402 lines
15 KiB
Python
402 lines
15 KiB
Python
import io
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from pathlib import Path
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import tempfile
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import unittest
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import numpy as np
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from localcast.sensor_fusion import (
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AdaptiveCameraController,
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CameraModel,
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CameraQualityTarget,
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DenseStereoConfig,
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FusionConfig,
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Observation2D,
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PointCloud,
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RenderBridgeConfig,
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RenderFramePacket,
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RenderPointPacket,
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SensorRig,
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SpoutOutputConfig,
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TrackCache,
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frame_to_vertex_array,
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dense_stereo_points,
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get_live_render_frame,
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lower_frame_to_screen_brushes,
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lower_points_to_render_frame,
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overlay_audio_events,
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put_live_render_frame,
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remote_video_artifact_for_present_time,
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)
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from localcast.sensor_fusion.spout_output import rasterize_frame_rgba
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from scripts.live_sensor_fusion import (
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leap_channel_motion_points,
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rgb_dense_stereo_splats,
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rgb_room_splats,
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unpack_leap_packed_channels,
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)
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from audio_field.cultcache_audio import make_audio_source_events, make_spatial_audio_frame
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from localcast.sensor_fusion.adapters import read_raw_bgr_frames
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def camera(sensor_id, x):
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return CameraModel(
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sensor_id=sensor_id,
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camera_matrix=np.array([[300.0, 0.0, 160.0], [0.0, 300.0, 120.0], [0.0, 0.0, 1.0]]),
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dist_coeffs=np.zeros(5),
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world_from_sensor=np.array(
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[
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[1.0, 0.0, 0.0, x],
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[0.0, 1.0, 0.0, 0.0],
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[0.0, 0.0, 1.0, 0.0],
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[0.0, 0.0, 0.0, 1.0],
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]
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),
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width=320,
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height=240,
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)
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class SensorFusionTests(unittest.TestCase):
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def test_triangulates_marker_from_two_calibrated_cameras(self):
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left = camera("left", -0.25)
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right = camera("right", 0.25)
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rig = SensorRig(
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cameras={"left": left, "right": right},
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config=FusionConfig(max_pair_dt_ns=30_000_000, max_reprojection_error_px=0.01),
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)
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target = np.array([0.05, 0.02, 2.0])
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observations = [
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Observation2D("left", "ball", 1_000_000_000, left.project_world(target), 0.9),
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Observation2D("right", "ball", 1_010_000_000, right.project_world(target), 0.8),
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]
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result = rig.fuse(observations)
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self.assertEqual(1, len(result.points))
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np.testing.assert_allclose(target, result.points[0].xyz, atol=1e-9)
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self.assertGreater(result.points[0].confidence, 0.5)
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def test_rejects_observations_outside_time_window(self):
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left = camera("left", -0.25)
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right = camera("right", 0.25)
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rig = SensorRig(cameras={"left": left, "right": right}, config=FusionConfig(max_pair_dt_ns=5))
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target = np.array([0.0, 0.0, 2.0])
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result = rig.fuse(
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[
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Observation2D("left", "ball", 10, left.project_world(target), 1.0),
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Observation2D("right", "ball", 100, right.project_world(target), 1.0),
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]
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)
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self.assertEqual(0, len(result.points))
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self.assertIn("ball: no valid camera pair", result.dropped)
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def test_track_cache_expires_stale_points(self):
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left = camera("left", -0.25)
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right = camera("right", 0.25)
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target = np.array([0.0, 0.0, 2.0])
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point = SensorRig(
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cameras={"left": left, "right": right}
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).fuse(
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[
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Observation2D("left", "ball", 100, left.project_world(target), 1.0),
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Observation2D("right", "ball", 100, right.project_world(target), 1.0),
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]
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).points[0]
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cache = TrackCache(ttl_ns=50)
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cache.update(point)
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cache.expire(120)
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self.assertEqual(1, len(cache.points()))
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cache.expire(200)
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self.assertEqual(0, len(cache.points()))
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def test_point_cloud_writes_ply(self):
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left = camera("left", -0.25)
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right = camera("right", 0.25)
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point = SensorRig(cameras={"left": left, "right": right}).fuse(
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[
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Observation2D("left", "ball", 100, left.project_world(np.array([0.0, 0.0, 2.0])), 1.0),
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Observation2D("right", "ball", 100, right.project_world(np.array([0.0, 0.0, 2.0])), 1.0),
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]
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).points[0]
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class MemoryPath:
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parent = None
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def __init__(self):
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self.text = ""
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def write_text(self, text, encoding):
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self.text = text
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sink = MemoryPath()
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sink.parent = type("Parent", (), {"mkdir": lambda self, parents, exist_ok: None})()
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PointCloud((point,)).write_ply(sink)
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self.assertIn("element vertex 1", sink.text)
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self.assertIn("end_header", sink.text)
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def test_raw_bgr_reader_emits_timestamped_frames(self):
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stream = io.BytesIO(bytes(range(12)))
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frames = list(read_raw_bgr_frames(stream, "eye", width=2, height=2, frame_bytes=12))
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self.assertEqual(1, len(frames))
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self.assertEqual("eye", frames[0].sensor_id)
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self.assertEqual((2, 2, 3), frames[0].image_bgr.shape)
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def test_render_frame_packet_carries_spout_and_audio_alignment_metadata(self):
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left = camera("left", -0.25)
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right = camera("right", 0.25)
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point = SensorRig(cameras={"left": left, "right": right}).fuse(
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[
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Observation2D("left", "ball", 1_000, left.project_world(np.array([0.0, 0.0, 2.0])), 1.0),
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Observation2D("right", "ball", 2_000, right.project_world(np.array([0.0, 0.0, 2.0])), 0.8),
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]
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).points[0]
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config = RenderBridgeConfig(
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spout_sender_name="test-spout",
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visual_delay_ns=100,
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audio_alignment_delay_ns=200,
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default_point_radius_m=0.05,
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)
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frame = lower_points_to_render_frame((point,), config, frame_id=7, created_monotonic_ns=3_000)
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data = frame.to_dict()
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self.assertEqual("localcast.sensor_fusion.render_frame.v1", data["schema"])
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self.assertEqual("test-spout", data["spout_sender_name"])
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self.assertEqual(2_100, data["present_time_ns"])
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self.assertEqual(2_200, data["audio_alignment_time_ns"])
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self.assertEqual(0.05, data["points"][0]["radius_m"])
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loaded = RenderFramePacket.from_dict(data)
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vertices = frame_to_vertex_array(loaded, point_scale=2.0)
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self.assertEqual((1, 8), vertices.shape)
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self.assertAlmostEqual(0.10, float(vertices[0, 7]), places=6)
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self.assertGreater(float(vertices[0, 6]), 0.0)
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brushes = lower_frame_to_screen_brushes(loaded, width=1920, height=1080, point_scale=2.0)
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self.assertEqual(1, len(brushes))
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self.assertGreaterEqual(brushes[0].radii_px[0], brushes[0].radii_px[1])
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def test_spout_output_config_is_importable_without_gpu_context(self):
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config = SpoutOutputConfig(sender_name="unit-test", width=128, height=72, fps=30)
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self.assertEqual("unit-test", config.sender_name)
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self.assertEqual(128, config.width)
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def test_rasterizer_uses_gaussian_envelope_not_solid_ellipse(self):
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frame = RenderFramePacket(
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schema="localcast.sensor_fusion.render_frame.v1",
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frame_id=1,
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created_monotonic_ns=1,
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source_time_min_ns=1,
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source_time_max_ns=1,
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present_time_ns=1,
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audio_alignment_time_ns=1,
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spout_sender_name="test",
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target_width=320,
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target_height=180,
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points=(
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RenderPointPacket(
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stable_key="rgb-splat",
