def __call__(self, context, *args):
LOG.info(self.mess)
tsi = args[0]
self.image = tsi.pixels
meanIntensity = np.mean(self.image)
if meanIntensity < self.minIntensity:
# FIXME: this should be handled with an error.
LOG.warn('Image is too dark, skiping colorcard detection!')
return([self.image, [None, None, None]])
if not self.useWhiteBackground:
self.imagePyramid = cd.createImagePyramid(self.image)
ccdImg = cv2.imread(self.ccf)[:, :, ::-1]
if ccdImg is None:
raise ValueError("Failed to read %s" % self.ccf)
self.colorcardPyramid = cd.createImagePyramid(ccdImg)
# create image pyramid for multiscale matching
SearchRange = [self.colorcardPyramid[0].shape[1],
self.colorcardPyramid[0].shape[0]]
score, loc, angle = cd.matchTemplatePyramid(
self.imagePyramid,
self.colorcardPyramid,
0,
EstimatedLocation=self.colorcardPosition,
SearchRange=SearchRange
)
if score > 0.3:
# extract color information
self.foundCard = self.image[
loc[1] - ccdImg.shape[0] // 2:loc[1] + ccdImg.shape[0] // 2,
loc[0] - ccdImg.shape[1] // 2:loc[0] + ccdImg.shape[1] // 2]
self.ccdColors, _ = cd.getColorcardColors(self.foundCard,
GridSize=[6, 4])
self.colorcardParams = cd.estimateColorParameters(
self.colorcardTrueColors,
self.colorcardColors
)
# Save colourcard image to instance
self.colorcardImage = ccdImg
# for displaying
self.loc = loc
else:
# FIXME: this should be handled with an error.
LOG.warn('Cannot find color card')
self.colorcardParams = [None, None, None]
else:
self.colorcardParams = cd.estimateColorParametersFromWhiteBackground(
self.image, self.backgroundWindow, self.maxIntensity)
return([tsi, self.colorcardParams])
def __call__(self, context, *args):
LOG.info(self.mess)
tsi = args[0]
self.image = tsi.pixels
temp = np.zeros_like(self.image)
temp[:, :, :] = self.image[:, :, :]
temp[:, :, 1] = 0 # suppress green channel
self.imagePyramid = cd.createImagePyramid(temp)
self.trayPyramids = []
for i in range(self.trayNumber):
# fixed tray image so that perspective postions of the trays are
# fixed
trayFile = os.path.join(context.ints.path,
self.settingPath,
self.trayFiles % i)
trayImage = cv2.imread(trayFile)[:, :, ::-1]
if trayImage is None:
LOG.error("Fail to read", trayFile)
trayImage[:, :, 1] = 0 # suppress green channel
trayPyramid = cd.createImagePyramid(trayImage)
self.trayPyramids.append(trayPyramid)
self.trayLocs = []
for i, trayPyramid in enumerate(self.trayPyramids):
SearchRange = [trayPyramid[0].shape[1] // 6,
trayPyramid[0].shape[0] // 6]
score, loc, angle = cd.matchTemplatePyramid(
self.imagePyramid,
trayPyramid,
RotationAngle=0,
EstimatedLocation=self.trayPositions[i],
SearchRange=SearchRange)
if score < 0.3:
# FIXME: For now we don't handle missing trays.
raise PCExBrakeInPipeline(
self.actName,
"Low tray matching score. Likely tray %d is missing." % i)
self.trayLocs.append(loc)
# add tray location information
context.outputwithimage["trayLocs"] = self.trayLocs
tsi.pixels = self.image
return([tsi, self.imagePyramid, self.trayLocs])
def __exec__(self, context, *args):
tsi = args[0]
self.image = tsi.pixels
temp = np.zeros_like(self.image)
temp[:, :, :] = self.image[:, :, :]
temp[:, :, 1] = 0 # suppress green channel
self.imagePyramid = cd.createImagePyramid(temp)
self.trayPyramids = []
for i in range(self.trayNumber):
# fixed tray image so that perspective postions of the trays are
# fixed
trayFile = os.path.join(context.ints.path,
self.settingPath,
self.trayFiles % i)
trayImage = read_image(trayFile)
if trayImage is None:
LOG.error("Fail to read", trayFile)
trayImage[:, :, 1] = 0 # suppress green channel
trayImage = trayImage[:, :, 0:3] # supress Alpha channel
trayPyramid = cd.createImagePyramid(trayImage)
self.trayPyramids.append(trayPyramid)
self.trayLocs = []
for i, trayPyramid in enumerate(self.trayPyramids):
SearchRange = [trayPyramid[0].shape[1] // 6,
trayPyramid[0].shape[0] // 6]
score, loc, angle = cd.matchTemplatePyramid(
self.imagePyramid,
trayPyramid,
RotationAngle=0,
EstimatedLocation=self.trayPositions[i],
SearchRange=SearchRange)
if score < 0.3:
raise PCExCannotFindTray(i, tsi.path)
self.trayLocs.append(loc)
tsi.pixels = self.image
return([tsi, self.imagePyramid, self.trayLocs])
def __exec__(self, context, *args):
tsi = args[0]
self.image = tsi.pixels
meanIntensity = np.mean(self.image)
if meanIntensity < self.minIntensity:
raise PCExImageTooDark(tsi.path)
if not self.useWhiteBackground:
self.imagePyramid = cd.createImagePyramid(self.image)
ccdImg = read_image(self.ccf)[:, :, 0:3]
if ccdImg is None:
raise PCExBadImage(self.ccf)
self.ccdPyramid = cd.createImagePyramid(ccdImg)
# create image pyramid for multiscale matching
SearchRange = [self.ccdPyramid[0].shape[1] * 1.5,
self.ccdPyramid[0].shape[0] * 1.5]
score, loc, angle = cd.matchTemplatePyramid(
self.imagePyramid, self.ccdPyramid,
0, EstimatedLocation=self.colorcardPosition,
SearchRange=SearchRange)
if score > 0.3:
# extract color information
self.foundCard = self.image[
loc[1] - ccdImg.shape[0] // 2:loc[1] + ccdImg.shape[0] // 2,
loc[0] - ccdImg.shape[1] // 2:loc[0] + ccdImg.shape[1] // 2]
self.ccdColors, _ = cd.getColorcardColors(self.foundCard,
GridSize=[6, 4])
self.ccdParams = cd.estimateColorParameters(
self.colorcardTrueColors,
self.ccdColors)
# Save colourcard image to instance
self.colorcardImage = ccdImg
# for displaying
self.loc = loc
else:
raise PCExCannotFindColorCard(tsi.path)
else:
self.ccdParams = cd.estimateColorParametersFromWhiteBackground(
self.image, self.backgroundWindow, self.maxIntensity)
return([tsi, self.ccdParams])
def __call__(self, context, *args):
LOG.info(self.mess)
tsi, self.imagePyramid, self.trayLocs = args
self.image = tsi.pixels
# read pot template image and scale to the pot size
potFile = os.path.join(
context.ints.path,
self.settingPath,
self.potFile)
potImage = cv2.imread(potFile)[:, :, ::-1]
potTemplateFile = os.path.join(
