def main():
"""Finds and interprets feature points"""
# Initialize Camera
print "Starting Webcam..."
try:
cam = Camera()
except:
print "Unable to initialize camera"
sys.exit(1)
display = Display(resolution = (RES_WIDTH, RES_HEIGHT))
while not display.isDone():
# capture the current frame
try:
capture = cam.getImage()
img = capture.smooth()
except cv.error:
print "Camera unsupported by OpenCV"
sys.exit(1)
# Build face and interpret expression
face_image = FaceImage(img)
if face_image.face:
#s face_image.interpret()
pass
capture.save(display)
time.sleep(0.01)
if display.mouseLeft:
display.done = True
def main():
picture = 'shot.png'
at = get_access_token()
cam = Camera()
display = Display((800, 600))
while display.isNotDone():
img = cam.getImage()
img.save(picture)
img.save(display)
content = FaceRecognization(at, picture)
print(content)
print(content['height'])
def live(self):
"""
**SUMMARY**
This shows a live view of the camera.
**EXAMPLE**
To use it's as simple as:
>>> cam = Camera()
>>> cam.live()
Left click will show mouse coordinates and color
Right click will kill the live image
"""
start_time = time.time()
from SimpleCV.Display import Display
i = self.getImage()
d = Display(i.size())
i.save(d)
col = Color.RED
while d.isNotDone():
i = self.getImage()
elapsed_time = time.time() - start_time
if d.mouseLeft:
txt = "coord: (" + str(d.mouseX) + "," + str(d.mouseY) + ")"
i.dl().text(txt, (10, i.height / 2), color=col)
txt = "color: " + str(i.getPixel(d.mouseX, d.mouseY))
i.dl().text(txt, (10, (i.height / 2) + 10), color=col)
print "coord: (" + str(d.mouseX) + "," + str(
d.mouseY) + "), color: " + str(
i.getPixel(d.mouseX, d.mouseY))
if elapsed_time > 0 and elapsed_time < 5:
i.dl().text("In live mode", (10, 10), color=col)
i.dl().text("Left click will show mouse coordinates and color",
(10, 20),
color=col)
i.dl().text("Right click will kill the live image", (10, 30),
color=col)
i.save(d)
if d.mouseRight:
print "Closing Window"
d.done = True
pg.quit()
def live(self):
"""
**SUMMARY**
This shows a live view of the camera.
**EXAMPLE**
To use it's as simple as:
>>> cam = Camera()
>>> cam.live()
Left click will show mouse coordinates and color
Right click will kill the live image
"""
start_time = time.time()
from SimpleCV.Display import Display
i = self.getImage()
d = Display(i.size())
i.save(d)
col = Color.RED
while d.isNotDone():
i = self.getImage()
elapsed_time = time.time() - start_time
if d.mouseLeft:
txt = "coord: (" + str(d.mouseX) + "," + str(d.mouseY) + ")"
i.dl().text(txt, (10,i.height / 2), color=col)
txt = "color: " + str(i.getPixel(d.mouseX,d.mouseY))
i.dl().text(txt, (10,(i.height / 2) + 10), color=col)
print "coord: (" + str(d.mouseX) + "," + str(d.mouseY) + "), color: " + str(i.getPixel(d.mouseX,d.mouseY))
if elapsed_time > 0 and elapsed_time < 5:
i.dl().text("In live mode", (10,10), color=col)
i.dl().text("Left click will show mouse coordinates and color", (10,20), color=col)
i.dl().text("Right click will kill the live image", (10,30), color=col)
i.save(d)
if d.mouseRight:
print "Closing Window"
d.done = True
pg.quit()
def main():
while (IfWIFI()):
print("No WIFI")
picture = 'shot.jpg'
at = get_access_token()
cam = Camera()
display = Display((800, 600))
a = 1
b = 0
while display.isNotDone():
count = ser.inWaiting()
if count != 0:
recv = ser.read(count)
print(type(recv))
if recv[0] == '*' and recv[-1] == '#':
print("detected")
img = cam.getImage()
img.save(picture)
img.save(display)
name = MarketRecognization(at, picture)
print(name)
if name == "Bread":
b = 1
if name == "Cookies":
b = 2
if name == "HotStrips":
b = 3
if name == "Sepals":
b = 4
if name == "EggRolls":
b = 5
if name == "Beans":
b = 6
ser.write("*,%s,%s,#" % (a, b))
ser.flushInput()
time.sleep(0.1)
def main():
# Try to connect to the camera.
cam = Camera()
if not cam:
print 'Error opening camera. Exiting...'
