Python Image.findBlobs方法代码示例

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
	def encuentraYFiltraBlobs(self,areaMin, areaMax, 
								   toleranciaWH, desviacionD,
								   toleranciaLP, tipoDibujo):
		
		imagenBlobs = Image(self.rutaImagenTratada_Fase2).copy()
		blobs = imagenBlobs.findBlobs()
		self.todosLosCandidatos = blobs
		
		if blobs:	
			
			blobs.image = imagenBlobs
			
			self.areaBlobs = blobs.area()
			blobs = self.filtroPorArea(blobs, areaMin, areaMax)
			self.numBlobsCandidatosPorArea = len(blobs)
			
			# Busca los blobs de forma circular , los blobs que pasan el filtro
			# se guardan en la lista self.articulaciones
			blobs = self.filtroPorForma(blobs, toleranciaWH, desviacionD, toleranciaLP)
			
			if tipoDibujo == 'blobs':
				self.dibujaBlobs(blobs)
			elif tipoDibujo == 'estructura':
				self.dibujaEstructura(imagenBlobs)
		
		# La imagen tratada tiene que ser guardada porque sino no funciona
		# la integracion con Tkinter
		imagenBlobs.save(self.rutaImagenBlobs)
		return Image(self.rutaImagenBlobs)

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
def detectBlobs(image_file):
	
	original = Image(image_file)
	blobs = original.findBlobs()
	
	for blob in blobs:
		blob.drawMinRect(color=Color.RED,width =10)

	#blobs[-1].drawMinRect(color=Color.RED,width =10)
	blobs.image = original
	#original.save("foundBlobs.jpg")
	return 1

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
def main():
    camera = cv2.VideoCapture('video2.avi')
    background_subtractor = cv2.BackgroundSubtractorMOG()

    # Store previous tracking image
    previous_track_image = Image()

    while camera.isOpened():
        is_success, image = camera.read()
        if is_success:
            mask = background_subtractor.apply(image, None, 0.1)
            # Vehicles will be detected from this image
            track_image = Image(ndimage.median_filter(mask, 3), cv2image=True)

            blobs = track_image.findBlobs(minsize=250, maxsize=800)

            if not blobs:
                # print('No Blobs Found.')
                continue
            else:
                # print("Width: {0}; Height: {1}".format(blobs[0].width(), blobs[0].height()))
                # Only keep near square blobs
                blobs = filter(lambda b: 0.25 < b.width() / b.height() < 4, blobs)

            # print("Found {0} Blobs. {1}".format(len(blobs)))

            if len(vehicle_track_set_list) == 0:
                # Find first batch of blobs
                for blob in blobs:
                    blob.drawRect(color=Color.BLUE, width=3, alpha=225)
                    # bounding_box = tuple(blob.boundingBox())
                    # print("Area: {0}".format(blob.area()))

                    track_set = track_image.track(method='mftrack', img=track_image, bb=blob.boundingBox())
                    if track_set:
                        vehicle_track_set_list.append(VehicleTrackSet(track_set))
                        track_set.drawBB(color=(255, 0, 0))
                        track_set.drawPath()
                        track_image.show()

            else:
                for blob in blobs:
                    blob.drawRect(color=Color.BLUE, width=3, alpha=225)
                    # print("Blob Coordinate: ({0}, {1}).".format(blob.x, blob.y))
                    update_track_set(track_image, previous_track_image, blob.boundingBox())

            # Save current image
            previous_track_image = track_image

            # time.sleep(0.1)
        else:
            camera.release()
            break

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
    def run(self):
        cam_mode=self.cam_mode
        wsh = self.wsh
        js = self.js
        wsh2 = self.wsh2
        d = "n"
        c2 = self.c2
        c = self.c
        sqx = self.sqx
        sqy = self.sqy
        x = 0
        y = 0
        stat="live cam"
        if cam_mode == 3:
            img1 = c2.getImage()
        if cam_mode==1:
            img1 = c.getImage()
            time.sleep(1)
	    with picamera.PiCamera() as camera:
                camera.resolution = (544, 288)
                camera.capture('imagesmall.jpg')
            img2 = Image('imagesmall.jpg')
            time.sleep(.5)
            img1 = img1.sideBySide(img2)
            img1 = img1.scale(544,288)
            time.sleep(.5)
        if cam_mode==2:
            with picamera.PiCamera() as camera:
                camera.resolution = (544, 288)
                camera.capture('imagesmall.jpg')
            img1 = Image('imagesmall.jpg')
        self.img1 = img1

