Merge pull request #8636 from german77/irs_cluster_release
service: irs: Implement clustering processor
This commit is contained in:
liamwhite
GitHub
commit
64fd9f41a7
6 changed files with 323 additions and 7 deletions
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@ -451,6 +451,7 @@ add_library(core STATIC
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hle/service/hid/hidbus.h
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hle/service/hid/irs.cpp
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hle/service/hid/irs.h
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hle/service/hid/irs_ring_lifo.h
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hle/service/hid/ring_lifo.h
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hle/service/hid/xcd.cpp
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hle/service/hid/xcd.h
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@ -166,7 +166,7 @@ void IRS::RunClusteringProcessor(Kernel::HLERequestContext& ctx) {
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if (result.IsSuccess()) {
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auto& device = GetIrCameraSharedMemoryDeviceEntry(parameters.camera_handle);
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MakeProcessor<ClusteringProcessor>(parameters.camera_handle, device);
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MakeProcessorWithCoreContext<ClusteringProcessor>(parameters.camera_handle, device);
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auto& image_transfer_processor =
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GetProcessor<ClusteringProcessor>(parameters.camera_handle);
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image_transfer_processor.SetConfig(parameters.processor_config);
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47
src/core/hle/service/hid/irs_ring_lifo.h
Normal file
47
src/core/hle/service/hid/irs_ring_lifo.h
Normal file
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@ -0,0 +1,47 @@
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// SPDX-FileCopyrightText: Copyright 2022 yuzu Emulator Project
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// SPDX-License-Identifier: GPL-3.0-or-later
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#pragma once
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#include <array>
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#include "common/common_types.h"
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namespace Service::IRS {
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template <typename State, std::size_t max_buffer_size>
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struct Lifo {
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s64 sampling_number{};
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s64 buffer_count{};
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std::array<State, max_buffer_size> entries{};
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const State& ReadCurrentEntry() const {
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return entries[GetBufferTail()];
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}
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const State& ReadPreviousEntry() const {
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return entries[GetPreviousEntryIndex()];
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}
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s64 GetBufferTail() const {
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return sampling_number % max_buffer_size;
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}
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std::size_t GetPreviousEntryIndex() const {
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return static_cast<size_t>((GetBufferTail() + max_buffer_size - 1) % max_buffer_size);
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}
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std::size_t GetNextEntryIndex() const {
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return static_cast<size_t>((GetBufferTail() + 1) % max_buffer_size);
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}
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void WriteNextEntry(const State& new_state) {
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if (buffer_count < static_cast<s64>(max_buffer_size)) {
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buffer_count++;
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}
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sampling_number++;
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entries[GetBufferTail()] = new_state;
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}
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};
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} // namespace Service::IRS
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@ -1,34 +1,265 @@
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// SPDX-FileCopyrightText: Copyright 2022 yuzu Emulator Project
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// SPDX-License-Identifier: GPL-3.0-or-later
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#include <queue>
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#include "core/hid/emulated_controller.h"
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#include "core/hid/hid_core.h"
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#include "core/hle/service/hid/irsensor/clustering_processor.h"
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namespace Service::IRS {
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ClusteringProcessor::ClusteringProcessor(Core::IrSensor::DeviceFormat& device_format)
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: device(device_format) {
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ClusteringProcessor::ClusteringProcessor(Core::HID::HIDCore& hid_core_,
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Core::IrSensor::DeviceFormat& device_format,
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std::size_t npad_index)
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: device{device_format} {
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npad_device = hid_core_.GetEmulatedControllerByIndex(npad_index);
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device.mode = Core::IrSensor::IrSensorMode::ClusteringProcessor;
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device.camera_status = Core::IrSensor::IrCameraStatus::Unconnected;
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device.camera_internal_status = Core::IrSensor::IrCameraInternalStatus::Stopped;
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SetDefaultConfig();
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shared_memory = std::construct_at(
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reinterpret_cast<ClusteringSharedMemory*>(&device_format.state.processor_raw_data));
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Core::HID::ControllerUpdateCallback engine_callback{
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.on_change = [this](Core::HID::ControllerTriggerType type) { OnControllerUpdate(type); },
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.is_npad_service = true,
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};
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callback_key = npad_device->SetCallback(engine_callback);
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}
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ClusteringProcessor::~ClusteringProcessor() = default;
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ClusteringProcessor::~ClusteringProcessor() {
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npad_device->DeleteCallback(callback_key);
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};
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void ClusteringProcessor::StartProcessor() {}
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void ClusteringProcessor::StartProcessor() {
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device.camera_status = Core::IrSensor::IrCameraStatus::Available;