sys.exit(1)
# Create PyGame display.
disp = Display()
# Main processing loop.
while not disp.isDone():
# Get an image from the camera.
img = cam.getImage()
faces = img.findHaarFeatures("face.xml")
i = 0
if not faces is None:
for f in faces:
f.draw(Color.GREEN)
# Show the camera image.
img.save(disp)
from SimpleCV import *
from numpy import *
from SimpleCV.Display import Display, pg
from SimpleCV import EdgeHistogramFeatureExtractor
from SimpleCV import MorphologyFeatureExtractor
def thresholdOp(in_image):
return in_image.hueDistance(60).binarize(thresh=70).invert().dilate(2)
cam = Camera(1)
#classifier.load(saveFile)
blobber = BlobMaker()
disp = Display(resolution=(1440,900))
#these params are to save the image
count = 0
path = ''
file = './data/bolts/bolts'
ext = '.png'
img = cam.getImage()
minsize = 350# img.width*img.height/200
maxsize = img.width*img.height/8
avgColorThresh = 85
count = 0
while not disp.isDone():
img = cam.getImage()
blobs = []
w = img.width
h = img.height
hthresh = w*h*0.05
import time
from SimpleCV import *
from SimpleCV.Display import Display, pg
from SimpleCV.Segmentation import ColorSegmentation
segmentation = ColorSegmentation()
cam = Camera()
SegmentMode = False
x0 = 0
y0 = 0
x1 = 0
y1 = 0
img = cam.getImage()
display = Display((img.width,img.height))
mouse_down = False
while not display.isDone():
img = cam.getImage()
img = img.scale(160,120)
dl = DrawingLayer((img.width,img.height))
mystring = "( " +str(display.mouseX)+" , "+str(display.mouseY)+" )"
#print((display.mouseX,display.mouseY))
if SegmentMode:
segmentation.addImage(img)
if(segmentation.isReady()):
img = segmentation.getSegmentedImage()
img = img.erode(iterations = 2).dilate().invert()
img.dl().ezViewText(mystring, (30,30))
img = img.applyLayers()
display.writeFrame(img)
if(display.mouseLeft):
SegmentMode = False
segmentation.reset()
#!/usr/bin/python
import time
from SimpleCV import *
from SimpleCV.Display import Display, pg
display = Display(resolution=(800,
600)) #create a new display to draw images on
cam = Camera() #initialize the camera
done = False # setup boolean to stop the program
# Loop until not needed
while not display.isDone():
cam.getImage().flipHorizontal().save(
display) # get image, flip it so it looks mirrored, save to display
time.sleep(
0.01
) # Let the program sleep for 1 millisecond so the computer can do other things
if display.mouseLeft:
display.done = True #if the left arrow is pressed, close the program
# (re) load the SVM and feature extractors
classifierSVM = SVMClassifier.load("nutbolt.pkl")
def thresholdOpGreen(in_image):
return in_image.hueDistance(60).binarize(thresh=70).invert().dilate(2)
morph_extractor = MorphologyFeatureExtractor()
morph_extractor.setThresholdOperation(thresholdOp)
classifierSVM.setFeatureExtractors([morph_extractor])
count = 0
cam = Camera(0)
blobber = BlobMaker()
disp = Display(resolution=(800, 600))
minsize = 100
maxsize = (800 * 600) / 10
while not disp.isDone():
img = cam.getImage().resize(800, 600)
blobs = []
w = img.width
h = img.height
dl = DrawingLayer((w, h))
#segment our items from the background
bw = thresholdOpGreen(img)
#extract the blobs
blobs = blobber.extractFromBinary(bw, img, minsize, maxsize)
# if we get a blob
if (len(blobs) > 0):
# sort the blobs by size
import cv2
from operator import add
from SimpleCV import *
from SimpleCV.Display import Display
def to_rgb1a(im):
