Merge remote-tracking branch 'origin/develop' into HEAD

.github/workflows/main.yml

@@ -156,11 +156,15 @@ jobs:
         run: python3 -m pip wheel . -w ./wheelhouse/ --verbose
       - name: Auditing wheel
         run: for whl in wheelhouse/*.whl; do auditwheel repair "$whl" --plat linux_armv7l -w wheelhouse/audited/; done
+      - name: Install tweaked auditwheel and add armv6l tag
+        run: |
+          python3 -m pip install git+https://github.com/luxonis/auditwheel@main
+          for whl in wheelhouse/*.whl; do python3 -m auditwheel addtag -t linux_armv7l linux_armv6l -w wheelhouse/postaudited/ "$whl"; done
       - name: Archive wheel artifacts
         uses: actions/upload-artifact@v3
         with:
           name: audited-wheels
-          path: wheelhouse/audited/
+          path: wheelhouse/postaudited/
       - name: Deploy wheels to artifactory (if not a release)
         if: startsWith(github.ref, 'refs/tags/v') != true
         run: bash ./ci/upload-artifactory.sh
@@ -566,7 +570,7 @@ jobs:
           owner: luxonis
           workflow: regression_test.yml
           workflow_inputs: '{"commit": "${{ github.ref }}", "parent_url": "https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}"}'
-          workflow_timeout_seconds: 120 # Default: 300
+          workflow_timeout_seconds: 300 # was 120  Default: 300
 
       - name: Release
         run: echo "https://github.com/luxonis/depthai-core-hil-tests/actions/runs/${{steps.return_dispatch.outputs.run_id}}" >> $GITHUB_STEP_SUMMARY

examples/Script/script_read_calibration.py

@@ -0,0 +1,33 @@
+#!/usr/bin/env python3
+import depthai as dai
+
+# Start defining a pipeline
+pipeline = dai.Pipeline()
+
+# Script node
+script = pipeline.create(dai.node.Script)
+script.setProcessor(dai.ProcessorType.LEON_CSS)
+script.setScript("""
+    import time
+
+    cal = Device.readCalibration2()
+    left_camera_id = cal.getStereoLeftCameraId()
+    right_camera_id = cal.getStereoRightCameraId()
+
+    extrinsics = cal.getCameraExtrinsics(left_camera_id, right_camera_id)
+    intrinsics_left = cal.getCameraIntrinsics(left_camera_id)
+
+    node.info(extrinsics.__str__())
+    node.info(intrinsics_left.__str__())
+
+    time.sleep(1)
+    node.io['end'].send(Buffer(32))
+""")
+
+xout = pipeline.create(dai.node.XLinkOut)
+xout.setStreamName('end')
+script.outputs['end'].link(xout.input)
+
+# Connect to device with pipeline
+with dai.Device(pipeline) as device:
+    device.getOutputQueue('end').get()

examples/SpatialDetection/spatial_calculator_multi_roi.py

@@ -67,7 +67,10 @@
         depthFrame = inDepth.getFrame() # depthFrame values are in millimeters
 
         depth_downscaled = depthFrame[::4]
-        min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
+        if np.all(depth_downscaled == 0):
+            min_depth = 0  # Set a default minimum depth value when all elements are zero
+        else:
+            min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
         max_depth = np.percentile(depth_downscaled, 99)
         depthFrameColor = np.interp(depthFrame, (min_depth, max_depth), (0, 255)).astype(np.uint8)
         depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_HOT)

examples/SpatialDetection/spatial_location_calculator.py

@@ -75,7 +75,10 @@
         depthFrame = inDepth.getFrame() # depthFrame values are in millimeters
 
         depth_downscaled = depthFrame[::4]
-        min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
+        if np.all(depth_downscaled == 0):
+            min_depth = 0  # Set a default minimum depth value when all elements are zero
+        else:
+            min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
         max_depth = np.percentile(depth_downscaled, 99)
         depthFrameColor = np.interp(depthFrame, (min_depth, max_depth), (0, 255)).astype(np.uint8)
         depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_HOT)

examples/SpatialDetection/spatial_mobilenet.py

@@ -115,7 +115,10 @@
         depthFrame = depth.getFrame() # depthFrame values are in millimeters
 
         depth_downscaled = depthFrame[::4]
-        min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
+        if np.all(depth_downscaled == 0):
+            min_depth = 0  # Set a default minimum depth value when all elements are zero
+        else:
+            min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
         max_depth = np.percentile(depth_downscaled, 99)
         depthFrameColor = np.interp(depthFrame, (min_depth, max_depth), (0, 255)).astype(np.uint8)
         depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_HOT)

examples/SpatialDetection/spatial_mobilenet_mono.py

@@ -118,7 +118,10 @@
         depthFrame = inDepth.getFrame() # depthFrame values are in millimeters
 
