luxonis · Erol444 · Apr 24, 2023 · Apr 13, 2023 · Apr 13, 2023 · Apr 24, 2023
diff --git a/docs/source/samples/SpatialDetection/spatial_calculator_multi_roi.rst b/docs/source/samples/SpatialDetection/spatial_calculator_multi_roi.rst
@@ -11,7 +11,7 @@ scanning camera for mobile robots.
 Demo
 ####
 
-.. image:: https://user-images.githubusercontent.com/18037362/190861621-b57fd1e3-5a3d-4d79-b1a7-d17a0b78c63e.gif
+.. image:: https://user-images.githubusercontent.com/18037362/231822498-6e3699a0-039e-424b-acb2-b246575e91ee.png
 
 Setup
 #####

diff --git a/docs/source/tutorials/code_samples.rst b/docs/source/tutorials/code_samples.rst
@@ -126,6 +126,7 @@ are presented with code.
 
 .. rubric:: SpatialDetection
 
+- :ref:`Spatial Calculator Multi-ROI` - Selects multiple ROIs and calculates spatial coordinates for each of them
 - :ref:`Spatial location calculator` - Demonstrates how to use the spatial location calculator
 - :ref:`RGB & MobilenetSSD with spatial data` - Displays RGB frames with MobileNet detections and spatial coordinates on them
 - :ref:`Mono & MobilenetSSD with spatial data` - Displays mono frames with MobileNet detections and spatial coordinates on them

diff --git a/examples/SpatialDetection/spatial_calculator_multi_roi.py b/examples/SpatialDetection/spatial_calculator_multi_roi.py
@@ -3,6 +3,7 @@
 import cv2
 import depthai as dai
 import math
+import numpy as np
 
 # Create pipeline
 pipeline = dai.Pipeline()
@@ -29,7 +30,7 @@
 
 stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
 stereo.setLeftRightCheck(True)
-stereo.setExtendedDisparity(True)
+stereo.setSubpixel(True)
 spatialLocationCalculator.inputConfig.setWaitForMessage(False)
 
 # Create 10 ROIs
@@ -65,8 +66,10 @@
 
         depthFrame = inDepth.getFrame() # depthFrame values are in millimeters
 
-        depthFrameColor = cv2.normalize(depthFrame, None, 255, 0, cv2.NORM_INF, cv2.CV_8UC1)
-        depthFrameColor = cv2.equalizeHist(depthFrameColor)
+        depth_downscaled = depthFrame[::4]
+        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)
 
         spatialData = spatialCalcQueue.get().getSpatialLocations()

diff --git a/examples/SpatialDetection/spatial_location_calculator.py b/examples/SpatialDetection/spatial_location_calculator.py
@@ -2,7 +2,7 @@
 
 import cv2
 import depthai as dai
-
+import numpy as np
 stepSize = 0.05
 
 newConfig = False
@@ -30,12 +30,9 @@
 monoRight.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P)
 monoRight.setBoardSocket(dai.CameraBoardSocket.RIGHT)
 
-lrcheck = False
-subpixel = False
-
 stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
-stereo.setLeftRightCheck(lrcheck)
-stereo.setSubpixel(subpixel)
+stereo.setLeftRightCheck(True)
+stereo.setSubpixel(True)
 
 # Config
 topLeft = dai.Point2f(0.4, 0.4)
@@ -77,8 +74,10 @@
 
         depthFrame = inDepth.getFrame() # depthFrame values are in millimeters
 
-        depthFrameColor = cv2.normalize(depthFrame, None, 255, 0, cv2.NORM_INF, cv2.CV_8UC1)
-        depthFrameColor = cv2.equalizeHist(depthFrameColor)
+        depth_downscaled = depthFrame[::4]
+        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)
 
         spatialData = spatialCalcQueue.get().getSpatialLocations()
@@ -94,10 +93,10 @@
             depthMax = depthData.depthMax
 
             fontType = cv2.FONT_HERSHEY_TRIPLEX
-            cv2.rectangle(depthFrameColor, (xmin, ymin), (xmax, ymax), color, cv2.FONT_HERSHEY_SCRIPT_SIMPLEX)
-            cv2.putText(depthFrameColor, f"X: {int(depthData.spatialCoordinates.x)} mm", (xmin + 10, ymin + 20), fontType, 0.5, 255)
-            cv2.putText(depthFrameColor, f"Y: {int(depthData.spatialCoordinates.y)} mm", (xmin + 10, ymin + 35), fontType, 0.5, 255)
-            cv2.putText(depthFrameColor, f"Z: {int(depthData.spatialCoordinates.z)} mm", (xmin + 10, ymin + 50), fontType, 0.5, 255)
+            cv2.rectangle(depthFrameColor, (xmin, ymin), (xmax, ymax), color, 1)
+            cv2.putText(depthFrameColor, f"X: {int(depthData.spatialCoordinates.x)} mm", (xmin + 10, ymin + 20), fontType, 0.5, color)
+            cv2.putText(depthFrameColor, f"Y: {int(depthData.spatialCoordinates.y)} mm", (xmin + 10, ymin + 35), fontType, 0.5, color)
+            cv2.putText(depthFrameColor, f"Z: {int(depthData.spatialCoordinates.z)} mm", (xmin + 10, ymin + 50), fontType, 0.5, color)
         # Show the frame
         cv2.imshow("depth", depthFrameColor)
 

diff --git a/examples/SpatialDetection/spatial_mobilenet.py b/examples/SpatialDetection/spatial_mobilenet.py
@@ -60,6 +60,7 @@
 stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
 # Align depth map to the perspective of RGB camera, on which inference is done
 stereo.setDepthAlign(dai.CameraBoardSocket.RGB)
+stereo.setSubpixel(True)
 stereo.setOutputSize(monoLeft.getResolutionWidth(), monoLeft.getResolutionHeight())
 
