0, 0, 1, 1)] * 9, 3, 3)
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assert not validate_box_grid([(0, 0, 1, 1)] * 8, 3, 3)
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def test_compute_final_crop_rect():
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cov = np.zeros((20, 20), dtype=np.uint8)
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cov[4:16, 4:16] = 1
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rect = compute_final_crop_rect(cov)
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assert rect is not None
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y0, y1, x0, x1 = rect
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assert y1 > y0 and x1 > x0
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def _mini_config():
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return {
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"min_area_frac": 0.01,
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"max_area_frac": 0.05,
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"max_aspect_ratio": 50,
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"index": [0, 1, 2, 3, 4, 5, 6, 7, 8],
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"margin": 10,
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"nominal_ov_pos": 100,
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"n": [3, 3],
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"row_tol": 0.6,
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"box_size": [32, 32],
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"blend": "numpy",
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"n_boxes_target": 9,
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}
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def test_stitcher_status_and_rt_with_synthetic_tiles():
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stitcher = Stitcher(isstitch=True, config_stitcher=_mini_config(), verbose=False)
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# Preload tiles as if extract_tiles already ran.
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tiles = [_solid_tile(30 + i * 10) for i in range(9)]
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stitcher.tile_list = tiles
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stitcher.units = [(0, 0, t) for t in tiles]
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stitcher.boxes = [(i * 40, 0, i * 40 + 32, 32) for i in range(9)]
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status = stitcher.status
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assert isinstance(status, StitchStatus)
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assert status.blend_mode == "numpy"
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assert status.expected_boxes == 9
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# Feature matching on flat solid tiles usually fails → None is OK.
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out = stitcher.stitch_rt_optimized()
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assert out is None or (isinstance(out, np.ndarray) and out.ndim == 3)
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def test_compound_eye_processor_calls_stitcher():
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class FakeStitcher:
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def __init__(self):
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self.calls = []
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def get_stitch_unit(self, frame):
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self.calls.append("get")
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def extract_tiles(self):
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self.calls.append("extract")
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def stitch_rt_optimized(self):
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self.calls.append("stitch")
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return np.zeros((8, 8, 3), dtype=np.uint8)
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fake = FakeStitcher()
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proc = CompoundEyeFrameProcessor(fake)
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out = proc.process(np.zeros((64, 64, 3), dtype=np.uint8))
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assert fake.calls == ["get", "extract", "stitch"]
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assert out.shape == (8, 8, 3)
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def test_unknown_backend_raises():
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with pytest.raises(ValueError):
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get_blend_backend("torch")
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def _six_by_three_frame():
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"""A 1920x1080 frame showing 6x3 tiles: one column more than the 15 detected."""
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img = np.zeros((1080, 1920, 3), dtype=np.uint8)
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for cx in (160, 470, 790, 1110, 1430, 1750):
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for cy in (180, 520, 860):
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img[cy - 120:cy + 120, cx - 120:cx + 120] = 200
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return img
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def _detect(img, **kwargs):
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from orisys.stitch.boxes import detect_nonblack_regions
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return detect_nonblack_regions(
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img, box_size=(250, 250), min_area_frac=0.01, max_area_frac=0.05,
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max_aspect_ratio=50, save_preview_path="", **kwargs,
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)
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def test_an_extra_tile_column_is_counted_without_an_exclusion():
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n_boxes, _boxes = _detect(_six_by_three_frame())
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assert n_boxes == 18
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@pytest.mark.parametrize("exclude_x", [(330, 0), (0, 330)])
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def test_exclude_x_masks_out_the_extra_column(exclude_x):
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n_boxes, boxes = _detect(_six_by_three_frame(), exclude_x=exclude_x)
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assert n_boxes == 15
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centres = sorted({(x0 + x1) // 2 for x0, _y0, x1, _y1 in boxes})
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assert (160 not in centres) == (exclude_x[0] > 0)
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assert (1750 not in centres) == (exclude_x[1] > 0)
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def test_the_shipped_right_margin_keeps_an_aligned_module():
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"""[0, 240] drops an extra edge column but not the outer column of a 5x3 module."""
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img = np.zeros((1080, 1920, 3), dtype=np.uint8)
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for cx in (324, 642, 960, 1278, 1596):
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for cy in (180, 520, 860):
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img[cy - 120:cy + 120, cx - 120:cx + 120] = 200
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assert _detect(img, exclude_x=(0, 240))[0] == 15
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assert _detect(_six_by_three_frame(), exclude_x=(0, 240))[0] == 15
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