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| # Tencent is pleased to support the open source community by making ncnn available. | |
| # | |
| # Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved. | |
| # | |
| # Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | |
| # in compliance with the License. You may obtain a copy of the License at | |
| # | |
| # https://opensource.org/licenses/BSD-3-Clause | |
| # | |
| # Unless required by applicable law or agreed to in writing, software distributed | |
| # under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR | |
| # CONDITIONS OF ANY KIND, either express or implied. See the License for the | |
| # specific language governing permissions and limitations under the License. | |
| import sys | |
| import numpy as np | |
| import pytest | |
| import ncnn | |
| def test_mat_dims1(): | |
| mat = ncnn.Mat(1) | |
| assert mat.dims == 1 and mat.w == 1 | |
| mat = ncnn.Mat(2, elemsize=4) | |
| assert mat.dims == 1 and mat.w == 2 and mat.elemsize == 4 | |
| mat = ncnn.Mat(3, elemsize=4, elempack=1) | |
| assert mat.dims == 1 and mat.w == 3 and mat.elemsize == 4 and mat.elempack == 1 | |
| mat = ncnn.Mat(4, elemsize=4, elempack=1, allocator=None) | |
| assert ( | |
| mat.dims == 1 | |
| and mat.w == 4 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| and mat.allocator == None | |
| ) | |
| mat = ncnn.Mat((1,)) | |
| assert mat.dims == 1 and mat.w == 1 | |
| mat = ncnn.Mat((2,), elemsize=4) | |
| assert mat.dims == 1 and mat.w == 2 and mat.elemsize == 4 | |
| mat = ncnn.Mat((3,), elemsize=4, elempack=1) | |
| assert mat.dims == 1 and mat.w == 3 and mat.elemsize == 4 and mat.elempack == 1 | |
| mat = ncnn.Mat((4,), elemsize=4, elempack=1, allocator=None) | |
| assert ( | |
| mat.dims == 1 | |
| and mat.w == 4 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| and mat.allocator == None | |
| ) | |
| def test_mat_dims2(): | |
| mat = ncnn.Mat(1, 2) | |
| assert mat.dims == 2 and mat.w == 1 and mat.h == 2 | |
| mat = ncnn.Mat(3, 4, elemsize=4) | |
| assert mat.dims == 2 and mat.w == 3 and mat.h == 4 and mat.elemsize == 4 | |
| mat = ncnn.Mat(5, 6, elemsize=4, elempack=1) | |
| assert ( | |
| mat.dims == 2 | |
| and mat.w == 5 | |
| and mat.h == 6 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| ) | |
| mat = ncnn.Mat(7, 8, elemsize=4, elempack=1, allocator=None) | |
| assert ( | |
| mat.dims == 2 | |
| and mat.w == 7 | |
| and mat.h == 8 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| and mat.allocator == None | |
| ) | |
| mat = ncnn.Mat((1, 2)) | |
| assert mat.dims == 2 and mat.w == 1 and mat.h == 2 | |
| mat = ncnn.Mat((3, 4), elemsize=4) | |
| assert mat.dims == 2 and mat.w == 3 and mat.h == 4 and mat.elemsize == 4 | |
| mat = ncnn.Mat((5, 6), elemsize=4, elempack=1) | |
| assert ( | |
| mat.dims == 2 | |
| and mat.w == 5 | |
| and mat.h == 6 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| ) | |
| mat = ncnn.Mat((7, 8), elemsize=4, elempack=1, allocator=None) | |
| assert ( | |
| mat.dims == 2 | |