        blobs = img1.findBlobs()
        if blobs :
            ##blobs.draw()
            img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
            img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
            blobx1 = blobs[-1].x
            bloby1 = blobs[-1].y
            print blobx1
            print bloby1
            img1.drawText("ogp: live cam", 10, 10, fontsize=50)
            img1.drawText(str(blobx1), blobx1, 250, color=(255,255,255), fontsize=20)
            img1.drawText(str(bloby1), 10, bloby1, color=(255,255,255), fontsize=20)
            img1.save(js.framebuffer)
            sqx2=sqx+20
            sqy2=sqy+20
            time.sleep(.5) 
            wsh.write_message(wsh2, "live")
        
        else:
            wsh.write_message(wsh2, "live")

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
	def update(self, dt):
		self.img = GameInstance().cam.getImage().flipHorizontal()
		GameInstance().lower = np.array((float(self.val[0]), float(self.val[1]), float(self.val[2])))
		GameInstance().upper = np.array((float(self.val[3]), float(self.val[4]), float(self.val[5])))
		hsv = self.img.toHSV()
		mask = cv2.inRange(hsv.getNumpy(), GameInstance().lower, GameInstance().upper)
		img2 = Image(source=mask)
		img2 = img2.erode(1)
		img2 = img2.dilate(2)
		if self.cvActiveBloops.active:
			blops = img2.findBlobs()
			if blops:
				self.cvBlob.texture = getKivyTexture(blops[-1].getMaskedImage())
		self.cvFilter.texture = getKivyTexture(img2)
		self.cvImage.texture = getKivyTexture(self.img)

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
def get_puzzle_from_image(raw_image):
    # Returns None if no puzzle found
    # Returns puzzle, x offset, y offset
    # if puzzle found. Offsets are top
    # left corner of puzzle

    # Remove color
    gray_image = raw_image.grayscale()

    # Smooth to remove speckle
    smooth_image = gray_image.gaussianBlur((5,5),0)

    # Convert to Numpy Array For OpenCV use
    cv_image = smooth_image.getGrayNumpyCv2()

    # Adaptive threshold does much better than linear
    raw_thresh_image = cv2.adaptiveThreshold(cv_image,255,1,1,11,2)

    # Convert back to a SimpleCV image
    thresh_image = Image(raw_thresh_image)

    # For some reason it gets rotated and flipped, reverse
    thresh_image = thresh_image.rotate90().flipVertical()

    # Find "blobs" which are interesting items in the image
    blobs = thresh_image.findBlobs()

    # Assume the largest rectangular blob is our puzzle
    puzzle_blob = None
    puzzle_area = 0

    for blob in blobs:
        if blob.isRectangle() and blob.area() > puzzle_area:
            puzzle_blob = blob
            puzzle_area = blob.area()

    # Only continue if there is a puzzle
    if puzzle_blob is None: return None, 0, 0

    # Crop image to just the puzzle
    puzzle_image = puzzle_blob.crop()
    offset_x, offset_y = puzzle_blob.topLeftCorner()

    return puzzle_image, offset_x, offset_y

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
    def histo(self):
        cam_mode = self.cam_mode
        js = self.js
        ms = self.ms
        w = self.w
        cent = 0
        rgb1 = 0
        c2 = self.c2
        wsh = self.wsh 
        wsh2 = self.wsh2
        s.write('s')
        
        if cam_mode == 3:
            img1 = c2.getImage()
        if cam_mode==1:
            with picamera.PiCamera() as camera:
                camera.resolution = (544, 288)
                camera.capture('imagesmall.jpg')
            img1 = Image('imagesmall.jpg')
        if cam_mode==2:
            with picamera.PiCamera() as camera:
                camera.resolution = (544, 288)
                camera.capture('imagesmall.jpg')
            img1 = Image('imagesmall.jpg')
        self.img1 = img1
        blobs = img1.findBlobs()  
        
        if blobs:
            print "blob"
            x = self.x
            y = self.y
            p = self.p
            p = p + 1
            img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
            img1.drawCircle((blobs[0].centroid()),10,color=(255,100,100))
            print blobs[-1].meanColor()
            rgb1 = blobs[-1].meanColor()
            cent = blobs[-1].centroid()

