def process(img, blocks):
cv2.imshow("img", img)
cv2.imshow("blocks", blocks)
C, M, Y, K = util.cvtColorBGR2CMYK_(blocks) #convert to CMYK
#imgNoBgnd = getUniformBackGround(img, K) #get uniform background
#cv2.imshow("imgnobgnd", imgNoBgnd)
invWhiteLines = getWhiteLines(C, M, Y, K) #get only white lines
#cv2.imshow("White Lines", invWhiteLines)
#remove white lines from image
invWhite3 = cv2.merge([invWhiteLines, invWhiteLines, invWhiteLines])
#imgBlocks = cv2.bitwise_and(imgNoBgnd, invWhite3)
imgBlocks = cv2.bitwise_and(img, invWhite3)
#imgBlocks = blocks
#find the blocks in imgBlocks
imgray = cv2.cvtColor(imgBlocks,cv.CV_RGB2GRAY);
cv2.imshow("grayscale for blocks", imgray)
_,imbw = cv2.threshold(imgray, 0, 255, cv2.THRESH_BINARY)
cv2.imshow("bw for blocks", imbw)
#cv2.imshow("img Blocks", imgBlocks)
ctrs = cv2.findContours(imbw, cv2.RETR_LIST , cv2.CHAIN_APPROX_SIMPLE);
#imgCopy = img
rectList = getRects(img, ctrs) #img
#print "B:\tG:\tR:"
for i in range(len(rectList)):
#print rectList[i]
#(x,y),(w,h),t = rectList[i][1]
#print x,y,w,h,t
#x,y,w,h = rectList[i][0]
rec = np.asarray(cv.GetSubRect(cv.fromarray(imgBlocks),rectList[i][0]))
cv2.imshow(str(i), rec)
def process(img):
C, M, Y, K = util.cvtColorBGR2CMYK_(img) #convert to CMYK
imgNoBgnd = getUniformBackGround(img, K) #get uniform background
invWhiteLines = getWhiteLines(C, M, Y, K) #get only white lines
#remove white lines from image
invWhite3 = cv2.merge([invWhiteLines, invWhiteLines, invWhiteLines])
imgBlocks = cv2.bitwise_and(imgNoBgnd, invWhite3)
cv2.imshow("White Lines", invWhiteLines)
#find the blocks in imgBlocks
imgray = cv2.cvtColor(imgBlocks,cv.CV_RGB2GRAY);
_,imbw = cv2.threshold(imgray, 20, 255, cv2.THRESH_BINARY_INV)
ctrs = cv2.findContours(imbw, cv2.RETR_LIST , cv2.CHAIN_APPROX_SIMPLE);
rectList = drawRects(img, ctrs) #img
for i in range(len(rectList)):
#print rectList[i][1]
#(x,y),(w,h),t = rectList[i][1]
#print x,y,w,h,t
#x,y,w,h = rectList[i][0]
rec = np.asarray(cv.GetSubRect(cv.fromarray(imgBlocks),rectList[i][0]))
cv2.imshow(str(i), rec)
#print rec.shape
rh,rw,rc = rec.shape
print rec[rh/2][rw/2][0],rec[rh/2][rw/2][1],rec[rh/2][rw/2][2]
Cfinal, Mfinal, Yfinal, Kfinal = util.cvtColorBGR2CMYK_(rec)
print Cfinal[rh/2][rw/2],Mfinal[rh/2][rw/2],Yfinal[rh/2][rw/2],Kfinal[rh/2][rw/2]
hsv = cv2.cvtColor(rec, cv.CV_BGR2HSV)
print hsv[rh/2][rw/2][0],hsv[rh/2][rw/2][1],hsv[rh/2][rw/2][2]
#cv2.imshow('hsv'+str(i),hsv)
print "***********************"
#brown, orange, maroon
destr = cv2.inRange(rec, np.array((50, 85, 150)), np.array((255, 255, 255)));
cv2.imshow("dR"+str(i), destr)
#orange
destg = cv2.inRange(rec, np.array((10, 150, 200)), np.array((255, 255, 255)));
cv2.imshow("dG"+str(i), destg)
#brown,
destb = cv2.inRange(rec, np.array((100, 100, 150)), np.array((255, 255, 255)));
cv2.imshow("dB"+str(i), destb)
#blue
destl = cv2.inRange(rec, np.array((140, 10, 10)), np.array((255, 255, 255)));
cv2.imshow("dl"+str(i), destl)
#green, brown, blue
deste = cv2.inRange(rec, np.array((0, 10, 10)), np.array((255, 255, 255)));
cv2.imshow("de"+str(i), deste)
#cv2.imshow("CF"+str(i),Cfinal)
#cv2.imshow("MF"+str(i),Mfinal)
#cv2.imshow("YF"+str(i),Yfinal)
#cv2.imshow("KF"+str(i),Kfinal)
#Process the CMYK of imgBlocks
#The processing is necessary to find the color of the blocks.
