bump to new buildroot and opencv 4.1

CMakeLists.txt

@@ -43,7 +43,7 @@ include_directories("include")
 include_directories("..")
 
 # Setup our library using the source files in src/Components and call it jevoisbase with the current version number:
-jevois_setup_library(src/Components jevoisbase 1.12.0)
+jevois_setup_library(src/Components jevoisbase 1.13.0)
 
 # Setup our modules that are in src/Modules, make them depend on jevoisbase:
 jevois_setup_modules(src/Modules jevoisbase)
@@ -233,7 +233,8 @@ add_definitions(-Wparentheses -w)
 #  ${JVB}/Contrib/cvEyeTracker-1.2.5/remove_corneal_reflection.cpp ${JVB}/Contrib/cvEyeTracker-1.2.5/svd.c)
 
 ########################################################################################################################
-# Neon-accelerated NE10 support:
+# Neon-accelerated Ne10 support. NOTE: as of JeVois 1.13.0, Ne10 is also installed on platform by default as a library,
+# may want to use that in new code:
 include_directories(Contrib/Ne10/inc)
 
 target_sources(jevoisbase PRIVATE ${JVB}/Contrib/Ne10/modules/imgproc/NE10_boxfilter.c)
@@ -407,13 +408,14 @@ ${TFS}/allocation.cc ${TFS}/arena_planner.cc ${TFS}/context.c)
 
 target_link_libraries(jevoisbase ${JEVOIS_OPENCV_LIBS} opencv_aruco opencv_bgsegm opencv_bioinspired opencv_calib3d
   opencv_ccalib opencv_core opencv_datasets opencv_dnn_objdetect opencv_dnn opencv_dpm opencv_face opencv_features2d
-  opencv_flann opencv_fuzzy opencv_hfs opencv_imgcodecs opencv_img_hash opencv_imgproc
+  opencv_flann opencv_fuzzy opencv_gapi opencv_hfs opencv_imgcodecs opencv_img_hash opencv_imgproc
   opencv_line_descriptor opencv_ml opencv_objdetect opencv_optflow opencv_phase_unwrapping opencv_photo opencv_plot
-  opencv_reg opencv_saliency opencv_shape opencv_stereo opencv_stitching opencv_structured_light opencv_superres
-  opencv_surface_matching opencv_text opencv_tracking opencv_videoio opencv_video opencv_videostab opencv_xfeatures2d
-  opencv_ximgproc opencv_xobjdetect opencv_xphoto)
+  opencv_quality opencv_reg opencv_saliency opencv_shape opencv_stereo opencv_stitching opencv_structured_light
+  opencv_superres opencv_surface_matching opencv_text opencv_tracking opencv_videoio opencv_video opencv_videostab
+  opencv_xfeatures2d opencv_ximgproc opencv_xobjdetect opencv_xphoto)
 # removed: opencv_freetype (not available on platform), opencv_highgui (not needed), opencv_rgbd (not needed)
 
+
 ########################################################################################################################
 # Install shared resources (cascade classifiers, neural network weights, etc):
 
@@ -465,7 +467,7 @@ else (JEVOIS_PLATFORM)
   set(JEVOIS_DEPEND "jevois-host (>=${JEVOIS_VERSION_MAJOR}.${JEVOIS_VERSION_MINOR}.${JEVOIS_VERSION_PATCH})")
 endif (JEVOIS_PLATFORM)
 
-set(CPACK_DEBIAN_PACKAGE_DEPENDS "${JEVOIS_DEPEND}, libgles2-mesa, libgles2-mesa-dev, curl")
+set(CPACK_DEBIAN_PACKAGE_DEPENDS "${JEVOIS_DEPEND}, libgles2-mesa, libgles2-mesa-dev, curl, libdmtx-dev, python3-scipy")
 
 # Use helper from JeVois.cmake for all other settings:
 jevois_setup_cpack("jevoisbase")

src/Modules/PyDMTX/PyDMTX.py

@@ -0,0 +1,68 @@
+import libjevois as jevois
+import cv2
+import numpy as np
+from pylibdmtx.pylibdmtx import decode
+
+## Decoding of DataMatrix (DMTX) 2D barcodes
+#
+# This module finds and decodes DataMatrix 2D barcodes.
+#
+# It uses libdmtx as a backend, and the pylibdmtx python wrapper.
+#
+# On host, you will need: sudo apt install libdmtx-dev; pip install pylibdmtx
+#
+# @author Laurent Itti
+# 
+# @videomapping YUYV 320 280 30.0 YUYV 320 240 30.0 JeVois PyDMTX
+# @email itti\@usc.edu
+# @address University of Southern California, HNB-07A, 3641 Watt Way, Los Angeles, CA 90089-2520, USA
+# @copyright Copyright (C) 2017 by Laurent Itti, iLab and the University of Southern California
+# @mainurl http://jevois.org
+# @supporturl http://jevois.org/doc
+# @otherurl http://iLab.usc.edu
+# @license GPL v3
+# @distribution Unrestricted
+# @restrictions None
+# @ingroup modules
+class PyDMTX:
+    # ###################################################################################################
+    ## Constructor
+    def __init__(self):
+        # Instantiate a JeVois Timer to measure our processing framerate:
+        self.timer = jevois.Timer("dmtx", 100, jevois.LOG_INFO)
+
+    # ###################################################################################################
+    ## Process function with USB output
+    def process(self, inframe, outframe):
+        # Get the next camera image (may block until it is captured) as OpenCV BGR:
+        inimg = inframe.getCvBGR()
+
+        # Start measuring image processing time (NOTE: does not account for input conversion time):
+        self.timer.start()
+
+        # Create dark-gray (value 80) image for the bottom panel, 40 pixels tall:
+        msgbox = np.zeros((40, inimg.shape[1], 3), dtype = np.uint8) + 80
+
+        # Find and decode any DataMatrix symbols:
+        dec = decode(inimg)
+
+        # Draw the results in the input image (which we will copy to output):
+        y = 13
+        for d in dec:
+            cv2.rectangle(inimg, (d.rect.left, d.rect.top), (d.rect.left+d.rect.width-1, d.rect.top+d.rect.height-1),
+                          (255,0,0), 2)
+            cv2.putText(msgbox, d.data.decode("utf-8"), (3, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255))
+            y = y + 12
+
+        # Create our output image as a copy of the input plus our message box:
+        outimg = np.vstack((inimg, msgbox))
+
+        # Write a title:
+        cv2.putText(outimg, "JeVois Python DataMatrix", (3, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255))
+
+        # Write frames/s info from our timer into the edge map (NOTE: does not account for output conversion time):
+        fps = self.timer.stop()
+        cv2.putText(outimg, fps, (3, inimg.shape[0] - 6), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255))
+
+        # Convert our OpenCv output image to video output format and send to host over USB:
+        outframe.sendCv(outimg)