context.ints.path,
self.settingPath,
self.potTemplateFile)
potTemplateImage = cv2.imread(potTemplateFile)[:, :, ::-1]
potTemplateImage[:, :, 1] = 0 # suppress green channel
potTemplateImage = cv2.resize(
potTemplateImage.astype(np.uint8),
(potImage.shape[1],
potImage.shape[0]))
self.potPyramid = cd.createImagePyramid(potTemplateImage)
XSteps = self.traySize[0] // self.potSize[0]
YSteps = self.traySize[1] // self.potSize[1]
StepX = self.traySize[0] // XSteps
StepY = self.traySize[1] // YSteps
self.potLocs2 = []
self.potLocs2_ = []
potGridSize = [4, 5]
for trayLoc in self.trayLocs:
if trayLoc is None:
self.potLocs2.append(None)
continue
StartX = trayLoc[0] - self.traySize[0] // 2 + StepX // 2
StartY = trayLoc[1] + self.traySize[1] // 2 - StepY // 2
SearchRange = [self.potPyramid[0].shape[1] // 4,
self.potPyramid[0].shape[0] // 4]
# SearchRange = [32, 32]
locX = np.zeros(potGridSize)
locY = np.zeros(potGridSize)
for k in range(potGridSize[0]):
for l in range(potGridSize[1]):
estimateLoc = [StartX + StepX * k, StartY - StepY * l]
score, loc, angle = cd.matchTemplatePyramid(
self.imagePyramid,
self.potPyramid,
RotationAngle=0,
EstimatedLocation=estimateLoc,
NoLevels=3,
SearchRange=SearchRange)
locX[k, l], locY[k, l] = loc
# correct for detection error
potLocs = []
potLocs_ = []
diffXX = locX[1:, :] - locX[:-1, :]
diffXY = locX[:, 1:] - locX[:, :-1]
diffYX = locY[1:, :] - locY[:-1, :]
diffYY = locY[:, 1:] - locY[:, :-1]
diffXXMedian = np.median(diffXX)
diffXYMedian = np.median(diffXY)
diffYXMedian = np.median(diffYX)
diffYYMedian = np.median(diffYY)
for k in range(potGridSize[0]):
for l in range(potGridSize[1]):
locX[k, l] = trayLoc[0] + diffXXMedian * (k - (potGridSize[0] - 1.0) / 2.0) + \
diffXYMedian * (l - (potGridSize[1] - 1.0) / 2.0)
locY[k, l] = trayLoc[1] + diffYXMedian * (k - (potGridSize[0] - 1.0) / 2.0) + \
diffYYMedian * (l - (potGridSize[1] - 1.0) / 2.0)
# this fixes perpective shift
# TODO: need a more elegant solution
locY[k, l] = locY[k, l] + 10
potLocs.append([locX[k, l], locY[k, l]])
potLocs_.append(estimateLoc)
self.potLocs2.append(potLocs)
self.potLocs2_.append(potLocs_)
# Create a new ImagePotMatrix with newly discovered locations
ipmPrev = None
if context.hasSubSecName("ipmPrev"):
ipmPrev = context.ipmPrev
flattened = list(chain.from_iterable(self.potLocs2))
growM = round(min(spatial.distance.pdist(flattened)) / 2)
tsi.ipm = tm_pot.ImagePotMatrix(
tsi,
pots=[],
growM=growM,
ipmPrev=ipmPrev)
potID = 1
for tray in self.potLocs2:
trayID = 1
for center in tray:
r = tm_pot.ImagePotRectangle(
center,
tsi.pixels.shape,
growM=growM)
p = tm_pot.ImagePotHandler(potID, r, tsi.ipm)
p.setMetaId("trayID", trayID)
tsi.ipm.addPot(p)
potID += 1
trayID += 1
context.outputwithimage["potLocs"] = self.potLocs2
return([tsi])
def __exec__(self, context, *args):
tsi, self.imagePyramid, self.trayLocs = args
self.image = tsi.pixels
# read pot template image and scale to the pot size
potFile = os.path.join(
context.ints.path,
self.settingPath,
self.potFile)
potImage = read_image(potFile)
potTemplateFile = os.path.join(
context.ints.path,
self.settingPath,
self.potTemplateFile)
potTemplateImage = read_image(potTemplateFile)