| and mat.w == 7 | |
| and mat.h == 8 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| and mat.allocator == None | |
| ) | |
| def test_mat_dims3(): | |
| mat = ncnn.Mat(1, 2, 3) | |
| assert mat.dims == 3 and mat.w == 1 and mat.h == 2 and mat.c == 3 | |
| mat = ncnn.Mat(4, 5, 6, elemsize=4) | |
| assert ( | |
| mat.dims == 3 and mat.w == 4 and mat.h == 5 and mat.c == 6 and mat.elemsize == 4 | |
| ) | |
| mat = ncnn.Mat(7, 8, 9, elemsize=4, elempack=1) | |
| assert ( | |
| mat.dims == 3 | |
| and mat.w == 7 | |
| and mat.h == 8 | |
| and mat.c == 9 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| ) | |
| mat = ncnn.Mat(10, 11, 12, elemsize=4, elempack=1, allocator=None) | |
| assert ( | |
| mat.dims == 3 | |
| and mat.w == 10 | |
| and mat.h == 11 | |
| and mat.c == 12 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| and mat.allocator == None | |
| ) | |
| mat = ncnn.Mat((1, 2, 3)) | |
| assert mat.dims == 3 and mat.w == 1 and mat.h == 2 and mat.c == 3 | |
| mat = ncnn.Mat((4, 5, 6), elemsize=4) | |
| assert ( | |
| mat.dims == 3 and mat.w == 4 and mat.h == 5 and mat.c == 6 and mat.elemsize == 4 | |
| ) | |
| mat = ncnn.Mat((7, 8, 9), elemsize=4, elempack=1) | |
| assert ( | |
| mat.dims == 3 | |
| and mat.w == 7 | |
| and mat.h == 8 | |
| and mat.c == 9 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| ) | |
| mat = ncnn.Mat((10, 11, 12), elemsize=4, elempack=1, allocator=None) | |
| assert ( | |
| mat.dims == 3 | |
| and mat.w == 10 | |
| and mat.h == 11 | |
| and mat.c == 12 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| and mat.allocator == None | |
| ) | |
| def test_mat_dims4(): | |
| mat = ncnn.Mat(1, 2, 3, 4) | |
| assert mat.dims == 4 and mat.w == 1 and mat.h == 2 and mat.d == 3 and mat.c == 4 | |
| mat = ncnn.Mat(4, 5, 6, 7, elemsize=4) | |
| assert ( | |
| mat.dims == 4 and mat.w == 4 and mat.h == 5 and mat.d == 6 and mat.c == 7 and mat.elemsize == 4 | |
| ) | |
| mat = ncnn.Mat(7, 8, 9, 10, elemsize=4, elempack=1) | |
| assert ( | |
| mat.dims == 4 | |
| and mat.w == 7 | |
| and mat.h == 8 | |
| and mat.d == 9 | |
| and mat.c == 10 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| ) | |
| mat = ncnn.Mat(10, 11, 12, 13, elemsize=4, elempack=1, allocator=None) | |
| assert ( | |
| mat.dims == 4 | |
| and mat.w == 10 | |
| and mat.h == 11 | |
| and mat.d == 12 | |
| and mat.c == 13 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| and mat.allocator == None | |
| ) | |
| mat = ncnn.Mat((1, 2, 3, 4)) | |
| assert mat.dims == 4 and mat.w == 1 and mat.h == 2 and mat.d == 3 and mat.c == 4 | |
| mat = ncnn.Mat((4, 5, 6, 7), elemsize=4) | |
| assert ( | |
| mat.dims == 4 and mat.w == 4 and mat.h == 5 and mat.d == 6 and mat.c == 7 and mat.elemsize == 4 | |
| ) | |
| mat = ncnn.Mat((7, 8, 9, 10), elemsize=4, elempack=1) | |
| assert ( | |
| mat.dims == 4 | |
| and mat.w == 7 | |
| and mat.h == 8 | |
| and mat.d == 9 | |
| and mat.c == 10 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| ) | |
| mat = ncnn.Mat((10, 11, 12, 13), elemsize=4, elempack=1, allocator=None) | |
| assert ( | |
| mat.dims == 4 | |
| and mat.w == 10 | |
| and mat.h == 11 | |
| and mat.d == 12 | |
| and mat.c == 13 | |
| and mat.elemsize == 4 | |
| and mat.elempack == 1 | |
| and mat.allocator == None | |
| ) | |
| def test_numpy(): | |
| mat = ncnn.Mat(1) | |
| array = mat.numpy() | |
| assert mat.dims == array.ndim and mat.w == array.shape[0] | |
| mat = ncnn.Mat(2, 3) | |
| array = mat.numpy() | |
| assert array.dtype == np.float32 | |
| assert ( | |
| mat.dims == array.ndim and mat.w == array.shape[1] and mat.h == array.shape[0] | |
| ) | |
| mat = ncnn.Mat(4, 5, 6) | |
| array = np.array(mat) | |
| assert ( | |
| mat.dims == array.ndim | |
| and mat.w == array.shape[2] | |
| and mat.h == array.shape[1] | |
| and mat.c == array.shape[0] | |
| ) | |
| mat = ncnn.Mat(7, 8, 9, 10) | |
| array = np.array(mat) | |
| assert ( | |
| mat.dims == array.ndim | |
| and mat.w == array.shape[3] | |
| and mat.h == array.shape[2] | |
| and mat.d == array.shape[1] | |
| and mat.c == array.shape[0] | |
| ) | |
| mat = ncnn.Mat(1, elemsize=1) | |
| array = mat.numpy() | |
| assert array.dtype == np.int8 | |
| mat = ncnn.Mat(1, elemsize=2) | |
| array = mat.numpy() | |
| assert array.dtype == np.float16 | |
| # pybind11 def_buffer throw bug | |
| # with pytest.raises(RuntimeError) as execinfo: | |
| # mat = ncnn.Mat(1, elemsize=3) | |
| # array = np.array(mat) | |
| # assert "convert ncnn.Mat to numpy.ndarray only elemsize 1, 2, 4 support now, but given 3" in str( | |
| # execinfo.value | |
| # ) | |
| assert array.dtype == np.float16 | |
| mat = ncnn.Mat(1, elemsize=4) | |
| array = mat.numpy() | |
| assert array.dtype == np.float32 | |
| mat = np.random.randint(0, 128, size=(12,)).astype(np.uint8) | |
| array = np.array(mat) | |
| assert (mat == array).all() | |
| mat = np.random.rand(12).astype(np.float32) | |
| array = np.array(mat) | |
| assert (mat == array).all() | |
| mat = np.random.randint(0, 128, size=(12, 11)).astype(np.uint8) | |
| array = np.array(mat) | |
| assert (mat == array).all() | |
| mat = np.random.rand(12, 11).astype(np.float32) | |
| array = np.array(mat) | |
| assert (mat == array).all() | |
| mat = np.random.randint(0, 256, size=(12, 11, 3)).astype(np.uint8) | |
| array = np.array(mat) | |
| assert (mat == array).all() | |
| mat = np.random.rand(12, 11, 3).astype(np.float32) | |
| array = np.array(mat) | |
| assert (mat == array).all() | |
| mat = np.random.randint(0, 256, size=(12, 11, 7, 3)).astype(np.uint8) | |
| array = np.array(mat) | |
| assert (mat == array).all() | |
| mat = np.random.rand(12, 11, 7, 3).astype(np.float32) | |
| array = np.array(mat) | |
| assert (mat == array).all() | |
| array = np.array([1, 2, 3], dtype=np.int32) | |
| mat = ncnn.Mat(array) | |
| array2 = mat.numpy(format='i') | |
| assert array2.dtype == np.int32 | |
| array[0] = 10 | |
| assert array2[0] == 10 | |
| array = np.array([1, 2, 3], dtype=np.float32) | |
| mat = ncnn.Mat(array) | |
| array2 = mat.numpy(format='f') | |
