ykcheungab
67 lines
2.2 KiB
Python
67 lines
2.2 KiB
Python
import os
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import numpy as np
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def _collect_vnormal_sequence(sensor, frames: int) -> np.ndarray:
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seq = []
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for _ in range(frames):
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img = sensor.get_img()
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assert img is not None
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sensor.compute_deformation(check_motion=False)
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(vnormal,) = sensor.read_info(sensor.info.VNORMAL)
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seq.append(vnormal.copy())
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return np.asarray(seq)
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def test_available_backends_smoke(sensor_factory, available_backends):
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for backend in available_backends:
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sensor = sensor_factory(backend=backend)
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try:
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img = sensor.get_img()
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assert img is not None
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sensor.compute_deformation(check_motion=False)
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flow, vnormal, vshear = sensor.read_info(
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sensor.info.VRAW,
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sensor.info.VNORMAL,
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sensor.info.VSHEAR,
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)
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assert flow.shape == vnormal.shape == vshear.shape
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assert flow.shape[-1] == 2
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assert np.isfinite(flow).all()
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assert np.isfinite(vnormal).all()
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assert np.isfinite(vshear).all()
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finally:
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sensor.disconnect()
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def test_backend_parity_against_cpu(sensor_factory, available_backends):
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if len(available_backends) <= 1:
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return
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compare_frames = int(os.getenv("ORISYS_PARITY_FRAMES", "30"))
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warmup = int(os.getenv("ORISYS_PARITY_WARMUP", "5"))
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tol = float(os.getenv("ORISYS_PARITY_REL_TOL", "2.0"))
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cpu_sensor = sensor_factory(backend="cpu")
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try:
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cpu_seq = _collect_vnormal_sequence(cpu_sensor, compare_frames)
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finally:
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cpu_sensor.disconnect()
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cpu_ref = cpu_seq[warmup:].mean(axis=0)
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cpu_scale = float(np.mean(np.abs(cpu_ref))) + 1e-6
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for backend in available_backends:
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if backend == "cpu":
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continue
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sensor = sensor_factory(backend=backend)
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try:
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seq = _collect_vnormal_sequence(sensor, compare_frames)
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finally:
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sensor.disconnect()
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cand_ref = seq[warmup:].mean(axis=0)
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rel = float(np.mean(np.abs(cand_ref - cpu_ref)) / cpu_scale)
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assert rel < tol, f"{backend} parity drift too high: relative_error={rel:.4f}, tol={tol}"
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