############################################################################# # # 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))