class DM:
def __init__(self, max_count, timeout):
self.max_count = max_count
self.timeout = timeout
self.loadReader()
self.symbols = [] #a symbol is a list of the content and four (x,y) points as a sub list
return
def loadReader(self):
self.read = DataMatrix(max_count = self.max_count, timeout = self.timeout, shape = DataMatrix.DmtxSymbol10x10)
return
def scan(self, img):
self.read.decode(size(img, 1), size(img, 0), buffer(img.tostring()))
self.symbols = []
for idx in range(1, self.read.count()+1):
self.symbols.append(self.read.stats(idx))
def setTimeout(self, v):
self.timeout = v
self.loadReader()
return
def setMaxCount(self, v):
self.max_count = v
self.loadReader()
return
def writeDM(self):
# Write a Data Matrix barcode
dm_write = DataMatrix()
dm_write.encode("Hello, world!")
dm_write.save("hello.png", "png")
return
def decode(imgcv2):
code = ""
try:
st = datetime.datetime.now()
img = Image.fromarray(imgcv2)
if img.mode != 'RGB':
img = img.convert('RGB')
dm_read = DataMatrix()
code = dm_read.decode(
img.size[0],
img.size[1],
buffer(
img.tostring()),
timeout=80,
maxcount=1,
corrections=3)
end = datetime.datetime.now()
if dm_read.count() == 1:
# print code, end - st
time = end - st
print dm_read.stats(1), "t:", str(time)[6:]
points = dm_read.stats(1)[1]
# print "points:", points
# os.system("beep -f1296 -l10")
except Exception:
print "error decode"
pass
return code, points
from pydmtx import DataMatrix
from PIL import Image
# Write a Data Matrix barcode
dm_write = DataMatrix()
dm_write.encode("Hello, world!")
dm_write.save("hello.png", "png")
# Read a Data Matrix barcode
dm_read = DataMatrix()
img = Image.open("hello.png")
print dm_read.decode(img.size[0], img.size[1], buffer(img.tostring()))
print dm_read.count()
print dm_read.message(1)
print dm_read.stats(1)
class DmtxFinder:
def __init__(self):
self.cache = {}
self.dm = DataMatrix()
def Cached(self, name, rows, cols, type):
key = (name, rows, cols)
if not key in self.cache:
self.cache[key] = cv.CreateMat(rows, cols, type)
return self.cache[key]
def find0(self, img):
started = time.time()
self.dm.decode(
img.width,
img.height,
buffer(img.tostring()),
max_count=4,
#min_edge = 6,
#max_edge = 19 # Units of 2 pixels
)
print "brute", time.time() - started
found = {}
for i in range(self.dm.count()):
stats = dm_read.stats(i + 1)
print stats
found[stats[0]] = stats[1]
return found
def find(self, img):
started = time.time()
gray = self.Cached('gray', img.height, img.width, cv.CV_8UC1)
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
sobel = self.Cached('sobel', img.height, img.width, cv.CV_16SC1)
sobely = self.Cached('sobely', img.height, img.width, cv.CV_16SC1)
cv.Sobel(gray, sobel, 1, 0)
cv.Sobel(gray, sobely, 0, 1)
cv.Add(sobel, sobely, sobel)
sobel8 = self.Cached('sobel8', sobel.height, sobel.width, cv.CV_8UC1)
absnorm8(sobel, sobel8)
cv.Threshold(sobel8, sobel8, 128.0, 255.0, cv.CV_THRESH_BINARY)
sobel_integral = self.Cached('sobel_integral', img.height + 1,
img.width + 1, cv.CV_32SC1)
cv.Integral(sobel8, sobel_integral)
d = 16
_x1y1 = cv.GetSubRect(
sobel_integral,
(0, 0, sobel_integral.cols - d, sobel_integral.rows - d))
_x1y2 = cv.GetSubRect(
sobel_integral,
(0, d, sobel_integral.cols - d, sobel_integral.rows - d))
_x2y1 = cv.GetSubRect(
sobel_integral,
(d, 0, sobel_integral.cols - d, sobel_integral.rows - d))
_x2y2 = cv.GetSubRect(
sobel_integral,
(d, d, sobel_integral.cols - d, sobel_integral.rows - d))
summation = cv.CloneMat(_x2y2)
cv.Sub(summation, _x1y2, summation)
cv.Sub(summation, _x2y1, summation)
cv.Add(summation, _x1y1, summation)
sum8 = self.Cached('sum8', summation.height, summation.width,
cv.CV_8UC1)
absnorm8(summation, sum8)
cv.Threshold(sum8, sum8, 32.0, 255.0, cv.CV_THRESH_BINARY)
cv.ShowImage("sum8", sum8)
seq = cv.FindContours(sum8, cv.CreateMemStorage(), cv.CV_RETR_EXTERNAL)
subimg = cv.GetSubRect(img, (d / 2, d / 2, sum8.cols, sum8.rows))
t_cull = time.time() - started
seqs = []
while seq:
seqs.append(seq)
seq = seq.h_next()
started = time.time()
found = {}
print 'seqs', len(seqs)
for seq in seqs:
area = cv.ContourArea(seq)
if area > 1000:
rect = cv.BoundingRect(seq)
edge = int((14 / 14.) * math.sqrt(area) / 2 + 0.5)
candidate = cv.GetSubRect(subimg, rect)
sym = self.dm.decode(
candidate.width,
candidate.height,
buffer(candidate.tostring()),
max_count=1,
#min_edge = 6,
#max_edge = int(edge) # Units of 2 pixels
)
if sym:
onscreen = [(d / 2 + rect[0] + x, d / 2 + rect[1] + y)
for (x, y) in self.dm.stats(1)[1]]
found[sym] = onscreen
else:
print "FAILED"
t_brute = time.time() - started
print "cull took", t_cull, "brute", t_brute
return found
class DmtxFinder:
def __init__(self):
self.cache = {}
self.dm = DataMatrix()
def Cached(self, name, rows, cols, type):
key = (name, rows, cols)
if not key in self.cache:
self.cache[key] = cv.CreateMat(rows, cols, type)
return self.cache[key]
def find0(self, img):
started = time.time()
self.dm.decode(img.width,
img.height,
buffer(img.tostring()),
max_count = 4,
#min_edge = 6,
#max_edge = 19 # Units of 2 pixels
)
print "brute", time.time() - started
found = {}
for i in range(self.dm.count()):
stats = dm_read.stats(i + 1)
print stats
found[stats[0]] = stats[1]
return found
def find(self, img):
started = time.time()
gray = self.Cached('gray', img.height, img.width, cv.CV_8UC1)
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
sobel = self.Cached('sobel', img.height, img.width, cv.CV_16SC1)
sobely = self.Cached('sobely', img.height, img.width, cv.CV_16SC1)
cv.Sobel(gray, sobel, 1, 0)
cv.Sobel(gray, sobely, 0, 1)
cv.Add(sobel, sobely, sobel)
sobel8 = self.Cached('sobel8', sobel.height, sobel.width, cv.CV_8UC1)
absnorm8(sobel, sobel8)
cv.Threshold(sobel8, sobel8, 128.0, 255.0, cv.CV_THRESH_BINARY)
sobel_integral = self.Cached('sobel_integral', img.height + 1, img.width + 1, cv.CV_32SC1)
cv.Integral(sobel8, sobel_integral)
d = 16
_x1y1 = cv.GetSubRect(sobel_integral, (0, 0, sobel_integral.cols - d, sobel_integral.rows - d))
_x1y2 = cv.GetSubRect(sobel_integral, (0, d, sobel_integral.cols - d, sobel_integral.rows - d))
_x2y1 = cv.GetSubRect(sobel_integral, (d, 0, sobel_integral.cols - d, sobel_integral.rows - d))
_x2y2 = cv.GetSubRect(sobel_integral, (d, d, sobel_integral.cols - d, sobel_integral.rows - d))
summation = cv.CloneMat(_x2y2)
cv.Sub(summation, _x1y2, summation)
cv.Sub(summation, _x2y1, summation)
cv.Add(summation, _x1y1, summation)
sum8 = self.Cached('sum8', summation.height, summation.width, cv.CV_8UC1)
absnorm8(summation, sum8)
cv.Threshold(sum8, sum8, 32.0, 255.0, cv.CV_THRESH_BINARY)
cv.ShowImage("sum8", sum8)
seq = cv.FindContours(sum8, cv.CreateMemStorage(), cv.CV_RETR_EXTERNAL)
subimg = cv.GetSubRect(img, (d / 2, d / 2, sum8.cols, sum8.rows))
t_cull = time.time() - started
seqs = []
while seq:
seqs.append(seq)
seq = seq.h_next()
started = time.time()
found = {}
print 'seqs', len(seqs)
for seq in seqs:
area = cv.ContourArea(seq)
if area > 1000:
rect = cv.BoundingRect(seq)
edge = int((14 / 14.) * math.sqrt(area) / 2 + 0.5)
candidate = cv.GetSubRect(subimg, rect)
sym = self.dm.decode(candidate.width,
candidate.height,
buffer(candidate.tostring()),
max_count = 1,
#min_edge = 6,
#max_edge = int(edge) # Units of 2 pixels
)
if sym:
onscreen = [(d / 2 + rect[0] + x, d / 2 + rect[1] + y) for (x, y) in self.dm.stats(1)[1]]
found[sym] = onscreen
else:
print "FAILED"
t_brute = time.time() - started
print "cull took", t_cull, "brute", t_brute
return found
import os
from pydmtx import DataMatrix
from PIL import Image
#------------------------------------------------------------
# write a data matrix barcode
#------------------------------------------------------------
path = os.path.abspath('.')
path = os.path.join(path, 'hello.png')
matrix = DataMatrix()
matrix.encode("Hello, world!")
matrix.save(path, "png")
#------------------------------------------------------------
# read a data matrix Barcode
#------------------------------------------------------------
matrix = DataMatrix()
image = Image.open(path)
print matrix.decode(image.size[0], image.size[1], buffer(image.tostring()))
print matrix.count()
print matrix.message(1)
print matrix.stats(1)
if options.test:
# re-read image
image = Image("original.png")
else:
if calibrated:
image_orig = cam.getImage()
image = cam.undistort(image_orig)
else:
image = cam.getImage()
overlay = DrawingLayer((image.width, image.height))
dm_read.decode(image.width, image.height, buffer(image.toString()))
for count in range(dm_read.count()):
stats = dm_read.stats(count + 1)
# Highlight barcode
arrow = []
arrow.append(stats[1][0])
arrow.append(stats[1][1])
arrow.append(stats[1][3])
arrow.append(stats[1][0])
arrow.append(stats[1][2])
overlay.lines(arrow, Color.RED, width=2)
# Attempt to improve the co-ords of each corner
best = []
zoomed = 64
for x in range(3):
if options.dmtx:
