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#############################################################################
#
# ViSP, open source Visual Servoing Platform software.
# Copyright (C) 2005 - 2025 by Inria. All rights reserved.
#
# This software is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
# See the file LICENSE.txt at the root directory of this source
# distribution for additional information about the GNU GPL.
#
# For using ViSP with software that can not be combined with the GNU
# GPL, please contact Inria about acquiring a ViSP Professional
# Edition License.
#
# See https://visp.inria.fr for more information.
#
# This software was developed at:
# Inria Rennes - Bretagne Atlantique
# Campus Universitaire de Beaulieu
# 35042 Rennes Cedex
# France
#
# If you have questions regarding the use of this file, please contact
# Inria at visp@inria.fr
#
# This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
# WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
#
# Description:
# ViSP Python bindings test
#
#############################################################################
from typing import Any, List, Dict
from visp.core import ImageGray, ImageRGBa, ImageRGBf, RGBa, RGBf
import numpy as np
import pytest
def get_data_dicts() -> List[Dict[str, Any]]:
h, w = 20, 20
return [
{
'instance': ImageGray(h, w, 0),
'base_value': 0,
'value': 255,
'np_value': 255,
'shape': (h, w),
'dtype': np.uint8
},
{
'instance': ImageRGBa(h, w, RGBa(0, 50, 75, 255)),
'base_value': RGBa(0, 50, 75, 255),
'value': RGBa(255, 128, 0, 100),
'np_value': np.asarray([255, 128, 0, 100], dtype=np.uint8),
'shape': (h, w, 4),
'dtype': np.uint8
},
{
'instance': ImageRGBf(h, w, RGBf(0.0, 0.0, 0.0)),
'base_value': RGBf(0.0, 0.0, 0.0),
'value': RGBf(255, 0, 0),
'np_value': np.asarray([255, 0, 0], dtype=np.float32),
'shape': (h, w, 3),
'dtype': np.float32
},
]
def test_np_array_shape_type():
'''
Tests buffer definition, shape and dtype
'''
for test_dict in get_data_dicts():
np_array = np.array(test_dict['instance'], copy=False)
assert np_array.shape == test_dict['shape']
assert np_array.dtype == test_dict['dtype']
def test_np_array_shape_type_numpy_fn():
'''
Tests converting to a numpy array by calling our defined function
'''
for test_dict in get_data_dicts():
np_array = test_dict['instance'].numpy()
assert np_array.shape == test_dict['shape']
assert np_array.dtype == test_dict['dtype']
def test_np_array_replace_value():
'''
Tests 2D pixel indexing and correspondance between visp pixel reps and numpy reps
'''
for test_dict in get_data_dicts():
vp_image = test_dict['instance']
np_array = np.array(vp_image, copy=False)
np_array[::2, ::2] = test_dict['np_value']
for i in range(vp_image.getHeight()):
for j in range(vp_image.getWidth()):
if i % 2 == 0 and j % 2 == 0:
assert vp_image[i, j] == test_dict['value']
assert vp_image[-i, -j] == test_dict['value']
else:
assert vp_image[i, j] == test_dict['base_value']
assert vp_image[-i, -j] == test_dict['base_value']
with pytest.raises(RuntimeError):
vp_image[vp_image.getHeight()]
with pytest.raises(RuntimeError):
vp_image[0, vp_image.getWidth()]
with pytest.raises(RuntimeError):
vp_image[-vp_image.getHeight() - 1]
with pytest.raises(RuntimeError):
vp_image[0, -vp_image.getWidth() - 1]
def test_setitem_with_single_value():
for test_dict in get_data_dicts():
vp_image = test_dict['instance']
# 2D indexing (basic)
vp_image[0, 0] = test_dict['base_value']
assert vp_image[0, 0] == test_dict['base_value']
vp_image[0, 0] = test_dict['value']
assert vp_image[0, 0] == test_dict['value']
# Replace a row
vp_image[1] = test_dict['value']
for i in range(vp_image.getCols()):
assert vp_image[1, i] == test_dict['value']
# Replace a row
vp_image[:] = test_dict['value']
for i in range(vp_image.getRows()):
for j in range(vp_image.getCols()):
assert vp_image[i, j] == test_dict['value']
# Replace rows with a slice
vp_image[:] = test_dict['base_value']
vp_image[::2] = test_dict['value']
for i in range(vp_image.getRows()):
v = test_dict['base_value'] if i % 2 == 1 else test_dict['value']
for j in range(vp_image.getCols()):
assert vp_image[i, j] == v
vp_image[:] = test_dict['base_value']
vp_image[2:-2:2] = test_dict['value']
for i in range(vp_image.getRows()):
v = test_dict['base_value'] if i % 2 == 1 or i >= vp_image.getRows() - 2 or i < 2 else test_dict['value']
for j in range(vp_image.getCols()):
assert vp_image[i, j] == v
vp_image[:, :] = test_dict['base_value']
for i in range(vp_image.getRows()):
for j in range(vp_image.getCols()):
assert vp_image[i, j] == test_dict['base_value']
# Indexing with two slices
vp_image[2:-2:2, 3:-3] = test_dict['value']
for i in range(vp_image.getRows()):
is_v = i >= 2 and i % 2 == 0 and i < vp_image.getRows() - 2
for j in range(vp_image.getCols()):
is_vj = is_v and j >= 3 and j < vp_image.getCols() - 3
v = test_dict['value'] if is_vj else test_dict['base_value']
assert vp_image[i, j] == v
# Negative step not supported
with pytest.raises(RuntimeError):
vp_image[::-1] = test_dict['value']
with pytest.raises(RuntimeError):
vp_image[:, ::-1] = test_dict['value']
# Wrong start and end values
with pytest.raises(RuntimeError):
vp_image[2:1] = test_dict['value']
with pytest.raises(RuntimeError):
vp_image[:, 3:2] = test_dict['value']
def test_setitem_with_numpy_raw_image():
h, w = 30, 20
I = ImageGray(h, w, 0)
single_row = np.ones((w, ), dtype=np.uint8) * 255
I[2] = single_row
assert not np.any(np.equal(I.numpy()[list(set(range(h)) - {2})], single_row))
assert np.all(np.equal(I.numpy()[2], single_row))
I[:] = 0
I[1:-2] = single_row
assert np.all(np.equal(I.numpy()[list(set(range(h)) - {0, h - 2, h - 1})], single_row))
assert np.all(np.equal(I.numpy()[[0, h - 2, h - 1]], 0))
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