# This should be fsater than 1, as we only
# truncate to uint8 once (?)
w, h = im.shape
ret = np.empty((w, h, 3), dtype=np.uint8)
ret[:, :, 2] = ret[:, :, 1] = ret[:, :, 0] = im
return ret
d = Display()
#create video streams
cam = Kinect()
#initialize the camera
#cap = cv2.VideoCapture('vtest.avi')
fgbg = cv2.BackgroundSubtractorMOG2(1, 5)
while not d.isDone():
#ret, frame = cap.read()
frame = cam.getImage()
print frame
frame_np = frame.getNumpyCv2()
#!/usr/bin/python
import time, webbrowser
from operator import add
from SimpleCV import Color, ColorCurve, Kinect, Image, pg, np
from SimpleCV.Display import Display
d = Display()
#create video streams
cam = Kinect()
#initialize the camera
compositeframe = Image((640, 480))
#populate the compositeframe
offtime = 5.0
laststroke = time.time()
while not d.isDone():
img = cam.getImage()
imgscene = img.copy()
depth = cam.getDepth()
mindepth = np.min(depth.getNumpy())
if mindepth < 180:
depthbin = depth.binarize(np.min(depth.getNumpy()) + np.std(depth.getNumpy()) / 4).erode(3)
#take the front 1/4 stdev of the depth map
img = img.crop(0,25, 605, 455).scale(640,480)
#!/usr/bin/env python
# author: Powen Ko
print __doc__
import time
import csv
from SimpleCV import Color, ColorCurve, Camera, Image, pg, np, cv
from SimpleCV.Display import Display
cam = Camera()
display = Display((800,600))
data = "None"
mydict = dict()
myfile = "barcode-list.csv"
while display.isNotDone():
display.checkEvents()
img = cam.getImage()
img.drawRectangle(img.width/4,img.height/4,img.width/2,img.height/2,color=Color.RED,width=3)
if display.mouseLeft: #當用戶按下左鍵時
img.drawText("reading barcode... wait",10,10)
img.save(display)
barcode = img.findBarcode() #辨識條碼
if barcode:
print barcode
data = str(barcode[0].data) #取得條碼資料
print data
if mydict.has_key(data):
mydict[data] = mydict[data] + 1
else:
mydict[data] = 1
elif display.mouseRight: #當用戶按下右鍵時
print "save to CVS"
#!/usr/bin/python
import time, webbrowser
from operator import add
from SimpleCV import Color, ColorCurve, Kinect, Image, pg, np
from SimpleCV.Display import Display
d = Display(flags=pg.FULLSCREEN)
#create video streams
cam = Kinect()
#initialize the camera
compositeframe = Image((640, 480))
#populate the compositeframe
offtime = 5.0
laststroke = time.time()
while not d.isDone():
img = cam.getImage()
imgscene = img.copy()
depth = cam.getDepth()
mindepth = np.min(depth.getNumpy())
if mindepth < 180:
depthbin = depth.binarize(
np.min(depth.getNumpy()) + np.std(depth.getNumpy()) / 4).erode(3)
#take the front 1/4 stdev of the depth map
#!/usr/bin/python
import time
from SimpleCV import *
from SimpleCV.Display import Display, pg
display_width = 640
display_height = 480
display = Display(
resolution=(display_width,
display_height)) #create a new display to draw images on
cam = Camera() #initialize the camera
done = False # setup boolean to stop the program
# Loop until not needed
while not display.isDone():
image = cam.getImage().flipHorizontal()
crop_width = 200 #set the width of the crop window
crop_height = 200 #set the height of the crop window
crop_x = display.mouseX * image.width / display_width #set the x location to scale
crop_y = display.mouseY * image.height / display_height #set the y location to scale
if (display.mouseX <= 1): #mouse outside the left of the screen
crop_x = 1
if (display.mouseY <= 1): #mouse outside the top of the screen
crop_y = 1
if (display.mouseX + crop_width >=
display_width): #region outside the right side of the screen
crop_x = (display_width - crop_width)
if (display.mouseY + crop_height >=
display_height): #region below the bottom of the screen
#!/usr/bin/python
import time
from SimpleCV import *
from SimpleCV.Display import Display, pg
