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Changed seeding strategy and have one generator per row of output data #2297

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shantanuchhabra merged 6 commits into from
Sep 17, 2019
Merged

Changed seeding strategy and have one generator per row of output data #2297

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76f9d78
Changed seeding strategy to use std::seed_seq and have one generator …
shantanuchhabra Sep 10, 2019
680adfa
Addressed PR feedback and built
shantanuchhabra Sep 12, 2019
7798027
uniform_int_distribution is inclusive and also added an assert for range
shantanuchhabra Sep 12, 2019
285ed81
Passed engine by reference
shantanuchhabra Sep 13, 2019
7b5ad09
Passing as a pointer instead of as a reference per the Google style g…
shantanuchhabra Sep 13, 2019
ba66607
Merge branch 'master' into new_seeding
shantanuchhabra Sep 16, 2019
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8 changes: 4 additions & 4 deletions src/toolkits/object_detection/one_shot_object_detection/one_shot_object_detector.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ namespace one_shot_object_detection {
namespace data_augmentation {

flex_dict build_annotation(ParameterSampler &parameter_sampler,
std::string label,
const std::string &label,
size_t object_width, size_t object_height,
size_t background_width, size_t background_height,
size_t seed, size_t row_number) {
Expand Down Expand Up @@ -150,7 +150,7 @@ create_synthetic_image_from_background_and_starter(ParameterSampler &parameter_s
reinterpret_cast<const boost::gil::rgba8_pixel_t *>(
rgba_flex_image.get_image_data()),
rgba_flex_image.m_channels *
rgba_flex_image.m_width // row length in bytes
rgba_flex_image.m_width // row length in bytes
);

boost::gil::rgb8_image_t::const_view_t background_view = interleaved_view(
Expand Down Expand Up @@ -210,7 +210,7 @@ gl_sframe augment_data(const gl_sframe &data,
* Replacing the `for` with a `parallel_for` fails the export_coreml unit test
* with an EXC_BAD_ACCESS in the function call to boost::gil::resample_pixels
*/
for (const auto &row : decompressed_data.range_iterator()) {
for (const sframe_rows::row &row : decompressed_data.range_iterator()) {
// go through all the starter images and create augmented images for
// all starter images and the respective chunk of background images
const flex_image &object = row[image_column_index].get<flex_image>();
Expand All @@ -222,7 +222,7 @@ gl_sframe augment_data(const gl_sframe &data,
size_t segment_start = (segment_id * backgrounds.size()) / nsegments;
size_t segment_end = ((segment_id + 1) * backgrounds.size()) / nsegments;
size_t row_number = segment_start;
for (const auto &background_ft :
for (const flexible_type &background_ft :
backgrounds.range_iterator(segment_start, segment_end)) {
row_number++;
flex_image flex_background =
Expand Down
16 changes: 11 additions & 5 deletions src/toolkits/object_detection/one_shot_object_detection/util/parameter_sampler.cpp
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Expand Up @@ -6,6 +6,7 @@
*/

#include <core/data/image/numeric_extension/perspective_projection.hpp>
#include <core/logging/assertions.hpp>
#include <limits>

#include <toolkits/object_detection/one_shot_object_detection/util/parameter_sampler.hpp>
Expand Down Expand Up @@ -62,6 +63,12 @@ void ParameterSampler::set_warped_corners(
warped_corners_[3] = warped_corners[2];
}

int generate_random_index(std::mt19937 engine, int range) {
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@nickjong nickjong Sep 13, 2019

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Do not copy the engine, otherwise you're actually going to get the same random values every time. Here you must pass the engine by reference or as a pointer. Your goal is to reuse the same engine across all the random draws for a single row, not produce draws from individual copies of the original engine.

DASSERT_GT(range, 0);
std::uniform_int_distribution<int> index_distribution(0, range-1);
return index_distribution(engine);
}

/* Function to sample all the parameters needed to build a transform, and
* then also build the transform.
*/
Expand All @@ -71,15 +78,14 @@ void ParameterSampler::sample(size_t background_width, size_t background_height,
std::seed_seq seed_seq = {static_cast<int>(seed), static_cast<int>(row_number)};
std::mt19937 engine(seed_seq);

std::uniform_int_distribution<int> index_distribution(0, INT_MAX);
theta_mean = theta_means_[index_distribution(engine) % theta_means_.size()];
phi_mean = phi_means_[index_distribution(engine) % phi_means_.size()];
gamma_mean = gamma_means_[index_distribution(engine) % gamma_means_.size()];
theta_mean = theta_means_[generate_random_index(engine, theta_means_.size())];
phi_mean = phi_means_[generate_random_index(engine, phi_means_.size())];
gamma_mean = gamma_means_[generate_random_index(engine, gamma_means_.size())];

std::normal_distribution<double> theta_distribution(theta_mean, angle_stdev_);
std::normal_distribution<double> phi_distribution(phi_mean, angle_stdev_);
std::normal_distribution<double> gamma_distribution(gamma_mean, angle_stdev_);
std::normal_distribution<double> focal_distribution((double)background_width,
std::normal_distribution<double> focal_distribution(static_cast<double>(background_width),
focal_stdev_);
theta_ = theta_distribution(engine);
phi_ = phi_distribution(engine);
Expand Down