558 lines
15 KiB
C++
558 lines
15 KiB
C++
/*
|
|
* Copyright (c) 2017-2020 Arm Limited.
|
|
*
|
|
* SPDX-License-Identifier: MIT
|
|
*
|
|
* Permission is hereby granted, free of charge, to any person obtaining a copy
|
|
* of this software and associated documentation files (the "Software"), to
|
|
* deal in the Software without restriction, including without limitation the
|
|
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
|
|
* sell copies of the Software, and to permit persons to whom the Software is
|
|
* furnished to do so, subject to the following conditions:
|
|
*
|
|
* The above copyright notice and this permission notice shall be included in all
|
|
* copies or substantial portions of the Software.
|
|
*
|
|
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
|
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
|
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
|
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
|
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
|
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
|
* SOFTWARE.
|
|
*/
|
|
#include "tests/AssetsLibrary.h"
|
|
|
|
#include "Utils.h"
|
|
#include "utils/TypePrinter.h"
|
|
|
|
#include "arm_compute/core/ITensor.h"
|
|
|
|
#pragma GCC diagnostic push
|
|
#pragma GCC diagnostic ignored "-Wunused-parameter"
|
|
#include "libnpy/npy.hpp"
|
|
#pragma GCC diagnostic pop
|
|
|
|
#include <cctype>
|
|
#include <fstream>
|
|
#include <limits>
|
|
#include <map>
|
|
#include <mutex>
|
|
#include <sstream>
|
|
#include <stdexcept>
|
|
#include <tuple>
|
|
#include <unordered_map>
|
|
#include <utility>
|
|
|
|
namespace arm_compute
|
|
{
|
|
namespace test
|
|
{
|
|
namespace
|
|
{
|
|
template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type = 0>
|
|
void rgb_to_luminance(const RawTensor &src, RawTensor &dst)
|
|
{
|
|
// Ensure in/out tensors have same image dimensions (independent of element size and number of channels)
|
|
ARM_COMPUTE_ERROR_ON_MSG(src.num_elements() != dst.num_elements(), "Input and output images must have equal dimensions");
|
|
|
|
const size_t num_elements = dst.num_elements();
|
|
|
|
// Currently, input is always RGB888 (3 U8 channels per element). Output can be U8, U16/S16 or U32
|
|
// Note that src.data()[i] returns pointer to first channel of element[i], so RGB values have [0,1,2] offsets
|
|
for(size_t i = 0, j = 0; j < num_elements; i += 3, ++j)
|
|
{
|
|
reinterpret_cast<T *>(dst.data())[j] = 0.2126f * src.data()[i] + 0.7152f * src.data()[i + 1] + 0.0722f * src.data()[i + 2];
|
|
}
|
|
}
|
|
|
|
void extract_r_from_rgb(const RawTensor &src, RawTensor &dst)
|
|
{
|
|
ARM_COMPUTE_ERROR_ON(src.size() != 3 * dst.size());
|
|
|
|
const size_t num_elements = dst.num_elements();
|
|
|
|
for(size_t i = 0, j = 0; j < num_elements; i += 3, ++j)
|
|
{
|
|
dst.data()[j] = src.data()[i];
|
|
}
|
|
}
|
|
|
|
void extract_g_from_rgb(const RawTensor &src, RawTensor &dst)
|
|
{
|
|
ARM_COMPUTE_ERROR_ON(src.size() != 3 * dst.size());
|
|
|
|
const size_t num_elements = dst.num_elements();
|
|
|
|
for(size_t i = 1, j = 0; j < num_elements; i += 3, ++j)
|
|
{
|
|
dst.data()[j] = src.data()[i];
|
|
}
|
|
}
|
|
|
|
void extract_b_from_rgb(const RawTensor &src, RawTensor &dst)
|
|
{
|
|
ARM_COMPUTE_ERROR_ON(src.size() != 3 * dst.size());
|
|
|
|
const size_t num_elements = dst.num_elements();
|
|
|
|