potTemplateImage[:, :, 1] = 0 # suppress green channel
potTemplateImage = cv2.resize(
potTemplateImage.astype(np.uint8),
(potImage.shape[1],
potImage.shape[0]))
self.potPyramid = cd.createImagePyramid(potTemplateImage)
XSteps = int(round(self.traySize[0] / float(self.potSize[0])))
YSteps = int(round(self.traySize[1] / float(self.potSize[1])))
StepX = self.traySize[0] // XSteps
StepY = self.traySize[1] // YSteps
self.potLocs2 = []
self.potLocs2_ = []
potGridSize = [4, 5]
for trayLoc in self.trayLocs:
if trayLoc is None:
self.potLocs2.append(None)
continue
StartX = trayLoc[0] - self.traySize[0] // 2 + StepX // 2
StartY = trayLoc[1] + self.traySize[1] // 2 - StepY // 2
SearchRange = [self.potPyramid[0].shape[1] // 4,
self.potPyramid[0].shape[0] // 4]
# SearchRange = [32, 32]
locX = np.zeros(potGridSize)
locY = np.zeros(potGridSize)
for k in range(potGridSize[0]):
for l in range(potGridSize[1]):
estimateLoc = [StartX + StepX * k, StartY - StepY * l]
score, loc, angle = cd.matchTemplatePyramid(
self.imagePyramid,
self.potPyramid,
RotationAngle=0,
EstimatedLocation=estimateLoc,
NoLevels=3,
SearchRange=SearchRange)
locX[k, l], locY[k, l] = loc
# correct for detection error
potLocs = []
potLocs_ = []
diffXX = locX[1:, :] - locX[:-1, :]
diffXY = locX[:, 1:] - locX[:, :-1]
diffYX = locY[1:, :] - locY[:-1, :]
diffYY = locY[:, 1:] - locY[:, :-1]
diffXXMedian = np.median(diffXX)
diffXYMedian = np.median(diffXY)
diffYXMedian = np.median(diffYX)
diffYYMedian = np.median(diffYY)
for k in range(potGridSize[0]):
for l in range(potGridSize[1]):
locX[k, l] = trayLoc[0] + diffXXMedian * (k - (potGridSize[0] - 1.0) / 2.0) + \
diffXYMedian * (l - (potGridSize[1] - 1.0) / 2.0)
locY[k, l] = trayLoc[1] + diffYXMedian * (k - (potGridSize[0] - 1.0) / 2.0) + \
diffYYMedian * (l - (potGridSize[1] - 1.0) / 2.0)
# this fixes perpective shift
# TODO: need a more elegant solution
locY[k, l] = locY[k, l] + 10
potLocs.append([locX[k, l], locY[k, l]])
potLocs_.append(estimateLoc)
self.potLocs2.append(potLocs)
self.potLocs2_.append(potLocs_)
# Create a new ImagePotMatrix with newly discovered locations
ipmPrev = None
if context.hasSubSecName("ipmPrev"):
ipmPrev = context.ipmPrev
# Calculate growM with potSize from potdetect component.
growM = 0
if isinstance(self.potSize, list) and len(self.potSize) == 2:
growM = round(max(self.potSize) / 2)
else:
# if no user vals, we try to calculate it.
flattened = list(chain.from_iterable(self.potLocs2))
sortDist = np.sort(spatial.distance.pdist(flattened))
sortDist = sortDist[0:len(flattened)]
growM = round(np.median(sortDist) / 2)
tsi.ipm = tm_pot.ImagePotMatrix(
tsi, pots=[], growM=growM, ipmPrev=ipmPrev)
potID = self.startingPotId
for tray in self.potLocs2:
trayID = 1
for c in tray: # c => center
m = dict([[x, context.metas.getVal(x)[potID]]
for x in context.metas.listSubSecNames()
if potID in context.metas.getVal(x).keys()])
try:
r = tm_pot.ImagePotRectangle(c, tsi.pixels.shape,
growM=growM)
except:
raise PCExPotRectangleDimsOutOfImage(potID, c,
tsi.pixels.shape)
p = tm_pot.ImagePotHandler(potID, r, tsi.ipm, metaids=m)
p.setMetaId("trayID", trayID)
tsi.ipm.addPot(p)
potID += 1
trayID += 1
return([tsi])
