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# ----------------------------------------------------------------------------
# - Open3D: www.open3d.org -
# ----------------------------------------------------------------------------
# Copyright (c) 2018-2024 www.open3d.org
# SPDX-License-Identifier: MIT
# ----------------------------------------------------------------------------
import open3d as o3d
import open3d.core as o3c
from open3d.t.geometry import Image
import numpy as np
import pytest
import pickle
import tempfile
import sys
import os
sys.path.append(os.path.dirname(os.path.realpath(__file__)) + "/../..")
from open3d_test import list_devices
@pytest.mark.parametrize("device", list_devices())
def test_to_linear_transform(device):
TOL = {"rtol": 1e-7, "atol": 1e-7}
# reference data
input_data = np.array((10, 25, 0, 13, 5, 40), dtype=np.uint8).reshape(
(2, 3, 1))
output_ref = input_data / 255.
negative_image_ref = 1. - input_data / 255.
saturate_ref = np.array((180, 255, 0, 240, 80, 255),
dtype=np.uint8).reshape((2, 3, 1))
t_input = o3c.Tensor(input_data, dtype=o3c.uint8, device=device)
t_input3 = o3c.Tensor(np.broadcast_to(input_data, shape=(2, 3, 3)),
dtype=o3c.uint8,
device=device)
input1 = Image(t_input)
# UInt8 -> Float32: auto scale = 1./255
output1 = input1.to(o3c.float32)
assert output1.dtype == o3c.float32
np.testing.assert_allclose(output1.as_tensor().cpu().numpy(), output_ref,
**TOL)
# 3 channels
input3 = Image(t_input3)
output3 = input3.to(o3c.float32)
np.testing.assert_allclose(output3.as_tensor().cpu().numpy(),
np.broadcast_to(output_ref, (2, 3, 3)), **TOL)
# LinearTransform to negative image
output1.linear_transform(scale=-1, offset=1)
np.testing.assert_allclose(output1.as_tensor().cpu().numpy(),
negative_image_ref)
# 3 channels
output3.linear_transform(scale=-1, offset=1)
np.testing.assert_allclose(output3.as_tensor().cpu().numpy(),
np.broadcast_to(negative_image_ref, (2, 3, 3)),
**TOL)
# UInt8 -> UInt16: auto scale = 1
output1 = input1.to(o3c.uint16)
assert output1.dtype == o3c.uint16
np.testing.assert_allclose(output1.as_tensor().cpu().numpy(), input_data,
**TOL)
# 3 channels
output3 = input3.to(o3c.uint16)
np.testing.assert_allclose(output3.as_tensor().cpu().numpy(),
np.broadcast_to(input_data, (2, 3, 3)), **TOL)
# Saturation to [0, 255]
output1 = input1.linear_transform(scale=20, offset=-20)
np.testing.assert_allclose(output1.as_tensor().cpu().numpy(), saturate_ref,
**TOL)
# 3 channels
output3 = input3.linear_transform(scale=20, offset=-20)
np.testing.assert_allclose(output3.as_tensor().cpu().numpy(),
np.broadcast_to(saturate_ref, (2, 3, 3)), **TOL)
@pytest.mark.parametrize("device", list_devices())
def test_buffer_protocol_cpu(device):
if device.get_type() == o3c.Device.DeviceType.CPU:
# (rows, cols) -> (rows, cols, 1)
src_t = np.array([[0, 1, 2], [3, 4, 5]], dtype=np.float32)
im = Image(o3d.core.Tensor.from_numpy(src_t))
dst_t = np.asarray(im)
np.testing.assert_array_equal(src_t[..., None], dst_t)
# Check that the memory is shared.
dst_t[0, 0, 0] = 100
new_dst_t = np.asarray(im)
np.testing.assert_array_equal(dst_t, new_dst_t)
# (rows, cols, channels) -> (rows, cols, channels)
src_t = np.arange(18, dtype=np.float32).reshape((2, 3, 3))
im = Image(o3d.core.Tensor.from_numpy(src_t))
dst_t = np.asarray(im)
np.testing.assert_array_equal(src_t, dst_t)
# Check that the memory is shared.
dst_t[0, 0, 0] = 100
new_dst_t = np.asarray(im)
np.testing.assert_array_equal(dst_t, new_dst_t)
else:
# (rows, cols) -> (rows, cols, 1)
src_t = np.array([[0, 1, 2], [3, 4, 5]], dtype=np.float32)
im = Image(o3d.core.Tensor.from_numpy(src_t))
im = im.to(device=device)
# Ideally we shall test exception if .cpu() is not called, but
# pytest.raises() cannot catch this exception for some reason.
dst_t = np.asarray(im.cpu())
np.testing.assert_array_equal(src_t[..., None], dst_t)
# (rows, cols, channels) -> (rows, cols, channels)
src_t = np.arange(18, dtype=np.float32).reshape((2, 3, 3))
im = Image(o3d.core.Tensor.from_numpy(src_t))
im = im.to(device=device)
dst_t = np.asarray(im.cpu())
np.testing.assert_array_equal(src_t, dst_t)
@pytest.mark.parametrize("device", list_devices())
def test_pickle(device):
img = Image(o3c.Tensor.ones((10, 10, 3), o3c.uint8, device))
with tempfile.TemporaryDirectory() as temp_dir:
file_name = f"{temp_dir}/img.pkl"
pickle.dump(img, open(file_name, "wb"))
img_load = pickle.load(open(file_name, "rb"))
assert img_load.as_tensor().allclose(img.as_tensor())
assert img_load.device == img.device and img_load.dtype == o3c.uint8
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