JeVoisBase  1.16
JeVois Smart Embedded Machine Vision Toolkit Base Modules
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PyDMTX.py
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1 import pyjevois
2 if pyjevois.pro: import libjevoispro as jevois
3 else: import libjevois as jevois
4 import cv2
5 import numpy as np
6 from pylibdmtx.pylibdmtx import decode
7 
8 ## Decoding of DataMatrix (DMTX) 2D barcodes
9 #
10 # This module finds and decodes DataMatrix 2D barcodes.
11 #
12 # It uses libdmtx as a backend, and the pylibdmtx python wrapper.
13 #
14 # On host, you will need: sudo apt install libdmtx-dev; pip install pylibdmtx
15 #
16 # @author Laurent Itti
17 #
18 # @videomapping YUYV 320 280 30.0 YUYV 320 240 30.0 JeVois PyDMTX
19 # @email itti\@usc.edu
20 # @address University of Southern California, HNB-07A, 3641 Watt Way, Los Angeles, CA 90089-2520, USA
21 # @copyright Copyright (C) 2017 by Laurent Itti, iLab and the University of Southern California
22 # @mainurl http://jevois.org
23 # @supporturl http://jevois.org/doc
24 # @otherurl http://iLab.usc.edu
25 # @license GPL v3
26 # @distribution Unrestricted
27 # @restrictions None
28 # @ingroup modules
29 class PyDMTX:
30  # ###################################################################################################
31  ## Constructor
32  def __init__(self):
33  # Instantiate a JeVois Timer to measure our processing framerate:
34  self.timer = jevois.Timer("dmtx", 100, jevois.LOG_INFO)
35 
36  # ###################################################################################################
37  ## Process function with USB output
38  def process(self, inframe, outframe):
39  # Get the next camera image (may block until it is captured) as OpenCV BGR:
40  inimg = inframe.getCvBGR()
41 
42  # Start measuring image processing time (NOTE: does not account for input conversion time):
43  self.timer.start()
44 
45  # Create dark-gray (value 80) image for the bottom panel, 40 pixels tall:
46  msgbox = np.zeros((40, inimg.shape[1], 3), dtype = np.uint8) + 80
47 
48  # Find and decode any DataMatrix symbols:
49  dec = decode(inimg)
50 
51  # Draw the results in the input image (which we will copy to output):
52  y = 13
53  for d in dec:
54  cv2.rectangle(inimg, (d.rect.left, d.rect.top), (d.rect.left+d.rect.width-1, d.rect.top+d.rect.height-1),
55  (255,0,0), 2)
56  cv2.putText(msgbox, d.data.decode("utf-8"), (3, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255))
57  y = y + 12
58 
59  # Create our output image as a copy of the input plus our message box:
60  outimg = np.vstack((inimg, msgbox))
61 
62  # Write a title:
63  cv2.putText(outimg, "JeVois Python DataMatrix", (3, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255))
64 
65  # Write frames/s info from our timer into the edge map (NOTE: does not account for output conversion time):
66  fps = self.timer.stop()
67  cv2.putText(outimg, fps, (3, inimg.shape[0] - 6), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255))
68 
69  # Convert our OpenCv output image to video output format and send to host over USB:
70  outframe.sendCv(outimg)
PyDMTX.PyDMTX.timer
timer
Definition: PyDMTX.py:34
PyDMTX.PyDMTX.__init__
def __init__(self)
Constructor.
Definition: PyDMTX.py:32
PyDMTX.PyDMTX
Decoding of DataMatrix (DMTX) 2D barcodes.
Definition: PyDMTX.py:29
PyDMTX.PyDMTX.process
def process(self, inframe, outframe)
Process function with USB output.
Definition: PyDMTX.py:38
jevois::Timer