display = Display(resolution = (800, 600)) #create a new display to draw images on
cam = Camera() #initialize the camera
done = False # setup boolean to stop the program
# Loop until not needed
while not display.isDone():
cam.getImage().flipHorizontal().save(display) # get image, flip it so it looks mirrored, save to display
time.sleep(0.01) # Let the program sleep for 1 millisecond so the computer can do other things
if display.mouseLeft:
display.done = True #if the left arrow is pressed, close the program
Then line up the item in the red box and left click the mouse to tell
the program to try and read the barcode
'''
print __doc__
import time
import csv
from SimpleCV import Color, ColorCurve, Camera, Image, pg, np, cv
from SimpleCV.Display import Display
cam = Camera()
display = Display((800,600))
data = "None"
mydict = dict()
myfile = "barcode-list.csv"
while display.isNotDone():
display.checkEvents()#check for mouse clicks
img = cam.getImage()
img.drawRectangle(img.width/4,img.height/4,img.width/2,img.height/2,color=Color.RED,width=3)
if display.mouseLeft: # click the mouse to read
img.drawText("reading barcode... wait",10,10)
img.save(display)
barcode = img.findBarcode()
if barcode: # if we have a barcode
data = str(barcode.data)
print data
#!/usr/bin/python
#
# This example rotates through a few of the image morphology examples
#
from SimpleCV import *
from numpy import linspace
from scipy.interpolate import UnivariateSpline
import sys, time, socket
import time
from SimpleCV import *
from SimpleCV.Display import Display, pg
display = Display(resolution=(800,
600)) #create a new display to draw images on
cam = Camera() #initialize the camera
done = False # setup boolean to stop the program
max_threshold = 1 # this is used for the edge detection
threshold_step = 1 # this is the amount to adjust the threshold by each time the display is updated
threshold = max_threshold
example = 1
# Loop until not needed
while not display.isDone():
image = cam.getImage().flipHorizontal() # get image (or frame) from camera
# This just automatically cycles through threshold levels
if (threshold >= 20):
threshold = max_threshold
if (example >= 4):
example = 1
else:
from pygame.locals import * from random import randrange from helper_classes import Bird, Pipe import os #################### import SimpleCV from SimpleCV import * from SimpleCV.Display import Display import numpy as np cam = Camera(0) i = cam.getImage() #print i.size() d = Display(i.size()) col = Color.RED ###################### SCORE_COLOR = (255, 25, 20) HIGHSCORE_COLOR = (0, 0, 255) Y_SCORE_COLOR = (0, 255, 0) DISPLAY_WIDTH = 1200 DISPLAY_HEIGHT = 700 factor = float(DISPLAY_HEIGHT) / 480 FONT = None FONT_SIZE = 100
from SimpleCV import *
import numpy as np
from SimpleCV.Display import Display
cam = Camera()
import time
from mouse_api import *
m = Mouse()
nf = 2
h = 0
fl = []
reset = 0
while h < nf:
h = h + 1
snap = cam.getImage()
d = Display(snap.size())
snap.save(d)
col = Color.RED
start_time = time.time()
i = 0
while d.isNotDone():
elapsed_time = time.time() - start_time
if d.mouseLeft:
txt = "coord: (" + str(d.mouseX) + "," + str(d.mouseY) + ")"
snap.dl().text(txt, (10, snap.height / 2), color=col)
txt = "color: " + str(snap.getPixel(d.mouseX, d.mouseY))
snap.dl().text(txt, (10, (snap.height / 2) + 10), color=col)
print "coord: (" + str(d.mouseX) + "," + str(
d.mouseY) + "), color: " + str(
snap.getPixel(d.mouseX, d.mouseY))
if i == 1:
#!/usr/bin/python
import time, webbrowser
from operator import add
from SimpleCV import Color, ColorCurve, Camera, Image, pg, np, cv, HaarCascade
from SimpleCV.Display import Display
cam = Camera(1)
time.sleep(.1) # uhg
display = Display((800,600))
counter = 0
# load the cascades
face_cascade = HaarCascade("./../Features/HaarCascades/face.xml")
