mirror/eigen
2
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2024-12-21 07:19:46 +08:00
Code Issues Packages Projects Releases Wiki Activity
8f4b8d204b
eigen/unsupported/test/cxx11_tensor_image_patch.cpp
Benoit Steiner ec785b0180 Added support for extraction of patches from images
2014-11-13 09:28:54 -08:00

281 lines
8.6 KiB
C++
Raw Blame History

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#include "main.h"
#include <Eigen/CXX11/Tensor>
using Eigen::Tensor;
static void test_simple_patch()
{
Tensor<float, 4> tensor(2,3,5,7);
tensor.setRandom();
Tensor<float, 5> single_pixel_patch;
single_pixel_patch = tensor.extract_image_patches<1, 1>();
VERIFY_IS_EQUAL(single_pixel_patch.dimension(0), 2);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(1), 1);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(2), 1);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(3), 3*5);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(4), 7);
for (int i = 0; i < tensor.size(); ++i) {
VERIFY_IS_EQUAL(single_pixel_patch.data()[i], tensor.data()[i]);
}
Tensor<float, 5> entire_image_patch;
entire_image_patch = tensor.extract_image_patches<3, 5>();
VERIFY_IS_EQUAL(entire_image_patch.dimension(0), 2);
VERIFY_IS_EQUAL(entire_image_patch.dimension(1), 3);
VERIFY_IS_EQUAL(entire_image_patch.dimension(2), 5);
VERIFY_IS_EQUAL(entire_image_patch.dimension(3), 3*5);
VERIFY_IS_EQUAL(entire_image_patch.dimension(4), 7);
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 5; ++j) {
int patchId = i+3*j;
for (int r = 0; r < 3; ++r) {
for (int c = 0; c < 5; ++c) {
for (int d = 0; d < 2; ++d) {
for (int b = 0; b < 7; ++b) {
float expected = 0.0f;
if (r-1+i >= 0 && c-2+j >= 0 && r-1+i < 3 && c-2+j < 5) {
expected = tensor(d, r-1+i, c-2+j, b);
}
VERIFY_IS_EQUAL(entire_image_patch(d, r, c, patchId, b), expected);
}
}
}
}
}
}
Tensor<float, 5> twod_patch;
twod_patch = tensor.extract_image_patches<2, 2>();
VERIFY_IS_EQUAL(twod_patch.dimension(0), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(3), 3*5);
VERIFY_IS_EQUAL(twod_patch.dimension(4), 7);
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 5; ++j) {
int patchId = i+3*j;
for (int r = 0; r < 2; ++r) {
for (int c = 0; c < 2; ++c) {
for (int d = 0; d < 2; ++d) {
for (int b = 0; b < 7; ++b) {
float expected = 0.0f;
if (r-1+i >= 0 && c-1+j >= 0 && r-1+i < 3 && c-1+j < 5) {
expected = tensor(d, r-1+i, c-1+j, b);
}
VERIFY_IS_EQUAL(twod_patch(d, r, c, patchId, b), expected);
}
}
}
}
}
}
}
static void test_patch_no_extra_dim()
{
Tensor<float, 3> tensor(2,3,5);
tensor.setRandom();
Tensor<float, 4> single_pixel_patch;
single_pixel_patch = tensor.extract_image_patches<1, 1>();
VERIFY_IS_EQUAL(single_pixel_patch.dimension(0), 2);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(1), 1);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(2), 1);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(3), 3*5);
for (int i = 0; i < tensor.size(); ++i) {
VERIFY_IS_EQUAL(single_pixel_patch.data()[i], tensor.data()[i]);
}
Tensor<float, 4> entire_image_patch;
entire_image_patch = tensor.extract_image_patches<3, 5>();
VERIFY_IS_EQUAL(entire_image_patch.dimension(0), 2);
VERIFY_IS_EQUAL(entire_image_patch.dimension(1), 3);
VERIFY_IS_EQUAL(entire_image_patch.dimension(2), 5);
VERIFY_IS_EQUAL(entire_image_patch.dimension(3), 3*5);
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 5; ++j) {
int patchId = i+3*j;
for (int r = 0; r < 3; ++r) {
for (int c = 0; c < 5; ++c) {
for (int d = 0; d < 2; ++d) {
float expected = 0.0f;
if (r-1+i >= 0 && c-2+j >= 0 && r-1+i < 3 && c-2+j < 5) {
expected = tensor(d, r-1+i, c-2+j);
}
VERIFY_IS_EQUAL(entire_image_patch(d, r, c, patchId), expected);
}
}
}
}
}
Tensor<float, 4> twod_patch;
