Release 2.26.0

.github/workflows/main.workflow.yml

@@ -67,6 +67,8 @@ jobs:
         exclude:
           - os: windows-latest
             cmake: '3.10.x'
+          - os: macos-latest # Skip the old cmake on latest macos - doesn't handle ARM64 aarch correctly
+            cmake: '3.10.x'
 
     steps:
     - name: Cache .hunter folder
@@ -333,4 +335,4 @@ jobs:
         upload_url: ${{ steps.createRelease.outputs.upload_url }}
         asset_path: ${{ github.workspace }}/depthai-core-${{ steps.tag.outputs.version }}-win32-no-opencv.zip
         asset_name: depthai-core-${{ steps.tag.outputs.version }}-win32-no-opencv.zip
-        asset_content_type: application/octet-stream
+        asset_content_type: application/octet-stream

CMakeLists.txt

@@ -46,7 +46,7 @@ if(WIN32)
 endif()
 
 # Create depthai project
-project(depthai VERSION "2.25.1" LANGUAGES CXX C)
+project(depthai VERSION "2.26.0" LANGUAGES CXX C)
 get_directory_property(has_parent PARENT_DIRECTORY)
 if(has_parent)
     set(DEPTHAI_VERSION ${PROJECT_VERSION} PARENT_SCOPE)
@@ -219,6 +219,7 @@ add_library(${TARGET_CORE_NAME}
     src/pipeline/node/DetectionNetwork.cpp
     src/pipeline/node/Script.cpp
     src/pipeline/node/SpatialDetectionNetwork.cpp
+    src/pipeline/node/ImageAlign.cpp
     src/pipeline/node/SystemLogger.cpp
     src/pipeline/node/SpatialLocationCalculator.cpp
     src/pipeline/node/AprilTag.cpp
@@ -230,6 +231,7 @@ add_library(${TARGET_CORE_NAME}
     src/pipeline/node/DetectionParser.cpp
     src/pipeline/node/UVC.cpp
     src/pipeline/node/PointCloud.cpp
+    src/pipeline/node/Cast.cpp
     src/pipeline/datatype/Buffer.cpp
     src/pipeline/datatype/ImgFrame.cpp
     src/pipeline/datatype/EncodedFrame.cpp
@@ -250,6 +252,7 @@ add_library(${TARGET_CORE_NAME}
     src/pipeline/datatype/EdgeDetectorConfig.cpp
     src/pipeline/datatype/TrackedFeatures.cpp
     src/pipeline/datatype/FeatureTrackerConfig.cpp
+    src/pipeline/datatype/ImageAlignConfig.cpp
     src/pipeline/datatype/ToFConfig.cpp
     src/pipeline/datatype/PointCloudConfig.cpp
     src/pipeline/datatype/PointCloudData.cpp

cmake/Depthai/DepthaiBootloaderConfig.cmake

@@ -3,5 +3,5 @@ set(DEPTHAI_BOOTLOADER_MATURITY "release")
 # set(DEPTHAI_BOOTLOADER_MATURITY "snapshot")
 
 # "version if applicable"
-set(DEPTHAI_BOOTLOADER_VERSION "0.0.27")
-# set(DEPTHAI_BOOTLOADER_VERSION "0.0.24+57c26493754e2f00e57f6594b0b1a317f762d5f2")
+set(DEPTHAI_BOOTLOADER_VERSION "0.0.28")
+# set(DEPTHAI_BOOTLOADER_VERSION "0.0.27+5fb331f993adceeeda72202c233a9e3939ab3dab")

cmake/Depthai/DepthaiDeviceSideConfig.cmake

@@ -2,7 +2,7 @@
 set(DEPTHAI_DEVICE_SIDE_MATURITY "snapshot")
 
 # "full commit hash of device side binary"
-set(DEPTHAI_DEVICE_SIDE_COMMIT "c7127782f2da45aac89d5b5b816d04cc45ae40be")
+set(DEPTHAI_DEVICE_SIDE_COMMIT "24a3b465b979de3f69410cd225914d8bd029f3ba")
 