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device.camera_internal_status = Core::IrSensor::IrCameraInternalStatus::Ready;
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}
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void ClusteringProcessor::SuspendProcessor() {}
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void ClusteringProcessor::StopProcessor() {}
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void ClusteringProcessor::OnControllerUpdate(Core::HID::ControllerTriggerType type) {
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if (type != Core::HID::ControllerTriggerType::IrSensor) {
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return;
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}
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next_state = {};
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const auto camera_data = npad_device->GetCamera();
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auto filtered_image = camera_data.data;
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RemoveLowIntensityData(filtered_image);
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const auto window_start_x = static_cast<std::size_t>(current_config.window_of_interest.x);
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const auto window_start_y = static_cast<std::size_t>(current_config.window_of_interest.y);
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const auto window_end_x =
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window_start_x + static_cast<std::size_t>(current_config.window_of_interest.width);
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const auto window_end_y =
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window_start_y + static_cast<std::size_t>(current_config.window_of_interest.height);
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for (std::size_t y = window_start_y; y < window_end_y; y++) {
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for (std::size_t x = window_start_x; x < window_end_x; x++) {
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u8 pixel = GetPixel(filtered_image, x, y);
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if (pixel == 0) {
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continue;
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}
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const auto cluster = GetClusterProperties(filtered_image, x, y);
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if (cluster.pixel_count > current_config.pixel_count_max) {
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continue;
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}
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if (cluster.pixel_count < current_config.pixel_count_min) {
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continue;
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}
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// Cluster object limit reached
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if (next_state.object_count >= next_state.data.size()) {
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continue;
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}
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next_state.data[next_state.object_count] = cluster;
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next_state.object_count++;
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}
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}
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next_state.sampling_number = camera_data.sample;
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next_state.timestamp = next_state.timestamp + 131;
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next_state.ambient_noise_level = Core::IrSensor::CameraAmbientNoiseLevel::Low;
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shared_memory->clustering_lifo.WriteNextEntry(next_state);
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if (!IsProcessorActive()) {
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StartProcessor();
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}
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}
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void ClusteringProcessor::RemoveLowIntensityData(std::vector<u8>& data) {
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for (u8& pixel : data) {
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if (pixel < current_config.pixel_count_min) {
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pixel = 0;
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}
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}
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}
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ClusteringProcessor::ClusteringData ClusteringProcessor::GetClusterProperties(std::vector<u8>& data,
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std::size_t x,
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std::size_t y) {
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using DataPoint = Common::Point<std::size_t>;
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std::queue<DataPoint> search_points{};
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ClusteringData current_cluster = GetPixelProperties(data, x, y);
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SetPixel(data, x, y, 0);
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search_points.emplace<DataPoint>({x, y});
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while (!search_points.empty()) {
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const auto point = search_points.front();
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search_points.pop();
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// Avoid negative numbers
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if (point.x == 0 || point.y == 0) {
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continue;
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}
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std::array<DataPoint, 4> new_points{
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DataPoint{point.x - 1, point.y},
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{point.x, point.y - 1},
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{point.x + 1, point.y},
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{point.x, point.y + 1},
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};
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for (const auto new_point : new_points) {
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if (new_point.x >= width) {
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continue;
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}
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if (new_point.y >= height) {
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continue;
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}
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if (GetPixel(data, new_point.x, new_point.y) < current_config.object_intensity_min) {
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continue;
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}
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const ClusteringData cluster = GetPixelProperties(data, new_point.x, new_point.y);
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current_cluster = MergeCluster(current_cluster, cluster);
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SetPixel(data, new_point.x, new_point.y, 0);
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search_points.emplace<DataPoint>({new_point.x, new_point.y});
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}
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}
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return current_cluster;
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}
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ClusteringProcessor::ClusteringData ClusteringProcessor::GetPixelProperties(
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const std::vector<u8>& data, std::size_t x, std::size_t y) const {