Cfinal, Mfinal, Yfinal, Kfinal = util.cvtColorBGR2CMYK_(imgBlocks) #convert
cfinal = np.uint8(Cfinal*255)
_,cfinalbw = cv2.threshold(cfinal, 20, 255, cv2.THRESH_BINARY_INV)
cv2.imshow("asdsd",cfinalbw)
key = cv2.waitKey()
def process(self, imageIn, timeNow):
self.image = imageIn
if self.gui: self.imageOut = self.image.copy()
self.blobs = []
imageColors, imageWhites = hsv(self.image)
if self.gui:
cv2.imshow("imageColors", imageColors)
cv2.imshow("imageWhites", imageWhites)
C, M, Y, K = util.cvtColorBGR2CMYK_(imageWhites) #convert to CMYK
#imgNoBgnd = getUniformBackGround(imageColors, K) #get uniform background
#cv2.imshow("imgnobgnd", imgNoBgnd)
invWhiteLines = getWhiteLines(C, M, Y, K) #get only white lines
#cv2.imshow("White Lines", invWhiteLines)
#remove white lines from imageColors
invWhite3 = cv2.merge([invWhiteLines, invWhiteLines, invWhiteLines])
#imgBlocks = cv2.bitwise_and(imgNoBgnd, invWhite3)
imgBlocks = cv2.bitwise_and(imageColors, invWhite3)
#imgBlocks = imageWhites
#find the imageWhites in imgBlocks
imgray = cv2.cvtColor(imgBlocks,cv.CV_RGB2GRAY);
if self.gui:
cv2.imshow("grayscale for imageWhites", imgray)
_,imbw = cv2.threshold(imgray, 0, 255, cv2.THRESH_BINARY)
if self.gui:
cv2.imshow("bw for imageWhites", imbw)
#cv2.imshow("imgBlocks", imgBlocks)
# Contour processing: Old way
'''
ctrs = cv2.findContours(imbw, cv2.RETR_LIST , cv2.CHAIN_APPROX_SIMPLE);
#imgCopy = imageColors
rectList = getRects(ctrs, imageOut)
self.logd("processBlobs", "{0} rects".format(len(rectList)))
'''
# Contour processing: New way
# * Find contours
contours, _ = cv2.findContours(imbw, cv2.RETR_LIST , cv2.CHAIN_APPROX_SIMPLE)
# * Walk through list of contours
for contour in contours:
contour = contour.astype(np.int32) # convert contours to 32-bit int for each individual contour
# ** Compute blob properties to be used for filtering
area = cv2.contourArea(contour)
bbox = cv2.boundingRect(contour)
x, y, w, h = bbox
# ** Filter out ones that are too small or too big
if area < BlobTracker.minBlobArea or area > BlobTracker.maxBlobArea: continue
# ** Process only vertical rectangles (ie, w<h) with w and h > some threshold
if w >= h or w <= self.minBlobWidth or h <= self.minBlobHeight: continue
# ** Compute additional blob properties to be stored
rect = cv2.minAreaRect(contour)
length = "unknown"
if h > 173:
length = "large"
elif h > 140:
length = "medium"
elif h > 100:
length = "small"
# ** Identify color (name)
imageBlob = imgBlocks[y:y+h, x:x+w]
#imageBlob = np.asarray(cv.GetSubRect(cv.fromarray(imgBlocks),rectList[i][0]))
color_bgr = cv2.mean(imageBlob)
color_obj = findMatchColorBGR(colors, color_bgr)
#self.logd("process", "color_obj: {0}".format(color_obj))
color = color_obj.name if color_obj is not None else "none"
# ** Create blob object
blob = SimpleBlob(area=area, bbox=bbox, rect=rect, length=length, color_bgr=color_bgr, color=color)
# ** Apply additional filter(s) on computed blob properties # NOTE density is not being calculated in SimpleBlob
#if blob.density < BlobTracker.minBlobDensity: continue
# ** Add to blobs list; TODO resolve with existing blob objects and update properties if a match is found?
self.blobs.append(blob)
# Blob drawing: Old way
'''
if self.gui:
#print "B:\tG:\tR:"
for i in range(len(rectList)):
#print rectList[i]
#(x,y),(w,h),t = rectList[i][1]
#print x,y,w,h,t
#x,y,w,h = rectList[i][0]
cv2.imshow(str(i), imageBlob)
#showHist(imageBlob, i)
#print imageBlob.shape
#rh,rw,rc = imageBlob.shape
#print imageBlob[rh/2][rw/2][0],imageBlob[rh/2][rw/2][1],imageBlob[rh/2][rw/2][2]
#Cfinal, Mfinal, Yfinal, Kfinal = util.cvtColorBGR2CMYK_(imageBlob)
#print Cfinal[rh/2][rw/2],Mfinal[rh/2][rw/2],Yfinal[rh/2][rw/2],Kfinal[rh/2][rw/2]
#hsv = cv2.cvtColor(imageBlob, cv.CV_BGR2HSV)
#print hsv[rh/2][rw/2][0],hsv[rh/2][rw/2][1],hsv[rh/2][rw/2][2]
#cv2.imshow('hsv'+str(i),hsv)
#print "***********************"
'''
self.blobs.sort(key=lambda blob: blob.bbox) # sort blob list by bbox (left-to-right, top-to-bottom, ...)
# * Report and draw blobs
self.logd("process", "{0} blobs".format(len(self.blobs)))
for blob in self.blobs:
self.logd("process", str(blob)) #blob.detail()
if self.gui: blob.draw(self.imageOut)
if self.gui:
cv2.rectangle(self.imageOut, (318,0), (322,640), (255,255,255), -1) # draw center line
return True, self.imageOut