for(size_t i = 2, j = 0; j < num_elements; i += 3, ++j)
|
|
{
|
|
dst.data()[j] = src.data()[i];
|
|
}
|
|
}
|
|
|
|
void discard_comments(std::ifstream &fs)
|
|
{
|
|
while(fs.peek() == '#')
|
|
{
|
|
fs.ignore(std::numeric_limits<std::streamsize>::max(), '\n');
|
|
}
|
|
}
|
|
|
|
void discard_comments_and_spaces(std::ifstream &fs)
|
|
{
|
|
while(true)
|
|
{
|
|
discard_comments(fs);
|
|
|
|
if(isspace(fs.peek()) == 0)
|
|
{
|
|
break;
|
|
}
|
|
|
|
fs.ignore(1);
|
|
}
|
|
}
|
|
|
|
std::tuple<unsigned int, unsigned int, int> parse_netpbm_format_header(std::ifstream &fs, char number)
|
|
{
|
|
// check file type magic number is valid
|
|
std::array<char, 2> magic_number{ { 0 } };
|
|
fs >> magic_number[0] >> magic_number[1];
|
|
|
|
if(magic_number[0] != 'P' || magic_number[1] != number)
|
|
{
|
|
throw std::runtime_error("File type magic number not supported");
|
|
}
|
|
|
|
discard_comments_and_spaces(fs);
|
|
|
|
unsigned int width = 0;
|
|
fs >> width;
|
|
|
|
discard_comments_and_spaces(fs);
|
|
|
|
unsigned int height = 0;
|
|
fs >> height;
|
|
|
|
discard_comments_and_spaces(fs);
|
|
|
|
int max_value = 0;
|
|
fs >> max_value;
|
|
|
|
if(!fs.good())
|
|
{
|
|
throw std::runtime_error("Cannot read image dimensions");
|
|
}
|
|
|
|
if(max_value != 255)
|
|
{
|
|
throw std::runtime_error("RawTensor doesn't have 8-bit values");
|
|
}
|
|
|
|
discard_comments(fs);
|
|
|
|
if(isspace(fs.peek()) == 0)
|
|
{
|
|
throw std::runtime_error("Invalid image header");
|
|
}
|
|
|
|
fs.ignore(1);
|
|
|
|
return std::make_tuple(width, height, max_value);
|
|
}
|
|
|
|
std::tuple<unsigned int, unsigned int, int> parse_ppm_header(std::ifstream &fs)
|
|
{
|
|
return parse_netpbm_format_header(fs, '6');
|
|
}
|
|
|
|
std::tuple<unsigned int, unsigned int, int> parse_pgm_header(std::ifstream &fs)
|
|
{
|
|
return parse_netpbm_format_header(fs, '5');
|
|
}
|
|
|
|
void check_image_size(std::ifstream &fs, size_t raw_size)
|
|
{
|
|
const size_t current_position = fs.tellg();
|
|
fs.seekg(0, std::ios_base::end);
|
|
const size_t end_position = fs.tellg();
|
|
fs.seekg(current_position, std::ios_base::beg);
|
|
|
|
if((end_position - current_position) < raw_size)
|
|
{
|
|
throw std::runtime_error("Not enough data in file");
|
|
}
|
|
}
|
|
|
|
void read_image_buffer(std::ifstream &fs, RawTensor &raw)
|
|
{
|
|
fs.read(reinterpret_cast<std::fstream::char_type *>(raw.data()), raw.size());
|
|
|
|
if(!fs.good())
|
|
{
|
|
throw std::runtime_error("Failure while reading image buffer");
|
|
}
|
|
}
|
|
|
|
RawTensor load_ppm(const std::string &path)
|
|
{
|
|
std::ifstream file(path, std::ios::in | std::ios::binary);
|
|
|
|
if(!file.good())
|
|
{
|
|
throw framework::FileNotFound("Could not load PPM image: " + path);
|
|
}
|
|
|
|
unsigned int width = 0;
|
|
unsigned int height = 0;
|
|
|
|
std::tie(width, height, std::ignore) = parse_ppm_header(file);
|
|
|
|
RawTensor raw(TensorShape(width, height), Format::RGB888);
|
|
|
|
check_image_size(file, raw.size());
|
|
read_image_buffer(file, raw);
|
|
|
|
return raw;
|
|
}
|
|
|
|
RawTensor load_pgm(const std::string &path)
|
|
{
|
|
std::ifstream file(path, std::ios::in | std::ios::binary);
|
|
|
|
if(!file.good())
|
|
{
|
|
throw framework::FileNotFound("Could not load PGM image: " + path);
|
|
}
|
|
|
|
unsigned int width = 0;
|
|
unsigned int height = 0;
|
|
|
|
std::tie(width, height, std::ignore) = parse_pgm_header(file);
|