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return {
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.average_intensity = GetPixel(data, x, y) / 255.0f,
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.centroid =
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{
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.x = static_cast<f32>(x),
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.y = static_cast<f32>(y),
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},
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.pixel_count = 1,
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.bound =
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{
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.x = static_cast<s16>(x),
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.y = static_cast<s16>(y),
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.width = 1,
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.height = 1,
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},
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};
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}
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ClusteringProcessor::ClusteringData ClusteringProcessor::MergeCluster(
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const ClusteringData a, const ClusteringData b) const {
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const f32 a_pixel_count = static_cast<f32>(a.pixel_count);
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const f32 b_pixel_count = static_cast<f32>(b.pixel_count);
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const f32 pixel_count = a_pixel_count + b_pixel_count;
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const f32 average_intensity =
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(a.average_intensity * a_pixel_count + b.average_intensity * b_pixel_count) / pixel_count;
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const Core::IrSensor::IrsCentroid centroid = {
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.x = (a.centroid.x * a_pixel_count + b.centroid.x * b_pixel_count) / pixel_count,
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.y = (a.centroid.y * a_pixel_count + b.centroid.y * b_pixel_count) / pixel_count,
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};
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s16 bound_start_x = a.bound.x < b.bound.x ? a.bound.x : b.bound.x;
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s16 bound_start_y = a.bound.y < b.bound.y ? a.bound.y : b.bound.y;
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s16 a_bound_end_x = a.bound.x + a.bound.width;
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s16 a_bound_end_y = a.bound.y + a.bound.height;
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s16 b_bound_end_x = b.bound.x + b.bound.width;
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s16 b_bound_end_y = b.bound.y + b.bound.height;
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const Core::IrSensor::IrsRect bound = {
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.x = bound_start_x,
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.y = bound_start_y,
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.width = a_bound_end_x > b_bound_end_x ? static_cast<s16>(a_bound_end_x - bound_start_x)
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: static_cast<s16>(b_bound_end_x - bound_start_x),
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.height = a_bound_end_y > b_bound_end_y ? static_cast<s16>(a_bound_end_y - bound_start_y)
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: static_cast<s16>(b_bound_end_y - bound_start_y),
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};
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return {
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.average_intensity = average_intensity,
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.centroid = centroid,
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.pixel_count = static_cast<u32>(pixel_count),
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.bound = bound,
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};
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}
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u8 ClusteringProcessor::GetPixel(const std::vector<u8>& data, std::size_t x, std::size_t y) const {
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if ((y * width) + x > data.size()) {
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return 0;
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}
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return data[(y * width) + x];
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}
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void ClusteringProcessor::SetPixel(std::vector<u8>& data, std::size_t x, std::size_t y, u8 value) {
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if ((y * width) + x > data.size()) {
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return;
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}
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data[(y * width) + x] = value;
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}
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void ClusteringProcessor::SetDefaultConfig() {
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using namespace std::literals::chrono_literals;
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current_config.camera_config.exposure_time = std::chrono::microseconds(200ms).count();
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current_config.camera_config.gain = 2;
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current_config.camera_config.is_negative_used = false;
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current_config.camera_config.light_target = Core::IrSensor::CameraLightTarget::BrightLeds;
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current_config.window_of_interest = {
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.x = 0,
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.y = 0,
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.width = width,
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.height = height,
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};
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current_config.pixel_count_min = 3;
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current_config.pixel_count_max = static_cast<u32>(GetDataSize(format));
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current_config.is_external_light_filter_enabled = true;
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current_config.object_intensity_min = 150;
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npad_device->SetCameraFormat(format);
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}
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void ClusteringProcessor::SetConfig(Core::IrSensor::PackedClusteringProcessorConfig config) {
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current_config.camera_config.exposure_time = config.camera_config.exposure_time;
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current_config.camera_config.gain = config.camera_config.gain;
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current_config.camera_config.is_negative_used = config.camera_config.is_negative_used;
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current_config.camera_config.light_target =
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static_cast<Core::IrSensor::CameraLightTarget>(config.camera_config.light_target);
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current_config.window_of_interest = config.window_of_interest;
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current_config.pixel_count_min = config.pixel_count_min;
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current_config.pixel_count_max = config.pixel_count_max;
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current_config.is_external_light_filter_enabled = config.is_external_light_filter_enabled;
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current_config.object_intensity_min = config.object_intensity_min;