 # "version if applicable"
 set(DEPTHAI_DEVICE_SIDE_VERSION "")

examples/CMakeLists.txt

@@ -196,6 +196,22 @@ hunter_private_data(
     LOCATION concat_model
 )
 
+# blur model
+hunter_private_data(
+    URL "https://artifacts.luxonis.com/artifactory/luxonis-depthai-data-local/network/blur_simplified_openvino_2021.4_6shave.blob"
+    SHA1 "14d543bbaceffa438071f83be58ad22a07ce33ee"
+    FILE "blur_simplified_openvino_2021.4_6shave.blob"
+    LOCATION blur_model
+)
+
+# diff model
+hunter_private_data(
+    URL "https://artifacts.luxonis.com/artifactory/luxonis-depthai-data-local/network/diff_openvino_2022.1_6shave.blob"
+    SHA1 "fe9600e617d222f986a699f18e77e80ce2485000"
+    FILE "diff_openvino_2022.1_6shave.blob"
+    LOCATION diff_model
+)
+
 # normalization model
 hunter_private_data(
     URL "https://artifacts.luxonis.com/artifactory/luxonis-depthai-data-local/network/normalize_openvino_2021.4_4shave.blob"
@@ -386,3 +402,23 @@ dai_add_example(imu_video_synced Sync/imu_video_synced.cpp ON OFF)
 if(DEPTHAI_HAVE_PCL_SUPPORT)
     dai_add_example(visualize_pointcloud PointCloud/visualize_pointcloud.cpp ON ON)
 endif()
+
+# ImageAlign
+dai_add_example(tof_align ImageAlign/tof_align.cpp OFF OFF)
+dai_add_example(image_align ImageAlign/image_align.cpp ON OFF)
+dai_add_example(thermal_align ImageAlign/thermal_align.cpp OFF OFF)
+dai_add_example(depth_align ImageAlign/depth_align.cpp ON OFF)
+
+# Cast
+dai_add_example(blur Cast/blur.cpp ON OFF)
+target_compile_definitions(blur PRIVATE BLOB_PATH="${blur_model}")
+dai_add_example(concat Cast/concat.cpp ON OFF)
+target_compile_definitions(concat PRIVATE BLOB_PATH="${concat_model}")
+dai_add_example(diff Cast/diff.cpp ON OFF)
+target_compile_definitions(diff PRIVATE BLOB_PATH="${diff_model}")
+
+# ToF
+dai_add_example(spatial_tiny_yolo_tof_v3 SpatialDetection/spatial_tiny_yolo_tof.cpp OFF OFF)
+dai_add_example(spatial_tiny_yolo_tof_v4 SpatialDetection/spatial_tiny_yolo_tof.cpp OFF OFF)
+target_compile_definitions(spatial_tiny_yolo_tof_v3 PRIVATE BLOB_PATH="${tiny_yolo_v3_blob}")
+target_compile_definitions(spatial_tiny_yolo_tof_v4 PRIVATE BLOB_PATH="${tiny_yolo_v4_blob}")

examples/Camera/thermal_cam.cpp

@@ -22,17 +22,18 @@ int main() {
     // Find the sensor width, height.
     int width, height;
     bool thermal_found = false;
-    for (auto &features : d.getConnectedCameraFeatures()) {
-        if (std::find_if(features.supportedTypes.begin(), features.supportedTypes.end(), [](const dai::CameraSensorType &type) {
-            return type == dai::CameraSensorType::THERMAL;
-        }) != features.supportedTypes.end()) {
-            thermal->setBoardSocket(features.socket); // Thermal will always be on CAM_E
+    for(auto& features : d.getConnectedCameraFeatures()) {
+        if(std::find_if(features.supportedTypes.begin(),
+                        features.supportedTypes.end(),
+                        [](const dai::CameraSensorType& type) { return type == dai::CameraSensorType::THERMAL; })
+           != features.supportedTypes.end()) {
+            thermal->setBoardSocket(features.socket);  // Thermal will always be on CAM_E
             width = features.width;
             height = features.height;
             thermal_found = true;
         }
     }
-    if (!thermal_found) {
+    if(!thermal_found) {
         throw std::runtime_error("Thermal camera not found!");
     }
     thermal->setPreviewSize(width, height);