 spatialDetectionNetwork.setBlobPath(nnBlobPath)
@@ -113,8 +114,10 @@
 
         depthFrame = depth.getFrame() # depthFrame values are in millimeters
 
-        depthFrameColor = cv2.normalize(depthFrame, None, 255, 0, cv2.NORM_INF, cv2.CV_8UC1)
-        depthFrameColor = cv2.equalizeHist(depthFrameColor)
+        depth_downscaled = depthFrame[::4]
+        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)
 
         detections = inDet.detections
@@ -132,7 +135,7 @@
             ymin = int(topLeft.y)
             xmax = int(bottomRight.x)
             ymax = int(bottomRight.y)
-            cv2.rectangle(depthFrameColor, (xmin, ymin), (xmax, ymax), color, cv2.FONT_HERSHEY_SCRIPT_SIMPLEX)
+            cv2.rectangle(depthFrameColor, (xmin, ymin), (xmax, ymax), color, 1)
 
             # Denormalize bounding box
             x1 = int(detection.xmin * width)

diff --git a/examples/SpatialDetection/spatial_mobilenet_mono.py b/examples/SpatialDetection/spatial_mobilenet_mono.py
@@ -59,6 +59,7 @@
 
 # StereoDepth
 stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
+stereo.setSubpixel(True)
 
 # Define a neural network that will make predictions based on the source frames
 spatialDetectionNetwork.setConfidenceThreshold(0.5)
@@ -116,8 +117,10 @@
 
         depthFrame = inDepth.getFrame() # depthFrame values are in millimeters
 
-        depthFrameColor = cv2.normalize(depthFrame, None, 255, 0, cv2.NORM_INF, cv2.CV_8UC1)
-        depthFrameColor = cv2.equalizeHist(depthFrameColor)
+        depth_downscaled = depthFrame[::4]
+        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)
 
         detections = inDet.detections

diff --git a/examples/SpatialDetection/spatial_tiny_yolo.py b/examples/SpatialDetection/spatial_tiny_yolo.py
@@ -84,6 +84,7 @@
 # Align depth map to the perspective of RGB camera, on which inference is done
 stereo.setDepthAlign(dai.CameraBoardSocket.RGB)
 stereo.setOutputSize(monoLeft.getResolutionWidth(), monoLeft.getResolutionHeight())
+stereo.setSubpixel(True)
 
 spatialDetectionNetwork.setBlobPath(nnBlobPath)
 spatialDetectionNetwork.setConfidenceThreshold(0.5)
@@ -146,8 +147,10 @@
         frame = inPreview.getCvFrame()
         depthFrame = depth.getFrame() # depthFrame values are in millimeters
 
-        depthFrameColor = cv2.normalize(depthFrame, None, 255, 0, cv2.NORM_INF, cv2.CV_8UC1)
-        depthFrameColor = cv2.equalizeHist(depthFrameColor)
+        depth_downscaled = depthFrame[::4]
+        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)
 
         counter+=1
@@ -172,7 +175,7 @@
             ymin = int(topLeft.y)
             xmax = int(bottomRight.x)
             ymax = int(bottomRight.y)
-            cv2.rectangle(depthFrameColor, (xmin, ymin), (xmax, ymax), color, cv2.FONT_HERSHEY_SCRIPT_SIMPLEX)
+            cv2.rectangle(depthFrameColor, (xmin, ymin), (xmax, ymax), color, 1)
 
             # Denormalize bounding box
             x1 = int(detection.xmin * width)

diff --git a/examples/StereoDepth/depth_crop_control.py b/examples/StereoDepth/depth_crop_control.py
@@ -40,6 +40,7 @@
 manip.initialConfig.setCropRect(topLeft.x, topLeft.y, bottomRight.x, bottomRight.y)
 manip.setMaxOutputFrameSize(monoRight.getResolutionHeight()*monoRight.getResolutionWidth()*3)
 stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
+stereo.setSubpixel(True)
 
 # Linking
 configIn.out.link(manip.inputConfig)
@@ -62,8 +63,10 @@
         depthFrame = inDepth.getFrame() # depthFrame values are in millimeters
 
         # Frame is transformed, the color map will be applied to highlight the depth info
-        depthFrameColor = cv2.normalize(depthFrame, None, 255, 0, cv2.NORM_INF, cv2.CV_8UC1)
-        depthFrameColor = cv2.equalizeHist(depthFrameColor)
+        depth_downscaled = depthFrame[::4]
+        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)
 
         # Frame is ready to be shown

diff --git a/examples/mixed/rotated_spatial_detections.py b/examples/mixed/rotated_spatial_detections.py
@@ -4,7 +4,7 @@
 import sys
 import cv2
 import depthai as dai
-
+import numpy as np
 '''
 Spatial object detections demo for 180° rotated OAK camera.
 '''
@@ -58,6 +58,7 @@
 stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
 # Align depth map to the perspective of RGB camera, on which inference is done
 stereo.setDepthAlign(dai.CameraBoardSocket.RGB)
+stereo.setSubpixel(True)
 stereo.setOutputSize(monoLeft.getResolutionWidth(), monoLeft.getResolutionHeight())
 
 rotate_stereo_manip = pipeline.createImageManip()
@@ -104,8 +105,10 @@
         frame = inPreview.getCvFrame()
         depthFrame = depth.getFrame() # depthFrame values are in millimeters
 
-        depthFrameColor = cv2.normalize(depthFrame, None, 255, 0, cv2.NORM_INF, cv2.CV_8UC1)
-        depthFrameColor = cv2.equalizeHist(depthFrameColor)
+        depth_downscaled = depthFrame[::4]
+        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)
 
         detections = inDet.detections