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xyz=np.array([0.0, 0.0, 1.2]),
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radius_m=0.08,
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color_rgba=(1.0, 0.0, 0.0, 1.0),
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confidence=1.0,
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source_timestamp_ns=1,
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),
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),
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)
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image = rasterize_frame_rgba(frame, 320, 180, point_scale=1.0)
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red = image[:, :, 0]
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hot = red[red > 24]
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self.assertGreater(len(hot), 20)
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self.assertGreater(int(hot.max()), 180)
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self.assertGreater(len(np.unique(hot)), 8)
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self.assertTrue(np.any((hot > 40) & (hot < 160)))
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def test_render_frame_round_trips_through_typed_cultcache_doc(self):
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left = camera("left", -0.25)
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right = camera("right", 0.25)
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point = SensorRig(cameras={"left": left, "right": right}).fuse(
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[
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Observation2D("left", "ball", 1_000, left.project_world(np.array([0.0, 0.0, 2.0])), 1.0),
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Observation2D("right", "ball", 1_000, right.project_world(np.array([0.0, 0.0, 2.0])), 1.0),
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]
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).points[0]
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frame = lower_points_to_render_frame((point,), RenderBridgeConfig(), frame_id=3, created_monotonic_ns=10)
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "visual-state.msgpack"
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put_live_render_frame(path, frame)
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loaded = get_live_render_frame(path)
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self.assertIsNotNone(loaded)
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self.assertEqual(3, loaded.frame_id)
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self.assertEqual(1, len(loaded.points))
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self.assertEqual("ball", loaded.points[0].stable_key)
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def test_audio_source_events_overlay_against_audio_alignment_time(self):
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frame = RenderFramePacket(
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schema="localcast.sensor_fusion.render_frame.v1",
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frame_id=9,
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created_monotonic_ns=1_000,
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source_time_min_ns=1_000,
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source_time_max_ns=1_000,
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present_time_ns=1_100,
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audio_alignment_time_ns=1_000_000_000,
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spout_sender_name="test",
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target_width=128,
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target_height=72,
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points=(),
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)
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audio = make_spatial_audio_frame(
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np.zeros((1024, 4), dtype=np.float32),
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frame_id=4,
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sample_rate=48000,
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start_sample=48000,
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audio_time_ns=1_000_000_000,
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)
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events = make_audio_source_events(
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frame_id=5,
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sample_rate=48000,
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start_sample=0,
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frame_count=96000,
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audio_time_ns=0,
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events=[
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{"eventId": 1, "startSample": 48000, "positionMeters": [0.2, 0.3, 1.4], "confidence": 0.9, "energy": 0.001},
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{"eventId": 2, "startSample": 70000, "positionMeters": [2.0, 0.0, 1.0], "confidence": 0.9, "energy": 0.001},
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],
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voice_focus=[],
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)
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augmented, status = overlay_audio_events(frame, events, audio, window_ns=40_000_000)
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self.assertEqual(1, len(augmented.points))
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self.assertEqual("audio-event-1", augmented.points[0].stable_key)
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self.assertTrue(status.synchronized)
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self.assertEqual(1, status.overlay_event_count)
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def test_remote_video_artifact_reports_sync_delta(self):
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artifact = remote_video_artifact_for_present_time(
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source_name="Neighbor PC - Video",
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url="srt://0.0.0.0:5100?mode=listener&latency=120000",
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present_time_ns=1_250_000_000,
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observed_time_ns=1_100_000_000,
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expected_latency_ns=120_000_000,
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tolerance_ns=40_000_000,
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)
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self.assertEqual(30_000_000, artifact.delta_ns)
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self.assertTrue(artifact.synchronized)
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def test_rgb_room_splats_emit_camera_resolved_background(self):
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frame = np.zeros((48, 64, 3), dtype=np.uint8)
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frame[:, :, :] = np.array([48, 72, 96], dtype=np.uint8)
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frame[16:34, 24:40, :] = np.array([240, 240, 240], dtype=np.uint8)
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points = rgb_room_splats(
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"room-rgb:test",
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frame,