examples/Cast/blur.cpp

@@ -0,0 +1,50 @@
+#include <depthai/depthai.hpp>
+#include <opencv2/opencv.hpp>
+
+constexpr int SHAPE = 300;
+
+int main() {
+    dai::Pipeline p;
+
+    auto camRgb = p.create<dai::node::ColorCamera>();
+    auto nn = p.create<dai::node::NeuralNetwork>();
+    auto rgbOut = p.create<dai::node::XLinkOut>();
+    auto cast = p.create<dai::node::Cast>();
+    auto castXout = p.create<dai::node::XLinkOut>();
+
+    camRgb->setPreviewSize(SHAPE, SHAPE);
+    camRgb->setInterleaved(false);
+
+    nn->setBlobPath(BLOB_PATH);
+
+    rgbOut->setStreamName("rgb");
+    castXout->setStreamName("cast");
+
+    cast->setOutputFrameType(dai::ImgFrame::Type::BGR888p);
+
+    // Linking
+    camRgb->preview.link(nn->input);
+    camRgb->preview.link(rgbOut->input);
+    nn->out.link(cast->input);
+    cast->output.link(castXout->input);
+
+    dai::Device device(p);
+    auto qCam = device.getOutputQueue("rgb", 4, false);
+    auto qCast = device.getOutputQueue("cast", 4, false);
+
+    while(true) {
+        auto inCast = qCast->get<dai::ImgFrame>();
+        auto inRgb = qCam->get<dai::ImgFrame>();
+
+        if(inCast && inRgb) {
+            cv::imshow("Blur", inCast->getCvFrame());
+            cv::imshow("Original", inRgb->getCvFrame());
+        }
+
+        if(cv::waitKey(1) == 'q') {
+            break;
+        }
+    }
+
+    return 0;
+}

examples/Cast/concat.cpp

@@ -0,0 +1,63 @@
+#include <depthai/depthai.hpp>
+#include <opencv2/opencv.hpp>
+
+constexpr int SHAPE = 300;
+
+int main() {
+    dai::Pipeline p;
+
+    auto camRgb = p.create<dai::node::ColorCamera>();
+    auto left = p.create<dai::node::MonoCamera>();
+    auto right = p.create<dai::node::MonoCamera>();
+    auto manipLeft = p.create<dai::node::ImageManip>();
+    auto manipRight = p.create<dai::node::ImageManip>();
+    auto nn = p.create<dai::node::NeuralNetwork>();
+    auto cast = p.create<dai::node::Cast>();
+    auto castXout = p.create<dai::node::XLinkOut>();
+
+    camRgb->setPreviewSize(SHAPE, SHAPE);
+    camRgb->setInterleaved(false);
+    camRgb->setColorOrder(dai::ColorCameraProperties::ColorOrder::BGR);
+
+    left->setCamera("left");
+    left->setResolution(dai::MonoCameraProperties::SensorResolution::THE_400_P);
+    manipLeft->initialConfig.setResize(SHAPE, SHAPE);
+    manipLeft->initialConfig.setFrameType(dai::ImgFrame::Type::BGR888p);
+
+    right->setCamera("right");
+    right->setResolution(dai::MonoCameraProperties::SensorResolution::THE_400_P);
+    manipRight->initialConfig.setResize(SHAPE, SHAPE);
+    manipRight->initialConfig.setFrameType(dai::ImgFrame::Type::BGR888p);
+
+    nn->setBlobPath(BLOB_PATH);
+    nn->setNumInferenceThreads(2);
+
+    castXout->setStreamName("cast");
+    cast->setOutputFrameType(dai::ImgFrame::Type::BGR888p);
+
+    // Linking
+    left->out.link(manipLeft->inputImage);
+    right->out.link(manipRight->inputImage);
+    manipLeft->out.link(nn->inputs["img1"]);
+    camRgb->preview.link(nn->inputs["img2"]);
+    manipRight->out.link(nn->inputs["img3"]);
+    nn->out.link(cast->input);
+    cast->output.link(castXout->input);
+
+    // Pipeline is defined, now we can connect to the device
+    dai::Device device(p);
+    auto qCast = device.getOutputQueue("cast", 4, false);
+
+    while(true) {
+        auto inCast = qCast->get<dai::ImgFrame>();
+        if(inCast) {
+            cv::imshow("Concated frames", inCast->getCvFrame());
+        }
+
+        if(cv::waitKey(1) == 'q') {
+            break;
+        }
+    }
+
+    return 0;
+}