| assert array2.dtype == np.float32 | |
| array2[0] = 100 | |
| assert array[0] == 100 | |
| def test_fill(): | |
| mat = ncnn.Mat(1) | |
| mat.fill(1.0) | |
| array = np.array(mat) | |
| assert np.abs(array[0] - 1.0) < sys.float_info.min | |
| def test_clone(): | |
| mat1 = ncnn.Mat(1) | |
| mat2 = mat1.clone() | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w | |
| mat1 = ncnn.Mat(2, 3) | |
| mat2 = mat1.clone() | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w and mat1.h == mat2.h | |
| mat1 = ncnn.Mat(4, 5, 6) | |
| mat2 = mat1.clone() | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.c == mat2.c | |
| ) | |
| mat1 = ncnn.Mat(7, 8, 9, 10) | |
| mat2 = mat1.clone() | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.d == mat2.d | |
| and mat1.c == mat2.c | |
| ) | |
| mat1 = ncnn.Mat((1,)) | |
| mat2 = mat1.clone() | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w | |
| mat1 = ncnn.Mat((2, 3)) | |
| mat2 = mat1.clone() | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w and mat1.h == mat2.h | |
| mat1 = ncnn.Mat((4, 5, 6)) | |
| mat2 = mat1.clone() | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.c == mat2.c | |
| ) | |
| mat1 = ncnn.Mat((7, 8, 9, 10)) | |
| mat2 = mat1.clone() | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.d == mat2.d | |
| and mat1.c == mat2.c | |
| ) | |
| def test_clone_from(): | |
| mat2 = ncnn.Mat() | |
| mat1 = ncnn.Mat(1) | |
| mat2.clone_from(mat1) | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w | |
| mat1 = ncnn.Mat(2, 3) | |
| mat2.clone_from(mat1) | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w and mat1.h == mat2.h | |
| mat1 = ncnn.Mat(4, 5, 6) | |
| mat2.clone_from(mat1) | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.c == mat2.c | |
| ) | |
| mat1 = ncnn.Mat(7, 8, 9, 10) | |
| mat2.clone_from(mat1) | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.d == mat2.d | |
| and mat1.c == mat2.c | |
| ) | |
| mat1 = ncnn.Mat((1,)) | |
| mat2.clone_from(mat1) | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w | |
| mat1 = ncnn.Mat((2, 3)) | |
| mat2.clone_from(mat1) | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w and mat1.h == mat2.h | |
| mat1 = ncnn.Mat((4, 5, 6)) | |
| mat2.clone_from(mat1) | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.c == mat2.c | |
| ) | |
| mat1 = ncnn.Mat((7, 8, 9, 10)) | |
| mat2.clone_from(mat1) | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.d == mat2.d | |
| and mat1.c == mat2.c | |
| ) | |
| def test_reshape(): | |
| mat1 = ncnn.Mat() | |
| mat2 = mat1.reshape(1) | |
| assert mat2.dims == 0 | |
| mat2 = mat1.reshape(1, 1) | |
| assert mat2.dims == 0 | |
| mat2 = mat1.reshape(1, 1, 1) | |
| assert mat2.dims == 0 | |
| mat2 = mat1.reshape(1, 1, 1, 1) | |
| assert mat2.dims == 0 | |
| mat1 = ncnn.Mat(1) | |
| mat2 = mat1.reshape(1, 1) | |
| assert mat2.dims == 2 and mat2.w == 1 and mat2.h == 1 | |
| mat2 = mat1.reshape(1, 1, 1) | |
| assert mat2.dims == 3 and mat2.w == 1 and mat2.h == 1 and mat2.c == 1 | |
| mat2 = mat1.reshape(1, 1, 1, 1) | |