nose_cascade = HaarCascade("./../Features/HaarCascades/nose.xml")
stache = Image("./stache.png") # load the stache
mask = stache.createAlphaMask() # load the stache mask
count = 0
while( display.isNotDone() ):
#count = count + 1
img = cam.getImage()
img = img.scale(.5) #use a smaller image
faces = img.findHaarFeatures(face_cascade) #find faces
if( faces is not None ): # if we have a face
faces = faces.sortArea() #get the biggest one
face = faces[-1]
myFace = face.crop() # get the face image
noses = myFace.findHaarFeatures(nose_cascade) #find the nose
if( noses is not None ):# if we have a nose
noses = noses.sortArea()
nose = noses[0] # get the biggest
# these get the upper left corner of the face/nose
from SimpleCV import * from SimpleCV.Display import Display import xaut mouse = xaut.mouse() delay = mouse.move_delay(0) custom_red = (121.0, 41.0, 37.0) disp = Display(resolution=(640,480)) white_img = Image((640,480)).invert() YELLOW=(179.0, 195.0, 112.0) cam = Camera() while not disp.isDone(): original_img = cam.getImage().flipHorizontal() red_distance_img = original_img.colorDistance(color=Color.RED) red_bin = red_distance_img.threshold(100).invert() blobs = red_bin.findBlobs(minsize=50,maxsize=10720) if(blobs is not None): blob = max(blobs) mouse.move(15*(blob.x-256),12.5*(blob.y-192)) red_bin.save(disp) if disp.mouseLeft: disp.done = True xaut.cleanup()
import time
from SimpleCV import *
from SimpleCV.Display import Display, pg
w = 400
h = 300
t=1
display = Display(resolution = (w,h)) #create a new display to draw images on
img = Image('../sampleimages/aerospace.jpg')
img = img.scale(800,600)
img2 = img.scale(w,h)
smallWbigH = img.scale(100,400)
smallHbigW = img2.scale(500,100)
smallW = img2.scale(100,h)
smallH = img2.scale(w,100)
small = img2.scale(99,23)
big = img2.scale(555,432)
foo = "Image:"+str((img.width,img.height))
print(foo)
print('Image should scale clean')
display.writeFrame(img)
time.sleep(t)
foo = "Image:"+str((img2.width,img2.height))
print(foo)
print('Image should scale clean')
display.writeFrame(img2)
time.sleep(t)
foo = "Image:"+str((smallWbigH.width,smallWbigH.height))
print(foo)
then click the right lower corner of what you want to train.
This will give you a template. For instance if you wanted to train
a face to recognize in the image you would click on the upper left corner
of the face, then click in the lower right corner of the face. If you
want to retrain then just right click to reset.
'''
print __doc__
import time
from SimpleCV import Color, Image, np, Camera
from SimpleCV.Display import Display
cam = Camera(0)
display = Display((640, 480)) # create our display
quality = 400.00
minDist = 0.35
minMatch = 0.2
template_img = None
mode = "untrained"
startX = None
startY = None
endY = None
endX = None
while (display.isNotDone()):
img = cam.getImage().resize(640, 480)
#Display this if a template has not been trained yet
#!/usr/bin/python
import time
from SimpleCV import *
from SimpleCV.Display import Display, pg
display_width = 640
display_height = 480
display = Display(resolution=(display_width, display_height)) # create a new display to draw images on
cam = Camera() # initialize the camera
done = False # setup boolean to stop the program
# Loop until not needed
while not display.isDone():
image = cam.getImage().flipHorizontal()
crop_width = 200 # set the width of the crop window
crop_height = 200 # set the height of the crop window
crop_x = display.mouseX * image.width / display_width # set the x location to scale
crop_y = display.mouseY * image.height / display_height # set the y location to scale
if display.mouseX <= 1: # mouse outside the left of the screen
crop_x = 1
if display.mouseY <= 1: # mouse outside the top of the screen
crop_y = 1
