GMU:Eval(nature)/A Dish of Code: Difference between revisions

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(image processing code)
 
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===== Image Capture =====
Image capture with Processing
<pre style="font-size: smaller">
add_library('video')
video = Capture(this, 640, 480)
fps = 100
global recording
recording = False
def setup():
   
    # setup video and canvas
    video.start()
    size(video.width, video.height)
    frameRate(fps)
   
    # red text
    fill(255, 0, 0)
def draw():
   
    # load frame from webcam
    video.read()
       
    # show frame on screen
    image(video, 0, 0)
    # save frame to disk
    if recording == True:
        saveFrame("video_#######.png")
        if frameCount % fps < fps/2:
            text("RECORD", width - 50, 20)
    # can we keep up with the framerate ?
    if frameRate < (fps - 1):
        print "Warning. Can only record with %i fps" % frameRate
def keyPressed():
    global recording
    recording = not recording
   
def mousePressed():
    global recording
    recording = not recording
</pre>
===== Image Processing =====
===== Image Processing =====



Revision as of 12:51, 30 April 2015

Image Capture

Image capture with Processing

add_library('video')

video = Capture(this, 640, 480)

fps = 100
global recording
recording = False

def setup():
    
    # setup video and canvas
    video.start()
    size(video.width, video.height)
    frameRate(fps)
    
    # red text
    fill(255, 0, 0)


def draw():
    
    # load frame from webcam
    video.read()
         
    # show frame on screen
    image(video, 0, 0)

    # save frame to disk
    if recording == True:
        saveFrame("video_#######.png")
        if frameCount % fps < fps/2:
            text("RECORD", width - 50, 20)

    # can we keep up with the framerate ?
    if frameRate < (fps - 1):
        print "Warning. Can only record with %i fps" % frameRate



def keyPressed():
    global recording 
    recording = not recording
    
def mousePressed():
    global recording 
    recording = not recording


Image Processing

Foreground Separation

Simple Foreground Separation with Processing.


img = loadImage("leaves.jpg")

size(800, 600)

# function as for loop
def markit():
    for i in range(len(img.pixels)):
        if brightness(img.pixels[i]) > 100:
            img.pixels[i] = color(0)
        else:
            img.pixels[i] = color(255)
    
# function as list comprehension
def markit2():
    img.pixels = [color(0) if brightness(p) > 100 else color(255) for p in img.pixels ]

# modify image
img.loadPixels()
markit2()
img.updatePixels()

# show image
image(img, 0, 0, width, height)