            pth1 = "/var/www/images/image"
            pth3 = ".png"
            pth = pth1 + str(p) + pth3
            print pth
            img1.save(pth)
            
            thumbnail = img1.crop(150,25,250,250)
            thumbnail = thumbnail.scale(20,20)
            thumb1 = "/var/www/images/thumbs/thumb"
            thumb3 = ".png"
            thumbpath = thumb1 + str(p) + thumb3
            print thumbpath
            thumbnail.save(thumbpath)
            
            self.p = p
            
            mySet.add((p,x,y,w,cent,rgb1))
            self.mySet = mySet
            
            wshx = str(self.x)
            wshy = str(self.y)
            centroidx = int(cent[0])
            centroidy=int(cent[1])
            rcolor=rgb1[0]
            gcolor=rgb1[1]
            bcolor=rgb1[2]
            rcolor=int(rcolor)
            gcolor=int(gcolor)
            bcolor=int(bcolor)
            wsh.write_message(wsh2, "rgb_" + str(rcolor)+"_"+str(gcolor)+"_"+str(bcolor))
            wsh.write_message(wsh2, "x_" + str(centroidx)+"_"+str(centroidy))
            img1.save(js.framebuffer)
            wsh.write_message(wsh2, "d_" + wshx + "_" + wshy + "_" + str(p) )

        else:
            wshx = str(self.x)
            wshy = str(self.y)
            wsh.write_message(wsh2, wshx + " " + wshy + "dark")
 
            print "dark"

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
    def run(self):

        wsh = self.wsh
      ##  c = self.c
        js = self.js
        wsh2 = self.wsh2
        acu = int(1)
        acd = int(1)
        acl = int(1)
        acr = int(1)
        irpic = pinoir2(js)

        img1 = Image('imagesmall.jpg')   
        blobs = img1.findBlobs()
        img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
        img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
        acx1 = blobs[-1].x
        acy1 = blobs[-1].y


        img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
        img1.drawText(str(acx1), 10, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy1), 10, 75, color=(255,255,255), fontsize=20)
        img1.save(js.framebuffer)
        
        d = 'r'
        ms = 50
        s.write('4')
        mov = acx(s, d, ms, acu, acd, acl, acr)
        mov.run()
            
        time.sleep(1)

        img1 = c.getImage()   
        blobs = img1.findBlobs()
        img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
        img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
        acx2 = blobs[-1].x
        acy2 = blobs[-1].y

        
        img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
        img1.drawText(str(acx1), 10, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy1), 10, 75, color=(255,255,255), fontsize=20)        
        img1.drawText(str(acx2), 40, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy2), 40, 75, color=(255,255,255), fontsize=20)
        img1.save(js.framebuffer)
        
        d = 'd'
        ms = 50
        s.write('9')
        mov = acx(s, d, ms, acu, acd, acl, acr)
        mov.run()
        time.sleep(1)


        img1 = c.getImage()   
        blobs = img1.findBlobs()
        img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
        img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
        acx3 = blobs[-1].x
        acy3 = blobs[-1].y

        img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
        img1.drawText(str(acx1), 10, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy1), 10, 75, color=(255,255,255), fontsize=20)        
        img1.drawText(str(acx2), 40, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy2), 40, 75, color=(255,255,255), fontsize=20)
        img1.drawText(str(acx3), 70, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy3), 70, 75, color=(255,255,255), fontsize=20)
        img1.save(js.framebuffer)
        d = 'l'
        ms = 50
        s.write('2')
        mov = acx(s, d, ms, acu, acd, acl, acr)
        mov.run()
        time.sleep(1)


        img1 = c.getImage()   
        blobs = img1.findBlobs()
        img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
        img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
        acx4 = blobs[-1].x
        acy4 = blobs[-1].y

        img1.drawText("ogp: autocalibrating", 10, 10, fontsize=50)
        img1.drawText(str(acx1), 10, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy1), 10, 75, color=(255,255,255), fontsize=20)        
        img1.drawText(str(acx2), 40, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy2), 40, 75, color=(255,255,255), fontsize=20)
        img1.drawText(str(acx3), 70, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy3), 70, 75, color=(255,255,255), fontsize=20)
        img1.drawText(str(acx4), 100, 50, color=(255,255,255), fontsize=20)
        img1.drawText(str(acy4), 100, 75, color=(255,255,255), fontsize=20)
        img1.save(js.framebuffer)
        d = 'u'
        ms = 50
        s.write('6')
        mov = acx(s, d, ms, acu, acd, acl, acr)
#.........这里部分代码省略.........

