void intensity_2d_data_transformer::transform(
const void * data,
void * data_transformed,
neuron_data_type::input_type type,
const layer_configuration_specific& original_config)
{
if (type != neuron_data_type::type_byte)
throw neural_network_exception("intensity_2d_data_transformer is implemented for data stored as bytes only");
if (original_config.dimension_sizes.size() != 2)
throw neural_network_exception((boost::format("intensity_2d_data_transformer is processing 2d data only, data is passed with number of dimensions %1%") % original_config.dimension_sizes.size()).str());
float contrast = contrast_distribution(generator);
float brightness_shift = brightness_shift_distribution(generator) * 255.0F;
unsigned int neuron_count_per_feature_map = original_config.get_neuron_count_per_feature_map();
for(unsigned int feature_map_id = 0; feature_map_id < original_config.feature_map_count; ++feature_map_id)
{
cv::Mat1b image(static_cast<int>(original_config.dimension_sizes[1]), static_cast<int>(original_config.dimension_sizes[0]), static_cast<unsigned char *>(data_transformed) + (neuron_count_per_feature_map * feature_map_id));
data_transformer_util::change_brightness_and_contrast(
image,
contrast,
brightness_shift);
}
}
void gtsrb_toolset::write_folder(
nnforge::supervised_data_stream_writer& writer,
const boost::filesystem::path& relative_subfolder_path,
const char * annotation_file_name,
bool jitter)
{
boost::filesystem::path subfolder_path = get_input_data_folder() / relative_subfolder_path;
boost::filesystem::path annotation_file_path = subfolder_path / annotation_file_name;
std::cout << "Reading input data from " << subfolder_path.string() << std::endl;
boost::filesystem::ifstream file_input(annotation_file_path, std::ios_base::in);
nnforge::random_generator generator = nnforge::rnd::get_random_generator();
std::tr1::uniform_real<float> rotate_angle_distribution(-max_rotation_angle_in_degrees, max_rotation_angle_in_degrees);
std::tr1::uniform_real<float> scale_distribution(1.0F / max_scale_factor, max_scale_factor);
std::tr1::uniform_real<float> shift_distribution(-max_shift, max_shift);
std::tr1::uniform_real<float> contrast_distribution(1.0F / max_contrast_factor, max_contrast_factor);
std::tr1::uniform_real<float> brightness_shift_distribution(-max_brightness_shift, max_brightness_shift);
std::string str;
std::getline(file_input, str); // read the header
while (true)
{
std::getline(file_input, str);
std::vector<std::string> strs;
boost::split(strs, str, boost::is_any_of(";"));
if (strs.size() != 8)
break;
std::string file_name = strs[0];
boost::filesystem::path absolute_file_path = subfolder_path / file_name;
char* end;
unsigned int top_left_x = static_cast<unsigned int>(strtol(strs[3].c_str(), &end, 10));
unsigned int top_left_y = static_cast<unsigned int>(strtol(strs[4].c_str(), &end, 10));
unsigned int bottom_right_x = static_cast<unsigned int>(strtol(strs[5].c_str(), &end, 10));
unsigned int bottom_right_y = static_cast<unsigned int>(strtol(strs[6].c_str(), &end, 10));
unsigned int class_id = static_cast<unsigned int>(strtol(strs[7].c_str(), &end, 10));
if (jitter)
{
for(int i = 0; i < random_sample_count; ++i)
{
float rotation_angle = rotate_angle_distribution(generator);
float scale = scale_distribution(generator);
float shift_x = shift_distribution(generator);
float shift_y = shift_distribution(generator);
float contrast = contrast_distribution(generator);
float brightness_shift = brightness_shift_distribution(generator);
write_single_entry(
writer,
absolute_file_path,
class_id,
top_left_x,
top_left_y,
bottom_right_x,
bottom_right_y,
rotation_angle,
scale,
shift_x,
shift_y,
contrast,
brightness_shift);
}
}
else
{
write_single_entry(
writer,
absolute_file_path,
class_id,
top_left_x,
top_left_y,
bottom_right_x,
bottom_right_y);
}
}
}