|
|
|
RawTensor raw(TensorShape(width, height), Format::U8);
|
|
|
|
check_image_size(file, raw.size());
|
|
read_image_buffer(file, raw);
|
|
|
|
return raw;
|
|
}
|
|
} // namespace
|
|
|
|
AssetsLibrary::AssetsLibrary(std::string path, std::random_device::result_type seed) //NOLINT
|
|
: _library_path(std::move(path)),
|
|
_seed{ seed }
|
|
{
|
|
}
|
|
|
|
std::string AssetsLibrary::path() const
|
|
{
|
|
return _library_path;
|
|
}
|
|
|
|
std::random_device::result_type AssetsLibrary::seed() const
|
|
{
|
|
return _seed;
|
|
}
|
|
|
|
void AssetsLibrary::fill(RawTensor &raw, const std::string &name, Format format) const
|
|
{
|
|
//FIXME: Should be done by swapping cached buffers
|
|
const RawTensor &src = get(name, format);
|
|
std::copy_n(src.data(), raw.size(), raw.data());
|
|
}
|
|
|
|
void AssetsLibrary::fill(RawTensor &raw, const std::string &name, Channel channel) const
|
|
{
|
|
fill(raw, name, get_format_for_channel(channel), channel);
|
|
}
|
|
|
|
void AssetsLibrary::fill(RawTensor &raw, const std::string &name, Format format, Channel channel) const
|
|
{
|
|
const RawTensor &src = get(name, format, channel);
|
|
std::copy_n(src.data(), raw.size(), raw.data());
|
|
}
|
|
|
|
const AssetsLibrary::Loader &AssetsLibrary::get_loader(const std::string &extension) const
|
|
{
|
|
static std::unordered_map<std::string, Loader> loaders =
|
|
{
|
|
{ "ppm", load_ppm },
|
|
{ "pgm", load_pgm }
|
|
};
|
|
|
|
const auto it = loaders.find(extension);
|
|
|
|
if(it != loaders.end())
|
|
{
|
|
return it->second;
|
|
}
|
|
else
|
|
{
|
|
throw std::invalid_argument("Cannot load image with extension '" + extension + "'");
|
|
}
|
|
}
|
|
|
|
const AssetsLibrary::Converter &AssetsLibrary::get_converter(Format src, Format dst) const
|
|
{
|
|
static std::map<std::pair<Format, Format>, Converter> converters =
|
|
{
|
|
{ std::make_pair(Format::RGB888, Format::U8), rgb_to_luminance<uint8_t> },
|
|
{ std::make_pair(Format::RGB888, Format::U16), rgb_to_luminance<uint16_t> },
|
|
{ std::make_pair(Format::RGB888, Format::S16), rgb_to_luminance<int16_t> },
|
|
{ std::make_pair(Format::RGB888, Format::U32), rgb_to_luminance<uint32_t> }
|
|
};
|
|
|
|
const auto it = converters.find(std::make_pair(src, dst));
|
|
|
|
if(it != converters.end())
|
|
{
|
|
return it->second;
|
|
}
|
|
else
|
|
{
|
|
std::stringstream msg;
|
|
msg << "Cannot convert from format '" << src << "' to format '" << dst << "'\n";
|
|
throw std::invalid_argument(msg.str());
|
|
}
|
|
}
|
|
|
|
const AssetsLibrary::Converter &AssetsLibrary::get_converter(DataType src, Format dst) const
|
|
{
|
|
static std::map<std::pair<DataType, Format>, Converter> converters = {};
|
|
|
|
const auto it = converters.find(std::make_pair(src, dst));
|
|
|
|
if(it != converters.end())
|
|
{
|
|
return it->second;
|
|
}
|
|
else
|
|
{
|
|
std::stringstream msg;
|
|
msg << "Cannot convert from data type '" << src << "' to format '" << dst << "'\n";
|
|
throw std::invalid_argument(msg.str());
|
|
}
|
|
}
|
|
|
|
const AssetsLibrary::Converter &AssetsLibrary::get_converter(DataType src, DataType dst) const
|
|
{
|
|
static std::map<std::pair<DataType, DataType>, Converter> converters = {};
|
|
|
|
const auto it = converters.find(std::make_pair(src, dst));
|
|
|
|
if(it != converters.end())
|
|
{
|
|
return it->second;
|
|
}
|
|
else
|
|
{
|
|
std::stringstream msg;
|
|