| assert mat2.dims == 4 and mat2.w == 1 and mat2.h == 1 and mat2.d == 1 and mat2.c == 1 | |
| mat1 = ncnn.Mat(1, 2) | |
| mat2 = mat1.reshape(2) | |
| assert mat2.dims == 1 and mat2.w == 2 | |
| mat2 = mat1.reshape(2, 1) | |
| assert mat2.dims == 2 and mat2.w == 2 and mat2.h == 1 | |
| mat2 = mat1.reshape(2, 1, 1) | |
| assert mat2.dims == 3 and mat2.w == 2 and mat2.h == 1 and mat2.c == 1 | |
| mat2 = mat1.reshape(2, 1, 1, 1) | |
| assert mat2.dims == 4 and mat2.w == 2 and mat2.h == 1 and mat2.d == 1 and mat2.c == 1 | |
| mat1 = ncnn.Mat(1, 2, 3) | |
| mat2 = mat1.reshape(6) | |
| assert mat2.dims == 1 and mat2.w == 6 | |
| mat2 = mat1.reshape(2, 3) | |
| assert mat2.dims == 2 and mat2.w == 2 and mat2.h == 3 | |
| mat2 = mat1.reshape(2, 3, 1) | |
| assert mat2.dims == 3 and mat2.w == 2 and mat2.h == 3 and mat2.c == 1 | |
| mat2 = mat1.reshape(2, 1, 3, 1) | |
| assert mat2.dims == 4 and mat2.w == 2 and mat2.h == 1 and mat2.d == 3 and mat2.c == 1 | |
| mat1 = ncnn.Mat((1,)) | |
| mat2 = mat1.reshape((1, 1)) | |
| assert mat2.dims == 2 and mat2.w == 1 and mat2.h == 1 | |
| mat2 = mat1.reshape((1, 1, 1)) | |
| assert mat2.dims == 3 and mat2.w == 1 and mat2.h == 1 and mat2.c == 1 | |
| mat2 = mat1.reshape((1, 1, 1, 1)) | |
| assert mat2.dims == 4 and mat2.w == 1 and mat2.h == 1 and mat2.d == 1 and mat2.c == 1 | |
| mat1 = ncnn.Mat((1, 2)) | |
| mat2 = mat1.reshape((2,)) | |
| assert mat2.dims == 1 and mat2.w == 2 | |
| mat2 = mat1.reshape((2, 1)) | |
| assert mat2.dims == 2 and mat2.w == 2 and mat2.h == 1 | |
| mat2 = mat1.reshape((2, 1, 1)) | |
| assert mat2.dims == 3 and mat2.w == 2 and mat2.h == 1 and mat2.c == 1 | |
| mat2 = mat1.reshape((2, 1, 1, 1)) | |
| assert mat2.dims == 4 and mat2.w == 2 and mat2.h == 1 and mat2.d == 1 and mat2.c == 1 | |
| mat1 = ncnn.Mat((1, 2, 3)) | |
| mat2 = mat1.reshape((6,)) | |
| assert mat2.dims == 1 and mat2.w == 6 | |
| mat2 = mat1.reshape((2, 3)) | |
| assert mat2.dims == 2 and mat2.w == 2 and mat2.h == 3 and mat2.c == 1 | |
| mat2 = mat1.reshape((2, 3, 1)) | |
| assert mat2.dims == 3 and mat2.w == 2 and mat2.h == 3 and mat2.c == 1 | |
| mat2 = mat1.reshape((2, 1, 3, 1)) | |
| assert mat2.dims == 4 and mat2.w == 2 and mat2.h == 1 and mat2.d == 3 and mat2.c == 1 | |
| with pytest.raises(RuntimeError) as execinfo: | |
| mat1.reshape((1, 1, 1, 1, 1)) | |
| assert "shape must be 1, 2, 3 or 4 dims, not 5" in str(execinfo.value) | |
| def test_create(): | |
| mat = ncnn.Mat() | |
| mat.create(1) | |
| assert mat.dims == 1 and mat.w == 1 | |
| mat.create(2, 3) | |
| assert mat.dims == 2 and mat.w == 2 and mat.h == 3 | |
| mat.create(4, 5, 6) | |
| assert mat.dims == 3 and mat.w == 4 and mat.h == 5 and mat.c == 6 | |
| mat.create(7, 8, 9, 10) | |
| assert mat.dims == 4 and mat.w == 7 and mat.h == 8 and mat.d == 9 and mat.c == 10 | |
| mat.create((1,)) | |
| assert mat.dims == 1 and mat.w == 1 | |
| mat.create((2, 3)) | |
| assert mat.dims == 2 and mat.w == 2 and mat.h == 3 | |
| mat.create((4, 5, 6)) | |
| assert mat.dims == 3 and mat.w == 4 and mat.h == 5 and mat.c == 6 | |