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
            statusWin.addstr( 1, 1,  str(object.meanColor()))

            num_corners = len(corners)
            statusWin.addstr(2,1, "Corners Found:" + str(num_corners))

            corners.draw()

            img.addDrawingLayer(object.dl())


            # circle tracking

            #dist = img.colorDistance(Color.BLACK).dilate(2)
            #segmented = dist.stretch(200,255)

            blobs = img.findBlobs()
            if blobs:
                    circles = blobs.filter([b.isCircle(0.2) for b in blobs])
                    if circles:
                        img.drawCircle((circles[-1].x, circles[-1].y), circles[-1].radius(),Color.BLUE,3)




            img.save("/dev/shm/p4.png")

            #img.save(js.framebuffer)


        elif keyp == 'v':
             pz.stop()

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
    smooth_image = gray_image.gaussianBlur((5,5),0)

    # Convert to Numpy Array For OpenCV use
    cv_image = smooth_image.getGrayNumpyCv2()

    # Adaptive threshold does much better than linear
    raw_thresh_image = cv2.adaptiveThreshold(cv_image,255,1,1,11,2)

    # Convert back to a SimpleCV image
    thresh_image = Image(raw_thresh_image)

    # For some reason it gets rotated and flipped, reverse
    thresh_image = thresh_image.rotate90().flipVertical()

    # Find "blobs" which are interesting items in the image
    blobs = thresh_image.findBlobs()

    # Assume the largest rectangular blob is our puzzle
    puzzle_blob = None
    puzzle_area = 0

    for blob in blobs:
        if blob.isRectangle() and blob.area() > puzzle_area:
            puzzle_blob = blob
            puzzle_area = blob.area()

    # Only continue if there is a puzzle
    #if puzzle_blob is None: return

    # Crop image to just the puzzle
    puzzle_image = puzzle_blob.crop()

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
    def run(self):
        cam_mode=self.cam_mode
        s.write('s')
        wsh = self.wsh
        js = self.js
        wsh2 = self.wsh2
        ms = 50
        d = "n"
        acu = int(1)
        acd = int(1)
        acl = int(1)
        acr = int(1)
        c2=self.c2
        sqx=self.sqx
        sqy=self.sqy
        x=0
        y=0
        stat="centering"
        if cam_mode == 3:
            img1 = c2.getImage()
        if cam_mode==1:
            with picamera.PiCamera() as camera:
                camera.resolution = (544, 288)
                camera.capture('imagesmall.jpg')
            img1 = Image('imagesmall.jpg')
        if cam_mode==2:
            with picamera.PiCamera() as camera:
                camera.resolution = (544, 288)
                camera.capture('imagesmall.jpg')
            img1 = Image('imagesmall.jpg')
        self.img1 = img1

        blobs = img1.findBlobs()
        if blobs :
            ##blobs.draw()
            img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,255))
            img1.drawCircle((blobs[-1].centroid()),10,color=(255,100,100))
            blobx1 = blobs[-1].x
            bloby1 = blobs[-1].y
            print blobx1
            print bloby1
            img1.drawText("ogp: centering", 10, 10, fontsize=50)
            img1.drawText(str(blobx1), 10, 200, color=(255,255,255), fontsize=50)
            ##img1.drawText(str(bloby1), 50, 200, color=(255,255,255), fontsize=50)
            img1.drawText(str(bloby1), 10, 250, color=(255,255,255), fontsize=50)
            img1.save(js.framebuffer)
            sqx2=sqx+20
            sqy2=sqy+20

            if blobx1 > sqx2:
                d = '_r'
                s.write('4')
                mov = acx(s, d, ms, acu, acd, acl, acr)
                mov.run()
                wsh.write_message(wsh2, "g_"+ str(d))

            if blobx1 < sqx:
                d = 'l'
                s.write('2')
                mov = acx(s, d, ms, acu, acd, acl, acr)
                mov.run()
                wsh.write_message(wsh2, "g_"+ str(d))

            if bloby1 > sqy2:
                d = 'd'
                s.write('9')
                mov = acx(s, d, ms, acu, acd, acl, acr)
                mov.run()
                wsh.write_message(wsh2, "g_"+ str(d))

            if bloby1 < sqy:
                d = 'u'
                s.write('6')
                mov = acx(s, d, ms, acu, acd, acl, acr)
                mov.run()
                wsh.write_message(wsh2, "g_"+ str(d))
         
            wsh.write_message(wsh2, "c")
        
        else:
            wsh.write_message(wsh2, "c_" + "null" )