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np.array([0.0, -1.0, 1.5]),
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123,
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step=12,
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)
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self.assertGreater(len(points), 0)
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self.assertTrue(all(point.stable_key.startswith("room-rgb:test") for point in points))
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self.assertTrue(any(point.xyz[2] < 0.2 for point in points))
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self.assertTrue(any(point.xyz[1] > 0.7 for point in points))
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def test_leap_packed_map_channels_are_mapped_individually(self):
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packed = np.zeros((12, 12, 3), dtype=np.uint8)
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packed[:, :, 0] = 20
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packed[:, :, 1] = 80
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packed[:, :, 2] = 160
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channels = unpack_leap_packed_channels(packed)
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self.assertAlmostEqual(80 / 255.0, float(channels["green"][0, 0]), places=6)
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self.assertAlmostEqual(160 / 255.0, float(channels["magenta"][0, 0]), places=6)
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self.assertAlmostEqual(20 / 255.0, float(channels["blue"][0, 0]), places=6)
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def test_leap_motion_points_use_channel_identity(self):
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previous = np.zeros((24, 24), dtype=np.float32)
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current = previous.copy()
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current[12, 12] = 1.0
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points = leap_channel_motion_points("green", current, previous, 456, step=12)
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self.assertGreater(len(points), 0)
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self.assertTrue(all(point.stable_key.startswith("leap-motion:green") for point in points))
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self.assertTrue(all(point.source_timestamp_ns == 456 for point in points))
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def test_adaptive_camera_controller_reduces_overexposure(self):
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controller = AdaptiveCameraController(target=CameraQualityTarget(mean_luma=0.5, luma_deadband=0.02))
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command = controller.update(
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quality=type(
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"Quality",
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(),
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{
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"mean_luma": 0.82,
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"dark_clip": 0.0,
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"bright_clip": 0.12,
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"contrast": 0.2,
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"sharpness": 0.2,
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},
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)()
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)
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self.assertTrue(command.changed)
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self.assertIsNotNone(command.exposure)
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self.assertLess(command.exposure, 0.5)
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self.assertIsNotNone(command.gain)
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self.assertLess(command.gain, 0.25)
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def test_dense_stereo_emits_calibrated_rgb_surface_claims(self):
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height, width = 48, 72
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rng = np.random.default_rng(42)
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left_frame = rng.integers(0, 255, size=(height, width, 3), dtype=np.uint8)
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right_frame = np.roll(left_frame, -8, axis=1)
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left = camera("left", -0.25)
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right = camera("right", 0.25)
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left = CameraModel("left", left.camera_matrix, left.dist_coeffs, left.world_from_sensor, width, height)
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right = CameraModel("right", right.camera_matrix, right.dist_coeffs, right.world_from_sensor, width, height)
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points = dense_stereo_points(
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prefix="dense-test",
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left_frame_bgr=left_frame,
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right_frame_bgr=right_frame,
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left_camera=left,
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right_camera=right,
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timestamp_ns=789,
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config=DenseStereoConfig(
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sample_step=8,
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block_radius=2,
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max_disparity_px=16,
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min_ncc=0.55,
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max_reprojection_error_px=200.0,
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),
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)
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self.assertGreater(len(points), 0)
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self.assertTrue(all(point.stable_key.startswith("dense-test") for point in points))
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self.assertTrue(all(point.source_timestamp_ns == 789 for point in points))
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self.assertTrue(any(point.radius_m < 0.01 for point in points))
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def test_live_rgb_sampler_dense_path_uses_camera_pair_before_fallback_surfaces(self):
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height, width = 48, 72
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rng = np.random.default_rng(7)
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primary = rng.integers(0, 255, size=(height, width, 3), dtype=np.uint8)
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secondary = np.roll(primary, -7, axis=1)
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points = rgb_dense_stereo_splats(primary, secondary, 321, step=8)
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self.assertGreater(len(points), 0)
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self.assertTrue(all(point.stable_key.startswith("dense-rgb") for point in points))
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if __name__ == "__main__":
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unittest.main()
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