Refactor and enhance DA3 and BEN2 debug panels, introduce mesh export functionality
- Renamed DA3 and BEN2 debug panels for clarity and consistency. - Added a new function to draw DA3 input settings to reduce code duplication. - Implemented mesh export functionality, including confidence thresholding and edge filtering. - Updated export format options to include new mesh type and adjusted related properties. - Enhanced job handling to move generated inputs into job root and manage temporary directories. - Improved error handling and file management during export processes. - Added unit tests for new mesh functionality and ensured existing tests cover changes.
This commit is contained in:
@@ -474,6 +474,38 @@ class WorkerTest(unittest.TestCase):
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)
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self.assertEqual(result, [npz_path])
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def test_move_exported_file_retries_windows_file_lock(self):
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with tempfile.TemporaryDirectory() as directory:
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root = Path(directory)
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source = root / "source.npz"
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destination = root / "destination.npz"
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source.touch()
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path_type = type(source)
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original_replace = path_type.replace
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calls = 0
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def locked_once(path, target):
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nonlocal calls
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calls += 1
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if calls == 1:
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error = PermissionError("file is in use")
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error.winerror = 32
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raise error
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return original_replace(path, target)
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with patch.object(path_type, "replace", new=locked_once), patch.object(
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self.worker.time,
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"sleep",
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) as sleep:
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result = self.worker.move_exported_file(
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source,
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destination,
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)
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self.assertEqual(result, destination)
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self.assertTrue(destination.is_file())
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sleep.assert_called_once_with(0.1)
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def test_rejects_unsupported_input_file(self):
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with tempfile.TemporaryDirectory() as directory:
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input_path = Path(directory) / "input.txt"
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@@ -850,9 +882,10 @@ class WorkerTest(unittest.TestCase):
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self.assertEqual(status["progress"], 1.0)
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self.assertIn("3 frame", status["message"])
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def test_uses_official_da3_export_parameters_for_all_four_formats(self):
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def test_uses_da3_export_parameters_for_formats_and_debug_mesh(self):
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inference_options = []
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export_calls = []
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mesh_calls = []
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class FakeModel:
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@classmethod
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@@ -910,6 +943,27 @@ class WorkerTest(unittest.TestCase):
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fake_package = ModuleType("depth_anything_3")
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fake_package.__path__ = []
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def fake_mesh_export(
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prediction,
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images,
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output_directory,
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confidence_percentile,
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filter_edges,
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max_edge_length,
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):
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mesh_calls.append(
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(
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prediction,
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images,
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confidence_percentile,
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filter_edges,
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max_edge_length,
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)
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)
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output_path = Path(output_directory) / "mesh.glb"
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output_path.touch()
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return output_path
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with tempfile.TemporaryDirectory() as directory:
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root = Path(directory)
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input_path = root / "input.png"
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@@ -923,6 +977,10 @@ class WorkerTest(unittest.TestCase):
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"depth_anything_3.utils": fake_utils,
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"depth_anything_3.utils.export": fake_export_module,
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},
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), patch.object(
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self.worker,
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"export_textured_mesh_glb",
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side_effect=fake_mesh_export,
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):
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for export_format in self.worker.EXPORT_FORMATS:
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args = SimpleNamespace(
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@@ -941,6 +999,8 @@ class WorkerTest(unittest.TestCase):
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num_max_points=12345,
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show_cameras=0,
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gs_views_interval=2,
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mesh_filter_edges=True,
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mesh_max_edge_length=0.2,
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)
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self.worker.reconstruct(args)
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status = json.loads(
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@@ -948,9 +1008,17 @@ class WorkerTest(unittest.TestCase):
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)
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self.assertEqual(status["progress"], 1.0)
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self.assertIn(export_format, status["message"])
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result_directory = Path(args.output_dir)
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if export_format == "gs_ply":
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self.assertTrue((result_directory / "0000.ply").is_file())
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self.assertFalse((result_directory / "gs_ply").exists())
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if export_format == "depth_vis":
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self.assertTrue((result_directory / "0000.jpg").is_file())