twod_patch = tensor.extract_image_patches<2, 2>();
VERIFY_IS_EQUAL(twod_patch.dimension(0), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(3), 3*5);
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 5; ++j) {
int patchId = i+3*j;
for (int r = 0; r < 2; ++r) {
for (int c = 0; c < 2; ++c) {
for (int d = 0; d < 2; ++d) {
float expected = 0.0f;
if (r-1+i >= 0 && c-1+j >= 0 && r-1+i < 3 && c-1+j < 5) {
expected = tensor(d, r-1+i, c-1+j);
}
VERIFY_IS_EQUAL(twod_patch(d, r, c, patchId), expected);
}
}
}
}
}
}
static void test_imagenet_patches()
{
// Test the code on typical configurations used by the 'imagenet' benchmarks at
// https://github.com/soumith/convnet-benchmarks
Tensor<float, 4> l_in(3, 128, 128, 128);
l_in.setRandom();
Tensor<float, 5> l_out = l_in.extract_image_patches(11, 11);
VERIFY_IS_EQUAL(l_out.dimension(0), 3);
VERIFY_IS_EQUAL(l_out.dimension(1), 11);
VERIFY_IS_EQUAL(l_out.dimension(2), 11);
VERIFY_IS_EQUAL(l_out.dimension(3), 128*128);
VERIFY_IS_EQUAL(l_out.dimension(4), 128);
for (int b = 0; b < 128; ++b) {
for (int i = 0; i < 128; ++i) {
for (int j = 0; j < 128; ++j) {
int patchId = i+128*j;
for (int c = 0; c < 11; ++c) {
for (int r = 0; r < 11; ++r) {
for (int d = 0; d < 3; ++d) {
float expected = 0.0f;
if (r-5+i >= 0 && c-5+j >= 0 && r-5+i < 128 && c-5+j < 128) {
expected = l_in(d, r-5+i, c-5+j, b);
}
VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
}
}
}
}
}
}
l_in.resize(64, 64, 64, 128);
l_in.setRandom();
l_out = l_in.extract_image_patches(9, 9);
VERIFY_IS_EQUAL(l_out.dimension(0), 64);
VERIFY_IS_EQUAL(l_out.dimension(1), 9);
VERIFY_IS_EQUAL(l_out.dimension(2), 9);
VERIFY_IS_EQUAL(l_out.dimension(3), 64*64);
VERIFY_IS_EQUAL(l_out.dimension(4), 128);
for (int b = 0; b < 128; ++b) {
for (int i = 0; i < 64; ++i) {
for (int j = 0; j < 64; ++j) {
int patchId = i+64*j;
for (int c = 0; c < 9; ++c) {
for (int r = 0; r < 9; ++r) {
for (int d = 0; d < 64; ++d) {
float expected = 0.0f;
if (r-4+i >= 0 && c-4+j >= 0 && r-4+i < 64 && c-4+j < 64) {
expected = l_in(d, r-4+i, c-4+j, b);
}
VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
}
}
}
}
}
}
l_in.resize(128, 16, 16, 128);
l_in.setRandom();
l_out = l_in.extract_image_patches(7, 7);
VERIFY_IS_EQUAL(l_out.dimension(0), 128);
VERIFY_IS_EQUAL(l_out.dimension(1), 7);
VERIFY_IS_EQUAL(l_out.dimension(2), 7);
VERIFY_IS_EQUAL(l_out.dimension(3), 16*16);
VERIFY_IS_EQUAL(l_out.dimension(4), 128);
for (int b = 0; b < 128; ++b) {
for (int i = 0; i < 16; ++i) {
for (int j = 0; j < 16; ++j) {
int patchId = i+16*j;
for (int c = 0; c < 7; ++c) {
for (int r = 0; r < 7; ++r) {
for (int d = 0; d < 128; ++d) {
float expected = 0.0f;
if (r-3+i >= 0 && c-3+j >= 0 && r-3+i < 16 && c-3+j < 16) {
expected = l_in(d, r-3+i, c-3+j, b);
}
VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
}
}
}
}
}
}
l_in.resize(384, 13, 13, 128);
l_in.setRandom();
l_out = l_in.extract_image_patches(3, 3);
VERIFY_IS_EQUAL(l_out.dimension(0), 384);
VERIFY_IS_EQUAL(l_out.dimension(1), 3);
VERIFY_IS_EQUAL(l_out.dimension(2), 3);
VERIFY_IS_EQUAL(l_out.dimension(3), 13*13);
VERIFY_IS_EQUAL(l_out.dimension(4), 128);
for (int b = 0; b < 128; ++b) {
for (int i = 0; i < 13; ++i) {
for (int j = 0; j < 13; ++j) {
int patchId = i+13*j;
for (int c = 0; c < 3; ++c) {
for (int r = 0; r < 3; ++r) {
for (int d = 0; d < 384; ++d) {
float expected = 0.0f;
if (r-1+i >= 0 && c-1+j >= 0 && r-1+i < 13 && c-1+j < 13) {
expected = l_in(d, r-1+i, c-1+j, b);
}
VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
}
}
}
}
}
}
}
void test_cxx11_tensor_image_patch()
{
CALL_SUBTEST(test_simple_patch());
CALL_SUBTEST(test_patch_no_extra_dim());
CALL_SUBTEST(test_imagenet_patches());
}
Reference in New Issue View Git Blame Copy Permalink