msg << "Cannot convert from data type '" << src << "' to data type '" << dst << "'\n";
|
|
throw std::invalid_argument(msg.str());
|
|
}
|
|
}
|
|
|
|
const AssetsLibrary::Converter &AssetsLibrary::get_converter(Format src, DataType dst) const
|
|
{
|
|
static std::map<std::pair<Format, DataType>, Converter> converters = {};
|
|
|
|
const auto it = converters.find(std::make_pair(src, dst));
|
|
|
|
if(it != converters.end())
|
|
{
|
|
return it->second;
|
|
}
|
|
else
|
|
{
|
|
std::stringstream msg;
|
|
msg << "Cannot convert from format '" << src << "' to data type '" << dst << "'\n";
|
|
throw std::invalid_argument(msg.str());
|
|
}
|
|
}
|
|
|
|
const AssetsLibrary::Extractor &AssetsLibrary::get_extractor(Format format, Channel channel) const
|
|
{
|
|
static std::map<std::pair<Format, Channel>, Extractor> extractors =
|
|
{
|
|
{ std::make_pair(Format::RGB888, Channel::R), extract_r_from_rgb },
|
|
{ std::make_pair(Format::RGB888, Channel::G), extract_g_from_rgb },
|
|
{ std::make_pair(Format::RGB888, Channel::B), extract_b_from_rgb }
|
|
};
|
|
|
|
const auto it = extractors.find(std::make_pair(format, channel));
|
|
|
|
if(it != extractors.end())
|
|
{
|
|
return it->second;
|
|
}
|
|
else
|
|
{
|
|
std::stringstream msg;
|
|
msg << "Cannot extract channel '" << channel << "' from format '" << format << "'\n";
|
|
throw std::invalid_argument(msg.str());
|
|
}
|
|
}
|
|
|
|
RawTensor AssetsLibrary::load_image(const std::string &name) const
|
|
{
|
|
#ifdef _WIN32
|
|
const std::string image_path = ("\\images\\");
|
|
#else /* _WIN32 */
|
|
const std::string image_path = ("/images/");
|
|
#endif /* _WIN32 */
|
|
|
|
const std::string path = _library_path + image_path + name;
|
|
const std::string extension = path.substr(path.find_last_of('.') + 1);
|
|
return (*get_loader(extension))(path);
|
|
}
|
|
|
|
const RawTensor &AssetsLibrary::find_or_create_raw_tensor(const std::string &name, Format format) const
|
|
{
|
|
std::lock_guard<arm_compute::Mutex> guard(_format_lock);
|
|
|
|
const RawTensor *ptr = _cache.find(std::forward_as_tuple(name, format));
|
|
|
|
if(ptr != nullptr)
|
|
{
|
|
return *ptr;
|
|
}
|
|
|
|
RawTensor raw = load_image(name);
|
|
|
|
if(raw.format() != format)
|
|
{
|
|
//FIXME: Remove unnecessary copy
|
|
RawTensor dst(raw.shape(), format);
|
|
(*get_converter(raw.format(), format))(raw, dst);
|
|
raw = std::move(dst);
|
|
}
|
|
|
|
return _cache.add(std::forward_as_tuple(name, format), std::move(raw));
|
|
}
|
|
|
|
const RawTensor &AssetsLibrary::find_or_create_raw_tensor(const std::string &name, Format format, Channel channel) const
|
|
{
|
|
std::lock_guard<arm_compute::Mutex> guard(_channel_lock);
|
|
|
|
const RawTensor *ptr = _cache.find(std::forward_as_tuple(name, format, channel));
|
|
|
|
if(ptr != nullptr)
|
|
{
|
|
return *ptr;
|
|
}
|
|
|
|
const RawTensor &src = get(name, format);
|
|
//FIXME: Need to change shape to match channel
|
|
RawTensor dst(src.shape(), get_channel_format(channel));
|
|
|
|
(*get_extractor(format, channel))(src, dst);
|
|
|
|
return _cache.add(std::forward_as_tuple(name, format, channel), std::move(dst));
|
|
}
|
|
|
|
TensorShape AssetsLibrary::get_image_shape(const std::string &name)
|
|
{
|
|
return load_image(name).shape();
|
|
}
|
|
|
|
const RawTensor &AssetsLibrary::get(const std::string &name) const
|
|
{
|
|
//FIXME: Format should be derived from the image name. Not be fixed to RGB.