if display.mouseX + crop_width >= display_width: # region outside the right side of the screen
crop_x = display_width - crop_width
if display.mouseY + crop_height >= display_height: # region below the bottom of the screen
crop_y = display_height - crop_height
cropped_image = image.crop(crop_x, crop_y, crop_width, crop_height) # crop out the section of image we want
xray_image = cropped_image.edges().smooth() # get the edges of cropped region
def main(camindex = 0, capture_width = 800, capture_height = 600, chessboard_width = 9, chessboard_height = 6, planemode = False, gridsize = 0.029, calibrationFile = "default"):
global save_location
if planemode:
mode = 7
else:
mode = 0
dims = (chessboard_width, chessboard_height)
cam = Camera(camindex, prop_set = { "width": capture_width, "height": capture_height })
d = Display((capture_width, capture_height))
save_location = "" #change this if you want to save your calibration images
calibration_set = [] #calibration images
fc_set = []
introMessage()
while not d.isDone():
time.sleep(0.01)
i = cam.getImage().flipHorizontal()
cb = i.findChessboard(dims, subpixel = False)
if cb:
cb = cb[0]
elif mode != 6:
showText(i, "Put a chessboard in the green outline")
if mode == 0: #10 pictures, chessboard filling 80% of the view space
findLargeFlat(cb, i, calibration_set, dims)
if (len(calibration_set) == 10):
mode = 1
elif mode == 1: #5 pictures, chessboard filling 60% of screen, at 45 deg horiz
findHorizTilted(cb, i, calibration_set, dims)
if (len(calibration_set) == 15):
mode = 2
elif mode == 2: #5 pictures, chessboard filling 60% of screen, at 45 deg vert
findVertTilted(cb, i, calibration_set, dims)
if (len(calibration_set) == 20):
mode = 3
elif mode == 3: #5 pictures, chessboard filling 40% of screen, corners at 45
findCornerTilted(cb, i, calibration_set, dims)
if (len(calibration_set) == 25):
mode = 4
elif mode == 4: #10 pictures, chessboard filling 12% - 25% of view space
findSmallFlat(cb, i, calibration_set, dims)
if (len(calibration_set) == 35):
mode = 5
elif mode == 5:
cam.calibrate(calibration_set, gridsize, dims)
cam.saveCalibration(calibrationFile)
mode = 6
elif mode == 6:
showText(i, "Saved calibration to " + calibrationFile)
elif mode == 7:
findPlane(cb, i, calibration_set, dims)
if (len(calibration_set) == 25):
mode = 5
if cb:
cb.draw()
i.save(d)
#!/usr/bin/python
from operator import add
from SimpleCV import *
from SimpleCV.Display import Display
d = Display()
#create video streams
cam = Kinect()
#initialize the camera
frames_to_blur = 4
frames = ImageSet()
depth = cam.getDepth().stretch(0,200)
while True:
new_depth = cam.getDepth().stretch(0,200)
img = cam.getImage()
diff_1 = new_depth - depth
diff_2 = depth - new_depth
diff = diff_1 + diff_2
img_filter = diff.binarize(0)
motion_img = img - img_filter
motion_img_open = motion_img.morphOpen()
frames.append(motion_img_open)
if len(frames) > frames_to_blur:
frames.pop(0)
pic = reduce(add, [i / float(len(frames)) for i in frames])
#!/usr/bin/python
import time, webbrowser
from operator import add
from SimpleCV import Color, ColorCurve, Camera, Image, pg, np, cv
from SimpleCV.Display import Display
cam = Camera(0)
time.sleep(.1) # uhg
display = Display((800,600))
counter = 0
# load the cascades
face_cascade = cv.Load("./../Features/HaarCascades/face.xml")
nose_cascade = cv.Load("./../Features/HaarCascades/nose.xml")
stache = Image("./stache.png") # load the stache
mask = stache.createAlphaMask() # load the stache mask
count = 0
while( display.isNotDone() ):
#count = count + 1
img = cam.getImage()
img = img.scale(.5) #use a smaller image
faces = img.findHaarFeatures(face_cascade) #find faces
if( faces is not None ): # if we have a face
faces = faces.sortArea() #get the biggest one