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
from SimpleCV import Image
import time
#using opencv captured image, but purpose is make by video
call(“raspistill -n -t 0 -w %s -h %s -o image.bmp” % 640 480, shell=True)

img = Image(“image.bmp”)

img.show()
time.sleep(5)

#--------
cam = Camera()
img = cam.getImage()

#-----
img = img.edges()
img.show()
time.sleep(5)


img = img.binarize()
img.show()
time.sleep(5) 


img = img.findBlobs()
for blob in blobs:
    blob.draw()  
img.show()
time.sleep(5) 
#연속적인 이미지 촬영으로 영상을 만들면 속도가 너무 느리다 한방으로 가자

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import findBlobs [as 别名]
    def histo(self): ## this def is the "light meter" part---
        cam_mode = self.cam_mode ## the pic gets cataloged if true ---
        js = self.js
        w = self.w
        cent = 0
        rgb1 = 0
        c2 = self.c2
        wsh = self.wsh
        wsh2 = self.wsh2
        i=0
        brightpixels=0
        darkpixels=0
        blobs = 0

        if cam_mode == 3: ## sort out the confusing cam modes
            img1 = c2.getImage()
            time.sleep(.25)

        if cam_mode==1:
            with picamera.PiCamera() as camera:
                camera.resolution = (544, 288)
                camera.capture('imagesmall.jpg')
            img1 = Image('imagesmall.jpg')

        if cam_mode==2:
            with picamera.PiCamera() as camera:
                camera.resolution = (544, 288)
                camera.capture('imagesmall.jpg')
            img1 = Image('imagesmall.jpg')

        blobs = img1.findBlobs()
        time.sleep(0.5)

        if blobs:
##find the blob centroid and cut it out 20x20
            crop1 = blobs[-1].x      
            crop2 = blobs[-1].y
            crop3 = crop1 - 10
            crop4 = crop2 - 10
            thumbnail = img1.crop(crop3,crop4,20,20)
            img2 = thumbnail
            hist = img2.histogram(20)
            ## split the thumb into 20 levels of darkness
            brightpixels = hist[10]
            ## 10 is where the darkest of the light pixels accumulate
            print brightpixels

##while i < 20:
##old code for if you want to split the histogram in two
##if (i < 10):
##darkpixels = darkpixels + hist[i]
##self.darkpixels = darkpixels
##print hist[i]
##else:
##brightpixels = brightpixels + hist[i]
##self.brightpixels = brightpixels
##print hist[i]
##i = i + 1

            if (brightpixels<400):   ## heres where it decides to catalog the pic or not...
                wsh.write_message(wsh2, "histo_" + str(darkpixels) + "_" + str(brightpixels))
                print "blob"
                x = self.x
                y = self.y
                p = self.p
                p = p + 1
                thumb1 = "/var/www/html/images/thumbs/thumb"
                thumb3 = ".png"
                thumbpath = thumb1 + str(p) + thumb3
                print thumbpath
                thumbnail.save(thumbpath)
                img1.drawText("blob = True", 10, 35, color=(255,255,255),fontsize=30)
                img1.drawText("search_mode", 10, 5, color=(0,0,255),fontsize=40)
                img1.drawText("blob centroid", blobs[-1].x,blobs[-1].y, color=(255,255,255),fontsize=20)
                img1.drawCircle((blobs[-1].x,blobs[-1].y),30,color=(255,255,0))
                img1.drawCircle((blobs[0].centroid()),10,color=(255,255,255))
                print blobs[-1].meanColor()
                rgb1 = blobs[-1].meanColor()
                cent = blobs[-1].centroid()

                pth1 = "/var/www/html/images/image"
                pth3 = ".png"
                pth = pth1 + str(p) + pth3
                print pth
                img1.save(pth)
                time.sleep(0.5)

                self.p = p

                mySet.add((p,x,y,w,cent,rgb1))
                self.mySet = mySet

                wshx = str(self.x)
                wshy = str(self.y)

                centroidx = int(cent[0])
                centroidy=int(cent[1])
                rcolor=rgb1[0]
                gcolor=rgb1[1]
                bcolor=rgb1[2]
#.........这里部分代码省略.........