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self.assertFalse((result_directory / "depth_vis").exists())
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self.assertEqual(len(inference_options), 4)
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self.assertEqual(len(inference_options), 5)
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self.assertEqual(len(export_calls), 4)
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self.assertEqual(len(mesh_calls), 1)
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for images, options in inference_options:
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self.assertEqual(images, [str(input_path)])
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self.assertEqual(options["process_res"], 518)
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@@ -960,8 +1028,15 @@ class WorkerTest(unittest.TestCase):
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)
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self.assertTrue(options["use_ray_pose"])
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self.assertEqual(options["ref_view_strategy"], "middle")
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for _prediction, export_format, _export_dir, options in export_calls:
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expected_depth = -1.0 if export_format == "mini_npz" else 2.0
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for (
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_prediction,
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export_format,
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_export_dir,
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options,
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) in export_calls:
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expected_depth = (
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-1.0 if export_format == "mini_npz" else 2.0
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)
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np.testing.assert_array_equal(
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_prediction.depth,
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np.full((1, 2, 2), expected_depth, dtype=np.float32),
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@@ -985,9 +1060,14 @@ class WorkerTest(unittest.TestCase):
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)
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else:
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self.assertEqual(options, {})
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self.assertEqual(mesh_calls[0][1], [input_path])
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self.assertEqual(mesh_calls[0][2:], (35.0, True, 0.2))
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infer_gs_values = [options["infer_gs"] for _, options in inference_options]
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self.assertEqual(infer_gs_values, [False, True, False, False])
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self.assertEqual(
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infer_gs_values,
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[False, True, False, False, False],
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)
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def test_reconstruct_copies_frames_for_multi_frame_input(self):
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class FakeModel:
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@@ -1080,6 +1160,74 @@ class WorkerTest(unittest.TestCase):
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status = json.loads(Path(args.status).read_text(encoding="utf-8"))
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self.assertEqual(status["progress"], 1.0)
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def test_mesh_confidence_uses_percentile(self):
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depth = np.ones((1, 2, 2), dtype=np.float32)
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confidence = np.array([[[1.0, 2.0], [3.0, 4.0]]])
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threshold = self.worker.confidence_percentile_threshold(
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depth,
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confidence,
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50.0,
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)
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self.assertEqual(threshold, 2.5)
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def test_mesh_faces_apply_confidence_threshold_and_face_direction(self):
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points = np.array(
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[
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[[0.0, 0.0, 1.0], [1.0, 0.0, 1.0], [2.0, 0.0, 1.0]],
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[[0.0, 1.0, 1.0], [1.0, 1.0, 1.0], [2.0, 1.0, 1.0]],
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],
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dtype=np.float32,
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)
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depth = np.ones((2, 3), dtype=np.float32)
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confidence = np.ones((2, 3), dtype=np.float32)
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confidence[:, 0] = 0.0
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faces = self.worker.mesh_triangle_faces(
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points,
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depth,
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confidence,
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confidence_threshold=0.5,
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filter_edges=False,
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max_edge_length=0.0,
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)
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np.testing.assert_array_equal(faces, [[1, 4, 5], [1, 5, 2]])
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vertices = points.reshape(-1, 3)[faces[0]]
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normal = np.cross(
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vertices[1] - vertices[0],
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vertices[2] - vertices[0],
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)
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self.assertLess(normal[2], 0.0)
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def test_mesh_percentile_reduces_face_count(self):
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depth = np.ones((3, 3), dtype=np.float32)
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confidence = np.arange(1, 10, dtype=np.float32).reshape(3, 3)
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x, y = np.meshgrid(
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np.arange(3, dtype=np.float32),
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np.arange(3, dtype=np.float32),
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)
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points = np.stack((x, y, depth), axis=-1)
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face_counts = []
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for percentile in (0.0, 50.0, 100.0):
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threshold = self.worker.confidence_percentile_threshold(
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depth,
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confidence,
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percentile,
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)
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faces = self.worker.mesh_triangle_faces(
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points,
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depth,
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confidence,
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confidence_threshold=threshold,
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filter_edges=False,
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max_edge_length=0.0,
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)
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face_counts.append(len(faces))
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self.assertEqual(face_counts, [8, 2, 0])
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if __name__ == "__main__":
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unittest.main()
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