| mat.create((7, 8, 9, 10)) | |
| assert mat.dims == 4 and mat.w == 7 and mat.h == 8 and mat.d == 9 and mat.c == 10 | |
| def test_create_like(): | |
| mat2 = ncnn.Mat() | |
| mat1 = ncnn.Mat(1) | |
| mat2.create_like(mat1) | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w | |
| mat1 = ncnn.Mat(2, 3) | |
| mat2.create_like(mat1) | |
| assert mat1.dims == mat2.dims and mat1.w == mat2.w and mat1.h == mat2.h | |
| mat1 = ncnn.Mat(4, 5, 6) | |
| mat2.create_like(mat1) | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.c == mat2.c | |
| ) | |
| mat1 = ncnn.Mat(7, 8, 9, 10) | |
| mat2.create_like(mat1) | |
| assert ( | |
| mat1.dims == mat2.dims | |
| and mat1.w == mat2.w | |
| and mat1.h == mat2.h | |
| and mat1.d == mat2.d | |
| and mat1.c == mat2.c | |
| ) | |
| def test_addref_release(): | |
| mat = ncnn.Mat(1) | |
| assert mat.refcount == 1 | |
| mat.addref() | |
| assert mat.refcount == 2 | |
| mat.release() | |
| assert mat.refcount == None | |
| def test_empty(): | |
| mat = ncnn.Mat() | |
| assert mat.empty() == True | |
| mat = ncnn.Mat(1) | |
| assert mat.empty() == False | |
| def test_total(): | |
| mat = ncnn.Mat(1) | |
| assert mat.total() == 1 | |
| mat = ncnn.Mat(2, 3) | |
| assert mat.total() == 2 * 3 | |
| mat = ncnn.Mat(4, 5, 6) | |
| assert mat.total() == 4 * 5 * 6 | |
| mat = ncnn.Mat(7, 8, 9, 10) | |
| assert mat.total() == 7 * 8 * 9 * 10 | |
| def test_elembits(): | |
| mat = ncnn.Mat(1, elemsize=1, elempack=1) | |
| assert mat.elembits() == 8 | |
| mat = ncnn.Mat(2, elemsize=2, elempack=1) | |
| assert mat.elembits() == 16 | |
| mat = ncnn.Mat(3, elemsize=4, elempack=1) | |
| assert mat.elembits() == 32 | |
| def test_shape(): | |
| mat = ncnn.Mat(1) | |
| shape = mat.shape() | |
| assert shape.dims == 1 and shape.w == 1 | |
| mat = ncnn.Mat(2, 3) | |
| shape = mat.shape() | |
| assert shape.dims == 2 and shape.w == 2 and shape.h == 3 | |
| mat = ncnn.Mat(4, 5, 6) | |
| shape = mat.shape() | |
| assert shape.dims == 3 and shape.w == 4 and shape.h == 5 and shape.c == 6 | |
| mat = ncnn.Mat(7, 8, 9, 10) | |
| shape = mat.shape() | |
| assert shape.dims == 4 and shape.w == 7 and shape.h == 8 and shape.d == 9 and shape.c == 10 | |
| def test_channel_depth_row(): | |
| mat = ncnn.Mat(2, 3, 4, 5) | |
| mat.fill(6.0) | |
| channel = mat.channel(1) | |
| assert channel.dims == 3 and channel.w == 2 and channel.h == 3 and channel.c == 4 | |
| depth = channel.depth(1) | |
| assert depth.dims == 2 and depth.w == 2 and depth.h == 3 | |
| row = depth.row(1) | |
| assert len(row) == 2 and np.abs(row[0] - 6.0) < sys.float_info.min | |
| def test_channel_row(): | |
| mat = ncnn.Mat(2, 3, 4) | |
| mat.fill(4.0) | |
| channel = mat.channel(1) | |
| assert channel.dims == 2 and channel.w == 2 and channel.h == 3 and channel.c == 1 | |
| row = channel.row(1) | |
| assert len(row) == 2 and np.abs(row[0] - 4.0) < sys.float_info.min | |
| def test_channel_range(): | |
| mat = ncnn.Mat(1, 2, 3) | |
| channel_range = mat.channel_range(0, 2) | |
| assert ( | |