|
|
return find_or_create_raw_tensor(name, Format::RGB888);
|
|
}
|
|
|
|
RawTensor AssetsLibrary::get(const std::string &name)
|
|
{
|
|
//FIXME: Format should be derived from the image name. Not be fixed to RGB.
|
|
return RawTensor(find_or_create_raw_tensor(name, Format::RGB888));
|
|
}
|
|
|
|
RawTensor AssetsLibrary::get(const std::string &name, DataType data_type, int num_channels) const
|
|
{
|
|
const RawTensor &raw = get(name);
|
|
|
|
return RawTensor(raw.shape(), data_type, num_channels);
|
|
}
|
|
|
|
const RawTensor &AssetsLibrary::get(const std::string &name, Format format) const
|
|
{
|
|
return find_or_create_raw_tensor(name, format);
|
|
}
|
|
|
|
RawTensor AssetsLibrary::get(const std::string &name, Format format)
|
|
{
|
|
return RawTensor(find_or_create_raw_tensor(name, format));
|
|
}
|
|
|
|
const RawTensor &AssetsLibrary::get(const std::string &name, Channel channel) const
|
|
{
|
|
return get(name, get_format_for_channel(channel), channel);
|
|
}
|
|
|
|
RawTensor AssetsLibrary::get(const std::string &name, Channel channel)
|
|
{
|
|
return RawTensor(get(name, get_format_for_channel(channel), channel));
|
|
}
|
|
|
|
const RawTensor &AssetsLibrary::get(const std::string &name, Format format, Channel channel) const
|
|
{
|
|
return find_or_create_raw_tensor(name, format, channel);
|
|
}
|
|
|
|
RawTensor AssetsLibrary::get(const std::string &name, Format format, Channel channel)
|
|
{
|
|
return RawTensor(find_or_create_raw_tensor(name, format, channel));
|
|
}
|
|
|
|
namespace detail
|
|
{
|
|
inline void validate_npy_header(std::ifstream &stream, const std::string &expect_typestr, const TensorShape &expect_shape)
|
|
{
|
|
ARM_COMPUTE_UNUSED(expect_typestr);
|
|
ARM_COMPUTE_UNUSED(expect_shape);
|
|
|
|
std::string header = npy::read_header(stream);
|
|
|
|
// Parse header
|
|
std::vector<unsigned long> shape;
|
|
bool fortran_order = false;
|
|
std::string typestr;
|
|
npy::parse_header(header, typestr, fortran_order, shape);
|
|
|
|
// Check if the typestring matches the given one
|
|
ARM_COMPUTE_ERROR_ON_MSG(typestr != expect_typestr, "Typestrings mismatch");
|
|
|
|
// Validate tensor shape
|
|
ARM_COMPUTE_ERROR_ON_MSG(shape.size() != expect_shape.num_dimensions(), "Tensor ranks mismatch");
|
|
if(fortran_order)
|
|
{
|
|
for(size_t i = 0; i < shape.size(); ++i)
|
|
{
|
|
ARM_COMPUTE_ERROR_ON_MSG(expect_shape[i] != shape[i], "Tensor dimensions mismatch");
|
|
}
|
|
}
|
|
else
|
|
{
|
|
for(size_t i = 0; i < shape.size(); ++i)
|
|
{
|
|
ARM_COMPUTE_ERROR_ON_MSG(expect_shape[i] != shape[shape.size() - i - 1], "Tensor dimensions mismatch");
|
|
}
|
|
}
|
|
}
|
|
} // namespace detail
|
|
} // namespace test
|
|
} // namespace arm_compute
|