         depth_downscaled = depthFrame[::4]
-        min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
+        if np.all(depth_downscaled == 0):
+            min_depth = 0  # Set a default minimum depth value when all elements are zero
+        else:
+            min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
         max_depth = np.percentile(depth_downscaled, 99)
         depthFrameColor = np.interp(depthFrame, (min_depth, max_depth), (0, 255)).astype(np.uint8)
         depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_HOT)

examples/SpatialDetection/spatial_tiny_yolo.py

@@ -148,7 +148,10 @@
         depthFrame = depth.getFrame() # depthFrame values are in millimeters
 
         depth_downscaled = depthFrame[::4]
-        min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
+        if np.all(depth_downscaled == 0):
+            min_depth = 0  # Set a default minimum depth value when all elements are zero
+        else:
+            min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
         max_depth = np.percentile(depth_downscaled, 99)
         depthFrameColor = np.interp(depthFrame, (min_depth, max_depth), (0, 255)).astype(np.uint8)
         depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_HOT)

examples/StereoDepth/depth_crop_control.py

@@ -64,7 +64,10 @@
 
         # Frame is transformed, the color map will be applied to highlight the depth info
         depth_downscaled = depthFrame[::4]
-        min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
+        if np.all(depth_downscaled == 0):
+            min_depth = 0  # Set a default minimum depth value when all elements are zero
+        else:
+            min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
         max_depth = np.percentile(depth_downscaled, 99)
         depthFrameColor = np.interp(depthFrame, (min_depth, max_depth), (0, 255)).astype(np.uint8)
         depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_HOT)

examples/StereoDepth/rgb_depth_aligned.py

@@ -3,11 +3,16 @@
 import cv2
 import numpy as np
 import depthai as dai
+import argparse
 
 # Weights to use when blending depth/rgb image (should equal 1.0)
 rgbWeight = 0.4
 depthWeight = 0.6
 
+parser = argparse.ArgumentParser()
+parser.add_argument('-alpha', type=float, default=None, help="Alpha scaling parameter to increase float. [0,1] valid interval.")
+args = parser.parse_args()
+alpha = args.alpha
 
 def updateBlendWeights(percent_rgb):
     """
@@ -21,9 +26,6 @@ def updateBlendWeights(percent_rgb):
     depthWeight = 1.0 - rgbWeight
 
 
-# Optional. If set (True), the ColorCamera is downscaled from 1080p to 720p.
-# Otherwise (False), the aligned depth is automatically upscaled to 1080p
-downscaleColor = True
 fps = 30
 # The disparity is computed at this resolution, then upscaled to RGB resolution
 monoResolution = dai.MonoCameraProperties.SensorResolution.THE_720_P
@@ -34,7 +36,7 @@ def updateBlendWeights(percent_rgb):
 queueNames = []
 
 # Define sources and outputs
-camRgb = pipeline.create(dai.node.ColorCamera)
+camRgb = pipeline.create(dai.node.Camera)
 left = pipeline.create(dai.node.MonoCamera)
 right = pipeline.create(dai.node.MonoCamera)
 stereo = pipeline.create(dai.node.StereoDepth)
@@ -48,15 +50,17 @@ def updateBlendWeights(percent_rgb):
 queueNames.append("disp")
 
 #Properties
-camRgb.setBoardSocket(dai.CameraBoardSocket.CAM_A)
-camRgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_1080_P)
+rgbCamSocket = dai.CameraBoardSocket.CAM_A
+
+camRgb.setBoardSocket(rgbCamSocket)
+camRgb.setSize(1280, 720)
 camRgb.setFps(fps)
-if downscaleColor: camRgb.setIspScale(2, 3)
+
 # For now, RGB needs fixed focus to properly align with depth.
 # This value was used during calibration
 try:
     calibData = device.readCalibration2()
-    lensPosition = calibData.getLensPosition(dai.CameraBoardSocket.CAM_A)
+    lensPosition = calibData.getLensPosition(rgbCamSocket)
     if lensPosition:
         camRgb.initialControl.setManualFocus(lensPosition)
 except:
@@ -71,14 +75,19 @@ def updateBlendWeights(percent_rgb):
 stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
 # LR-check is required for depth alignment
 stereo.setLeftRightCheck(True)
-stereo.setDepthAlign(dai.CameraBoardSocket.CAM_A)
+stereo.setDepthAlign(rgbCamSocket)
 
 # Linking
-camRgb.isp.link(rgbOut.input)
+camRgb.video.link(rgbOut.input)
 left.out.link(stereo.left)
 right.out.link(stereo.right)
 stereo.disparity.link(disparityOut.input)
 
+camRgb.setMeshSource(dai.CameraProperties.WarpMeshSource.CALIBRATION)
+if alpha is not None:
+    camRgb.setCalibrationAlpha(alpha)
+    stereo.setAlphaScaling(alpha)
+
 # Connect to device and start pipeline
 with device:
     device.startPipeline(pipeline)

examples/StereoDepth/stereo_depth_from_host.py

@@ -588,6 +588,9 @@ def __init__(self, config):
 fov = 71.86
 focal = width / (2 * math.tan(fov / 2 / 180 * math.pi))
 