| channel_range.dims == 3 | |
| and channel_range.w == 1 | |
| and channel_range.h == 2 | |
| and channel_range.c == 2 | |
| ) | |
| def test_depth_range(): | |
| mat = ncnn.Mat(1, 2, 3, 4) | |
| depth_range = mat.channel(1).depth_range(1, 2) | |
| assert ( | |
| depth_range.dims == 3 | |
| and depth_range.w == 1 | |
| and depth_range.h == 2 | |
| and depth_range.c == 2 | |
| ) | |
| def test_row_range(): | |
| mat = ncnn.Mat(1, 2) | |
| row_range = mat.row_range(0, 2) | |
| assert row_range.dims == 2 and row_range.w == 1 and row_range.h == 2 | |
| def test_range(): | |
| mat = ncnn.Mat(2) | |
| range = mat.range(0, 2) | |
| assert range.dims == 1 and range.w == 2 | |
| def test_getitem_setitem(): | |
| mat = ncnn.Mat(2) | |
| mat.fill(1) | |
| assert ( | |
| np.abs(mat[0] - 1.0) < sys.float_info.min | |
| and np.abs(mat[1] - 1.0) < sys.float_info.min | |
| ) | |
| mat[0] = 2.0 | |
| assert ( | |
| np.abs(mat[0] - 2.0) < sys.float_info.min | |
| and np.abs(mat[1] - 1.0) < sys.float_info.min | |
| ) | |
| def test_from_pixels(): | |
| pixels = np.random.randint(0, 256, size=(300, 400, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels(pixels, ncnn.Mat.PixelType.PIXEL_RGB, 400, 300) # chw | |
| assert mat.dims == 3 and mat.w == 400 and mat.h == 300 and mat.c == 3 | |
| assert pixels[0, 0, 0] == mat.channel(0).row(0)[0] | |
| assert pixels[200, 150, 1] == mat.channel(1).row(200)[150] | |
| assert pixels[299, 399, 2] == mat.channel(2).row(299)[399] | |
| pixels = np.random.randint(0, 256, size=(300, 500, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels( | |
| pixels, ncnn.Mat.PixelType.PIXEL_RGB, 400, 300, stride=500 * 3 | |
| ) # chw | |
| assert mat.dims == 3 and mat.w == 400 and mat.h == 300 and mat.c == 3 | |
| assert pixels[0, 0, 0] == mat.channel(0).row(0)[0] | |
| assert pixels[200, 150, 1] == mat.channel(1).row(200)[150] | |
| assert pixels[299, 399, 2] == mat.channel(2).row(299)[399] | |
| def test_from_pixels_resize(): | |
| pixels = np.random.randint(0, 256, size=(300, 400, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels_resize( | |
| pixels, ncnn.Mat.PixelType.PIXEL_BGR2RGB, 400, 300, 200, 150 | |
| ) # chw | |
| assert mat.dims == 3 and mat.w == 200 and mat.h == 150 and mat.c == 3 | |
| pixels = np.random.randint(0, 256, size=(300, 400, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels_resize( | |
| pixels, ncnn.Mat.PixelType.PIXEL_BGR2RGB, 400, 300, 400, 300 | |
| ) # chw | |
| assert mat.dims == 3 and mat.w == 400 and mat.h == 300 and mat.c == 3 | |
| assert pixels[0, 0, 0] == mat.channel(2).row(0)[0] | |
| assert pixels[200, 150, 1] == mat.channel(1).row(200)[150] | |
| assert pixels[299, 399, 2] == mat.channel(0).row(299)[399] | |
| pixels = np.random.randint(0, 256, size=(300, 500, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels_resize( | |
| pixels, ncnn.Mat.PixelType.PIXEL_BGR2RGB, 400, 300, 500 * 3, 200, 150 | |
| ) # chw | |
| assert mat.dims == 3 and mat.w == 200 and mat.h == 150 and mat.c == 3 | |