face = faces[-1]
myFace = face.crop() # get the face image
noses = myFace.findHaarFeatures(nose_cascade) #find the nose
if( noses is not None ):# if we have a nose
noses = noses.sortArea()
nose = noses[0] # get the biggest
# these get the upper left corner of the face/nose
from SimpleCV import *
from numpy import *
from SimpleCV.Display import Display, pg
from SimpleCV import EdgeHistogramFeatureExtractor
from SimpleCV import MorphologyFeatureExtractor
def thresholdOp(in_image):
return in_image.hueDistance(60).binarize(thresh=70).invert().dilate(2)
cam = Camera(1)
#classifier.load(saveFile)
blobber = BlobMaker()
disp = Display(resolution=(1440, 900))
#these params are to save the image
count = 0
path = ''
file = './data/bolts/bolts'
ext = '.png'
img = cam.getImage()
minsize = 350 # img.width*img.height/200
maxsize = img.width * img.height / 8
avgColorThresh = 85
count = 0
while not disp.isDone():
img = cam.getImage()
blobs = []
w = img.width
#!/usr/bin/python
from SimpleCV import Kinect, Image, pg, np, time
from SimpleCV.Display import Display
d = Display(flags=pg.FULLSCREEN)
#create video streams
cam = Kinect()
#initialize the camera
depth = cam.getDepth().stretch(0, 200)
while True:
new_depth = cam.getDepth().stretch(0, 200)
img = cam.getImage()
diff_1 = new_depth - depth
diff_2 = depth - new_depth
diff = diff_1 + diff_2
img_filter = diff.binarize(0)
motion_img = img - img_filter
motion_img_open = motion_img.morphOpen()
motion_img_open.show()
depth = new_depth
import time
from SimpleCV import *
from SimpleCV.Display import Display, pg
from SimpleCV.Segmentation import ColorSegmentation
segmentation = ColorSegmentation()
cam = Camera()
SegmentMode = False
x0 = 0
y0 = 0
x1 = 0
y1 = 0
img = cam.getImage()
display = Display((img.width, img.height))
mouse_down = False
while not display.isDone():
img = cam.getImage()
img = img.scale(160, 120)
dl = DrawingLayer((img.width, img.height))
mystring = "( " + str(display.mouseX) + " , " + str(display.mouseY) + " )"
#print((display.mouseX,display.mouseY))
if SegmentMode:
segmentation.addImage(img)
if (segmentation.isReady()):
img = segmentation.getSegmentedImage()
img = img.erode(iterations=2).dilate().invert()
img.dl().ezViewText(mystring, (30, 30))
img = img.applyLayers()
display.writeFrame(img)
if (display.mouseLeft):
SegmentMode = False
sudo apt-get install python-zbar
Then line up the item in the red box and left click the mouse to tell
the program to try and read the barcode
'''
print __doc__
import time
import csv
from SimpleCV import Color, ColorCurve, Camera, Image, pg, np, cv
from SimpleCV.Display import Display
cam = Camera()
display = Display((800, 600))
data = "None"
mydict = dict()
myfile = "barcode-list.csv"
while display.isNotDone():
display.checkEvents() #check for mouse clicks
img = cam.getImage()
img.drawRectangle(img.width / 4,
img.height / 4,
img.width / 2,
img.height / 2,
color=Color.RED,
width=3)
if display.mouseLeft: # click the mouse to read
img.drawText("reading barcode... wait", 10, 10)
from SimpleCV import *
import numpy as np
from SimpleCV.Display import Display
cam=Camera()
import time
from mouse_api import *
m = Mouse()
nf = 2
h = 0
fl=[]
reset = 0
while h<nf:
h = h + 1
snap = cam.getImage()
d = Display(snap.size())
snap.save(d)
col = Color.RED
start_time = time.time()
i=0
while d.isNotDone():
elapsed_time = time.time() - start_time
if d.mouseLeft:
txt = "coord: (" + str(d.mouseX) + "," + str(d.mouseY) + ")"
snap.dl().text(txt, (10,snap.height / 2), color=col)
txt = "color: " + str(snap.getPixel(d.mouseX,d.mouseY))
snap.dl().text(txt, (10,(snap.height / 2) + 10), color=col)
print "coord: (" + str(d.mouseX) + "," + str(d.mouseY) + "), color: " + str(snap.getPixel(d.mouseX,d.mouseY))
if i==1:
x2=d.mouseX
y2=d.mouseY
