Don't ship internal only files

Summary: This isn't the real fix it's just moving the files into a folder we can exclude in shipit. See D62289505 where we exclude this directory from shipit. This project is exported to open source (Github) so we need to not ship these files -- I didn't realize this when I wrote the tests.

Reviewed By: jermenkoo

Differential Revision: D62289557

fbshipit-source-id: 60afb00fd8a6aa54aabe12a8a3fcc161a65b0495

test/perception_parity_test.py

-# (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
-from unittest import TestCase
-
-import numpy as np
-import torch as th
-from arvr.projects.facetracking.hmd.pythonbindings.engine import camera_operator
-
-# @manual=fbsource//arvr/projects/codec_avatar/drtk:utils
-from drtk.utils.projection import project_fisheye_distort_62
-
-
-def get_meshgrid_vec(width: int, height: int) -> np.ndarray:
-    image_indices = np.meshgrid(np.arange(width), np.arange(height))
-    image_indices = np.stack(image_indices, axis=-1)
-    return image_indices.reshape(-1, 2).astype(np.float32)
-
-
-def generate_unit_plane(
-    camera: camera_operator.CameraOperator, width: int, height: int
-) -> np.ndarray:
-    image_indices_vec = get_meshgrid_vec(width, height)
-
-    uv_positions_2d = camera.unproject_unit_plane(
-        image_indices_vec, apply_undistortion=False
-    ).astype(np.float64)
-
-    uv_positions_3d = np.concatenate(
-        [
-            uv_positions_2d,
-            np.ones([image_indices_vec.shape[0], 1], dtype=uv_positions_2d.dtype),
-        ],
-        axis=1,
-    )
-    return uv_positions_3d
-
-
-class PerceptionParityTest(TestCase):
-    def setUp(self):
-        np.random.seed(42)
-
-    def test_fisheye62(self) -> None:
-        # Hardcoded fisheye62 with no flips and no LUT
-        n_distortion_parameters = 8
-        width = 100
-        height = 200
-        random_intrinsics = np.eye(4, dtype=np.float64)
-        random_intrinsics[0, 0] = np.random.uniform(low=0.9, high=1.0) * max(
-            height, width
-        )
-        random_intrinsics[1, 1] = random_intrinsics[0, 0]
-        random_intrinsics[0, 2] = np.random.uniform(low=0.4, high=0.6) * width
-        random_intrinsics[1, 2] = np.random.uniform(low=0.4, high=0.6) * height
-        distortion = np.random.uniform(low=-0.1, high=0.1, size=n_distortion_parameters)
-
-        # Crate the perception fisheye62 camera
-        fisheye = camera_operator.CameraOperator.init_with_fisheye(
-            extrinsic_matrix=np.eye(4).astype(np.float64),
-            intrinsic_matrix=random_intrinsics,
-            distortion=distortion,
-            width=width,
-            height=height,
-            name="test",
-            id=12,
-        )
-        self.assertEqual(fisheye.model_type, "FISHEYE62_WITH_BOTH_FOCAL")
-
-        # Create the unprojected points using the perception camera (these are
-        # effectively arbitrary)
-        unit_plane_points = generate_unit_plane(fisheye, width, height)
-
-        perception_output = fisheye.apply_intrinsic(
-            unit_plane_points, apply_distortion=True
-        )
-
-        # Compare with drtk
-        focal = th.tensor(fisheye.intrinsic_matrix[:2, :2], dtype=th.float)
-        drtk_output = project_fisheye_distort_62(
-            th.tensor(unit_plane_points, dtype=th.float).unsqueeze(0),
-            th.diag_embed(th.diagonal(focal)).unsqueeze(0),
-            th.tensor(
-                [
-                    fisheye.principal_point_x,
-                    fisheye.principal_point_y,
-                ],
-                dtype=th.float,
-            ).unsqueeze(0),
-            th.tensor(fisheye.distortion, dtype=th.float).unsqueeze(0),
-        )
-
-        np.testing.assert_allclose(
-            perception_output, drtk_output.squeeze(0).numpy(), atol=1e-4, rtol=1e-4
-        )