| pixels = np.random.randint(0, 256, size=(300, 500, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels_resize( | |
| pixels, ncnn.Mat.PixelType.PIXEL_BGR2RGB, 400, 300, 500 * 3, 400, 300 | |
| ) # chw | |
| assert mat.dims == 3 and mat.w == 400 and mat.h == 300 and mat.c == 3 | |
| assert pixels[0, 0, 0] == mat.channel(2).row(0)[0] | |
| assert pixels[200, 150, 1] == mat.channel(1).row(200)[150] | |
| assert pixels[299, 399, 2] == mat.channel(0).row(299)[399] | |
| def test_from_pixels_roi(): | |
| pixels = np.random.randint(0, 256, size=(300, 400, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels_roi( | |
| pixels, ncnn.Mat.PixelType.PIXEL_RGB, 400, 300, 100, 75, 200, 150 | |
| ) # chw | |
| assert mat.dims == 3 and mat.w == 200 and mat.h == 150 and mat.c == 3 | |
| assert pixels[75, 100, 0] == mat.channel(0).row(0)[0] | |
| assert pixels[150, 200, 1] == mat.channel(1).row(75)[100] | |
| assert pixels[224, 299, 2] == mat.channel(2).row(149)[199] | |
| pixels = np.random.randint(0, 256, size=(300, 500, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels_roi( | |
| pixels, ncnn.Mat.PixelType.PIXEL_RGB, 400, 300, 500 * 3, 100, 75, 200, 150 | |
| ) # chw | |
| assert mat.dims == 3 and mat.w == 200 and mat.h == 150 and mat.c == 3 | |
| assert pixels[75, 100, 0] == mat.channel(0).row(0)[0] | |
| assert pixels[150, 200, 1] == mat.channel(1).row(75)[100] | |
| assert pixels[224, 299, 2] == mat.channel(2).row(149)[199] | |
| def test_from_pixels_roi_resize(): | |
| pixels = np.random.randint(0, 256, size=(300, 400, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels_roi_resize( | |
| pixels, ncnn.Mat.PixelType.PIXEL_RGB, 400, 300, 100, 75, 200, 150, 100, 75 | |
| ) # chw | |
| assert mat.dims == 3 and mat.w == 100 and mat.h == 75 and mat.c == 3 | |
| pixels = np.random.randint(0, 256, size=(300, 500, 3)).astype(np.uint8) # hwc | |
| mat = ncnn.Mat.from_pixels_roi_resize( | |
| pixels, | |
| ncnn.Mat.PixelType.PIXEL_RGB, | |
| 400, | |
| 300, | |
| 500 * 3, | |
| 100, | |
| 75, | |
| 200, | |
| 150, | |
| 100, | |
| 75, | |
| ) # chw | |
| assert mat.dims == 3 and mat.w == 100 and mat.h == 75 and mat.c == 3 | |
| def test_substract_mean_normalize(): | |
| pixels = np.random.randint(0, 256, size=(300, 400, 3)).astype(np.uint8) # hwc | |
| mean_vals = [127.5, 127.5, 127.5] | |
| norm_vals = [0.007843, 0.007843, 0.007843] | |
| mat = ncnn.Mat.from_pixels(pixels, ncnn.Mat.PixelType.PIXEL_RGB, 400, 300) # chw | |
| mat.substract_mean_normalize([], norm_vals) | |
| assert np.abs(pixels[0, 0, 0] * 0.007843 - mat.channel(0).row(0)[0]) < 1e-5 | |
| mat = ncnn.Mat.from_pixels(pixels, ncnn.Mat.PixelType.PIXEL_RGB, 400, 300) # chw | |
| mat.substract_mean_normalize(mean_vals, []) | |
| assert np.abs((pixels[0, 0, 0] - 127.5) - mat.channel(0).row(0)[0]) < 1e-5 | |
| mat = ncnn.Mat.from_pixels(pixels, ncnn.Mat.PixelType.PIXEL_RGB, 400, 300) # chw | |
| mat.substract_mean_normalize(mean_vals, norm_vals) | |
| assert ( | |
| np.abs((pixels[0, 0, 0] - 127.5) * 0.007843 - mat.channel(0).row(0)[0]) < 1e-5 | |
| ) | |