def test_tiff_io(self):
'''Round-trip TIFF test that checks both dimensions and contents.'''
w, h = 1000, 600
rgb = np.zeros((h, w, 3), np.uint8)
range = np.full((int(h / 2), int(w / 2)), 2.0, np.float32)
multi = MultiImageTiff({
MultiImagePageType.RGB: rgb,
MultiImagePageType.Depth: range
})
tiff_path = os.path.join(self.temp_directory,
'test-multi_image_tests1.tif')
multi.save(tiff_path, near=1.0)
read_near1 = MultiImageTiff.load(tiff_path)
tiff_path2 = os.path.join(self.temp_directory,
'test-multi_image_tests2.tif')
multi.save(tiff_path2, near=2.0)
read_near2 = MultiImageTiff.load(tiff_path2)
self.assertEqual(read_near1.rgb.shape, (h, w, 3))
self.assertEqual(read_near1.range.shape, (h / 2, w / 2))
np.testing.assert_array_equal(read_near1.rgb, multi.rgb)
np.testing.assert_array_almost_equal(read_near1.range,
multi.range,
decimal=4)
np.testing.assert_array_almost_equal(read_near1.range,
read_near2.range,
decimal=4)
def test_tiff_read(self):
tiff_path = os.path.join(PATH, 'checkered360-rgbd.tif')
multi = MultiImageTiff.load(tiff_path)
w, h = 360, 180
self.assertEqual(multi.rgb.shape, (h, w, 3))
self.assertEqual(multi.range.shape, (h / 2, w / 2))
# Check that range in middle of image is indeed ~ 5 m.
# agreeing with generated image from 360rgbd01_generate.ipynb
self.assertAlmostEqual(multi.range[int(h / 4), int(w / 4)],
5.0,
places=0)
def test_inverse_range(self):
w, h = 100, 60
rgb = np.zeros((h, w, 3), np.uint8)
inverse_range = np.full((h, w), 200, np.uint16)
range = depth_image_of_inverse_depth_map(inverse_range)
page_map = {
MultiImagePageType.RGB: rgb,
MultiImagePageType.InverseDepth: inverse_range
}
multi = MultiImageTiff(page_map)
tiff_path = os.path.join(self.temp_directory, 'test-invdepth.tiff')
multi.save(tiff_path)
read_inverse_range = MultiImageTiff.load(tiff_path)
np.testing.assert_array_almost_equal(read_inverse_range.range, range)
def test_tiff_read_failure(self):
with self.assertRaises(RuntimeError):
MultiImageTiff.load("dummy")
print('unitize(Vector3(100, 201, 50)): ', unitize(Vector3(100, 201, 50)))
# rot3_tests
from sumo.geometry.rot3 import Rot3, ENU_R_CAMERA
import numpy as np
wRc = np.transpose(np.array([[1, 0, 0], [0, 0, -1], [0, 1, 0]], dtype=float))
rot = Rot3(wRc)
print(rot.matrix())
# MultiImageTiff
from sumo.geometry.inverse_depth import depth_image_of_inverse_depth_map
from sumo.images.multi_image_tiff import MultiImageTiff, MultiImagePageType
tiff_path = parutil.get_file_path(
'/mnt/lustre/sunjiankai/Dataset/sample_data/sumo-input/sumo-input.tif')
multi = MultiImageTiff.load(tiff_path)
print('multi.rgb.shape: ', multi.rgb.shape, 'multi.range.shape (Depth): ',
multi.range.shape, 'multi.category.shape (Category): ',
multi.category.shape, 'multi.instance.shape (Instance): ',
multi.instance.shape)
# multi.rgb.shape: (1024, 6144, 3) multi.range.shape: (1024, 6144) multi.category.shape: (1024, 6144) multi.instance.shape: (1024, 6144)
from sumo.semantic.project_converter import ProjectConverter
from sumo.semantic.project_scene import ProjectScene
glb_path = parutil.get_file_path(
'/mnt/lustre/sunjiankai/Dataset/sample_data/sumo-output')
meshes_model = ProjectScene.load(glb_path, "bounding_box_sample")
bbox_model = ProjectConverter().run(meshes_model, "bounding_box")
print('bbox_model.elements[\'1087\'].bounds.corners():\n',
bbox_model.elements['1087'].bounds.corners())