+stereo.setBaseline(baseline/10)
+stereo.setFocalLength(focal)
+
 streams = ['left', 'right']
 if outRectified:
     streams.extend(['rectified_left', 'rectified_right'])

examples/mixed/rotated_spatial_detections.py

@@ -106,7 +106,10 @@
         depthFrame = depth.getFrame() # depthFrame values are in millimeters
 
         depth_downscaled = depthFrame[::4]
-        min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
+        if np.all(depth_downscaled == 0):
+            min_depth = 0  # Set a default minimum depth value when all elements are zero
+        else:
+            min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1)
         max_depth = np.percentile(depth_downscaled, 99)
         depthFrameColor = np.interp(depthFrame, (min_depth, max_depth), (0, 255)).astype(np.uint8)
         depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_HOT)

pyproject.toml

@@ -1,2 +1,2 @@
 [build-system]
-requires = ["setuptools", "wheel", "mypy", "cmake==3.25"]
+requires = ["setuptools", "wheel", "mypy<=1.3.0", "cmake==3.25"]

src/pipeline/datatype/ToFConfigBindings.cpp

@@ -48,10 +48,10 @@ void bind_tofconfig(pybind11::module& m, void* pCallstack){
 
     depthParams
         .def(py::init<>())
-        .def_readwrite("enable", &RawToFConfig::DepthParams::enable, DOC(dai, RawToFConfig, DepthParams, enable))
         .def_readwrite("freqModUsed", &RawToFConfig::DepthParams::freqModUsed, DOC(dai, RawToFConfig, DepthParams, freqModUsed))
         .def_readwrite("avgPhaseShuffle", &RawToFConfig::DepthParams::avgPhaseShuffle, DOC(dai, RawToFConfig, DepthParams, avgPhaseShuffle))
         .def_readwrite("minimumAmplitude", &RawToFConfig::DepthParams::minimumAmplitude, DOC(dai, RawToFConfig, DepthParams, minimumAmplitude))
+        .def_readwrite("median", &RawToFConfig::DepthParams::median, DOC(dai, RawToFConfig, DepthParams, median))
         ;
 
     // Message
@@ -63,6 +63,7 @@ void bind_tofconfig(pybind11::module& m, void* pCallstack){
         .def("setFreqModUsed", static_cast<ToFConfig&(ToFConfig::*)(dai::ToFConfig::DepthParams::TypeFMod)>(&ToFConfig::setFreqModUsed), DOC(dai, ToFConfig, setFreqModUsed))
         .def("setAvgPhaseShuffle", &ToFConfig::setAvgPhaseShuffle, DOC(dai, ToFConfig, setAvgPhaseShuffle))
         .def("setMinAmplitude", &ToFConfig::setMinAmplitude, DOC(dai, ToFConfig, setMinAmplitude))
+        .def("setMedianFilter", &ToFConfig::setMedianFilter, DOC(dai, ToFConfig, setMedianFilter))
 
         .def("set", &ToFConfig::set, py::arg("config"), DOC(dai, ToFConfig, set))
         .def("get", &ToFConfig::get, DOC(dai, ToFConfig, get))

utilities/cam_test.py

@@ -89,6 +89,8 @@ def socket_type_pair(arg):
                     help="Show also ToF amplitude output alongside depth")
 parser.add_argument('-tofcm', '--tof-cm', action='store_true',
                     help="Show ToF depth output in centimeters, capped to 255")
+parser.add_argument('-tofmedian', '--tof-median', choices=[0,3,5,7], default=5, type=int,
+                    help="ToF median filter kernel size")
 parser.add_argument('-rgbprev', '--rgb-preview', action='store_true',
                     help="Show RGB `preview` stream instead of full size `isp`")
 
@@ -221,6 +223,16 @@ def get(self):
             tofConfig.depthParams.freqModUsed = dai.RawToFConfig.DepthParams.TypeFMod.MIN
             tofConfig.depthParams.avgPhaseShuffle = False
             tofConfig.depthParams.minimumAmplitude = 3.0
+
+            if args.tof_median == 0:
+                tofConfig.depthParams.median = dai.MedianFilter.MEDIAN_OFF
+            elif args.tof_median == 3:
+                tofConfig.depthParams.median = dai.MedianFilter.KERNEL_3x3
+            elif args.tof_median == 5:
+                tofConfig.depthParams.median = dai.MedianFilter.KERNEL_5x5
+            elif args.tof_median == 7:
+                tofConfig.depthParams.median = dai.MedianFilter.KERNEL_7x7
+
             tof[c].initialConfig.set(tofConfig)
             if args.tof_amplitude:
                 amp_name = 'tof_amplitude_' + c