examples/Cast/diff.cpp

@@ -0,0 +1,66 @@
+#include <depthai/depthai.hpp>
+#include <filesystem>
+#include <opencv2/opencv.hpp>
+
+constexpr int SHAPE = 720;
+
+int main() {
+    dai::Pipeline p;
+
+    auto camRgb = p.create<dai::node::ColorCamera>();
+    auto nn = p.create<dai::node::NeuralNetwork>();
+    auto script = p.create<dai::node::Script>();
+    auto rgbXout = p.create<dai::node::XLinkOut>();
+    auto cast = p.create<dai::node::Cast>();
+    auto castXout = p.create<dai::node::XLinkOut>();
+
+    camRgb->setVideoSize(SHAPE, SHAPE);
+    camRgb->setPreviewSize(SHAPE, SHAPE);
+    camRgb->setInterleaved(false);
+
+    nn->setBlobPath(BLOB_PATH);
+
+    script->setScript(R"(
+        old = node.io['in'].get()
+        while True:
+            frame = node.io['in'].get()
+            node.io['img1'].send(old)
+            node.io['img2'].send(frame)
+            old = frame
+    )");
+
+    rgbXout->setStreamName("rgb");
+    castXout->setStreamName("cast");
+    cast->setOutputFrameType(dai::RawImgFrame::Type::GRAY8);
+
+    // Linking
+    camRgb->preview.link(script->inputs["in"]);
+    script->outputs["img1"].link(nn->inputs["img1"]);
+    script->outputs["img2"].link(nn->inputs["img2"]);
+    camRgb->video.link(rgbXout->input);
+    nn->out.link(cast->input);
+    cast->output.link(castXout->input);
+
+    // Pipeline is defined, now we can connect to the device
+    dai::Device device(p);
+    auto qCam = device.getOutputQueue("rgb", 4, false);
+    auto qCast = device.getOutputQueue("cast", 4, false);
+
+    while(true) {
+        auto colorFrame = qCam->get<dai::ImgFrame>();
+        if(colorFrame) {
+            cv::imshow("Color", colorFrame->getCvFrame());
+        }
+
+        auto inCast = qCast->get<dai::ImgFrame>();
+        if(inCast) {
+            cv::imshow("Diff", inCast->getCvFrame());
+        }
+
+        if(cv::waitKey(1) == 'q') {
+            break;
+        }
+    }
+
+    return 0;
+}

examples/FeatureTracker/feature_tracker.cpp

@@ -16,7 +16,7 @@ class FeatureTrackerDrawer {
     // for how many frames the feature is tracked
     static int trackedFeaturesPathLength;
 
-    using featureIdType = decltype(dai::Point2f::x);
+    using featureIdType = decltype(dai::TrackedFeature::id);
 
     std::unordered_set<featureIdType> trackedIDs;
     std::unordered_map<featureIdType, std::deque<dai::Point2f>> trackedFeaturesPath;