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LOG_INFO(Service_IRS,
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"Processor config, exposure_time={}, gain={}, is_negative_used={}, "
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"light_target={}, window_of_interest=({}, {}, {}, {}), pixel_count_min={}, "
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"pixel_count_max={}, is_external_light_filter_enabled={}, object_intensity_min={}",
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current_config.camera_config.exposure_time, current_config.camera_config.gain,
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current_config.camera_config.is_negative_used,
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current_config.camera_config.light_target, current_config.window_of_interest.x,
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current_config.window_of_interest.y, current_config.window_of_interest.width,
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current_config.window_of_interest.height, current_config.pixel_count_min,
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current_config.pixel_count_max, current_config.is_external_light_filter_enabled,
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current_config.object_intensity_min);
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npad_device->SetCameraFormat(format);
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}
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} // namespace Service::IRS
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@ -5,12 +5,19 @@
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#include "common/common_types.h"
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#include "core/hid/irs_types.h"
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#include "core/hle/service/hid/irs_ring_lifo.h"
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#include "core/hle/service/hid/irsensor/processor_base.h"
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namespace Core::HID {
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class EmulatedController;
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} // namespace Core::HID
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namespace Service::IRS {
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class ClusteringProcessor final : public ProcessorBase {
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public:
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explicit ClusteringProcessor(Core::IrSensor::DeviceFormat& device_format);
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explicit ClusteringProcessor(Core::HID::HIDCore& hid_core_,
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Core::IrSensor::DeviceFormat& device_format,
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std::size_t npad_index);
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~ClusteringProcessor() override;
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// Called when the processor is initialized
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@ -26,6 +33,10 @@ public:
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void SetConfig(Core::IrSensor::PackedClusteringProcessorConfig config);
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private:
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static constexpr auto format = Core::IrSensor::ImageTransferProcessorFormat::Size320x240;
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static constexpr std::size_t width = 320;
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static constexpr std::size_t height = 240;
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// This is nn::irsensor::ClusteringProcessorConfig
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struct ClusteringProcessorConfig {
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Core::IrSensor::CameraConfig camera_config;
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@ -68,7 +79,32 @@ private:
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static_assert(sizeof(ClusteringProcessorState) == 0x198,
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"ClusteringProcessorState is an invalid size");
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struct ClusteringSharedMemory {
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Service::IRS::Lifo<ClusteringProcessorState, 6> clustering_lifo;
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static_assert(sizeof(clustering_lifo) == 0x9A0, "clustering_lifo is an invalid size");
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INSERT_PADDING_WORDS(0x11F);
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};
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static_assert(sizeof(ClusteringSharedMemory) == 0xE20,
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"ClusteringSharedMemory is an invalid size");
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void OnControllerUpdate(Core::HID::ControllerTriggerType type);
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void RemoveLowIntensityData(std::vector<u8>& data);
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ClusteringData GetClusterProperties(std::vector<u8>& data, std::size_t x, std::size_t y);
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ClusteringData GetPixelProperties(const std::vector<u8>& data, std::size_t x,
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std::size_t y) const;
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ClusteringData MergeCluster(const ClusteringData a, const ClusteringData b) const;
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u8 GetPixel(const std::vector<u8>& data, std::size_t x, std::size_t y) const;
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void SetPixel(std::vector<u8>& data, std::size_t x, std::size_t y, u8 value);
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// Sets config parameters of the camera
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void SetDefaultConfig();
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ClusteringSharedMemory* shared_memory = nullptr;
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ClusteringProcessorState next_state{};
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ClusteringProcessorConfig current_config{};
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Core::IrSensor::DeviceFormat& device;
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Core::HID::EmulatedController* npad_device;
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int callback_key{};
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};
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} // namespace Service::IRS
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@ -804,6 +804,7 @@ void GRenderWindow::TouchEndEvent() {
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}
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void GRenderWindow::InitializeCamera() {
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constexpr auto camera_update_ms = std::chrono::milliseconds{50}; // (50ms, 20Hz)
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if (!Settings::values.enable_ir_sensor) {
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return;
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}
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@ -837,7 +838,7 @@ void GRenderWindow::InitializeCamera() {
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camera_timer = std::make_unique<QTimer>();
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connect(camera_timer.get(), &QTimer::timeout, [this] { RequestCameraCapture(); });
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// This timer should be dependent of camera resolution 5ms for every 100 pixels
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camera_timer->start(100);
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camera_timer->start(camera_update_ms);
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}
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void GRenderWindow::FinalizeCamera() {
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Reference in a new issue