In [10]:

    

import os
os.getpid()


    

    
Out[10]:





8420

In [32]:

    

>>> import cv2
>>> print cv2.__version__


    

    




2.4.9

In [6]:

    

import numpy as np
import cv2


    

In [36]:

    

import os 
WORKSPACE = r"C:\android\android_workspace\tamtam"
ORIGINAL_VIDEO = WORKSPACE + r"\experiments\videos\samsung-s4-front.MOV"
RESULTS_DIR = WORKSPACE + r"\experiments\results" + "\\"
RESULTS_DIR += os.path.splitext(os.path.basename(ORIGINAL_VIDEO))[0] + "__"

assert os.path.exists(WORKSPACE)
assert os.path.exists(ORIGINAL_VIDEO)
# assert os.path.exists(RESULTS_DIR)


    

In [14]:

    

## READ video example

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"


    

In [15]:

    

## WRITE video example video example

RESULT_VIDEO = RESULTS_DIR + "test.MOV"
print RESULT_VIDEO

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RESULT_VIDEO, four_cc, fps, (frame_width, frame_height), False)

assert res_video.isOpened()


    

    




D:\my\tamtam\experiments\results\test.MOV
True

In [16]:

    

RES_FILE =RESULTS_DIR + "BackgroundSubtractorMOG.mov"

# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), False)

assert res_video.isOpened()

# make bacground video


fgbg = cv2.BackgroundSubtractorMOG()
i = 1

while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break

    fgmask = fgbg.apply(frame)
    res_video.write(fgmask & fgmask)
    if frame is None:
        print 'break2 !' , frame
        break

    # cv2.imwrite(r"d:\my\res\fram_%d.jpg" % i, fgmask)
    i = i + 1

video.release()
res_video.release()


    

    




True
break ! False

In [17]:

    

RES_FILE =RESULTS_DIR + "BackgroundSubtractorMOG2.mov"

# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), False)

assert res_video.isOpened()

# make bacground video


fgbg = cv2.BackgroundSubtractorMOG2()
i = 1

while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break

    fgmask = fgbg.apply(frame)
    res_video.write(fgmask & fgmask)
    if frame is None:
        print 'break2 !' , frame
        break

    # cv2.imwrite(r"d:\my\res\fram_%d.jpg" % i, fgmask)
    i = i + 1

video.release()
res_video.release()


    

    




True
break ! False

In [18]:

    

RES_FILE =RESULTS_DIR + "CopyOfVideo.mov"

# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height))

assert res_video.isOpened()

# make bacground video


i = 1

while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break

    res_video.write(frame)

    # cv2.imwrite(r"d:\my\res\fram_%d.jpg" % i, fgmask)
    i = i + 1

video.release()
res_video.release()


    

    




True
break ! False

In [40]:

    

RES_FILE =RESULTS_DIR + "simple_background_subtraction.mov"

# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), True)

assert res_video.isOpened()

# make bacground video


i = 1

ret, frame0 = video.read()
means = []
while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break

    res_video.write(frame - frame0)
    means.append(np.mean(frame - frame0))
    i = i + 1

video.release()
res_video.release()


    

    




True
break ! False

In [19]:

    

cv2.imwrite(RESULTS_DIR + "fram0.jpg", frame0)


    

    
Out[19]:





True

In [8]:

    

RES_FILE =RESULTS_DIR + "simple_background_subtraction_grayscale.mov"

# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), False)

assert res_video.isOpened()

# make bacground video


i = 1

ret, frame0 = video.read()
frame0_gray = cv2.cvtColor(frame0, cv2.COLOR_BGR2GRAY)

while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break
        
    frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    new = frame_gray - frame0_gray
    if np.mean(new) > 50:
        xxx = new
    res_video.write(new)

    # cv2.imwrite(r"d:\my\res\fram_%d.jpg" % i, fgmask)
    i = i + 1

video.release()
res_video.release()


    

    




True
break ! False

In [4]:

    

RES_FILE =RESULTS_DIR + "background_subtraction_with_blur.mov"


# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer
four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), True)

assert res_video.isOpened()

# make bacground video


i = 1

ret, frame0 = video.read()
ret, frame1 = video.read()

while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break
        
    new  = frame - frame0

    res_video.write(cv2.blur(new, (100, 100)))

    # cv2.imwrite(r"d:\my\res\fram_%d.jpg" % i, fgmask)
    i = i + 1

video.release()
res_video.release()


    

    




True
break ! False

In [21]:

    

# in range activation


HAND_MIN = np.array([190, 190, 190],np.uint8)
HAND_MAX = np.array([255, 255, 255],np.uint8)

new  = cv2.inRange(xxx, HAND_MIN, HAND_MAX)
cv2.imwrite(r"d:\my\res\test.jpg", new)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-21-99ae2ed19ceb> in <module>()
      3 HAND_MAX = np.array([255, 255, 255],np.uint8)
      4 
----> 5 new  = cv2.inRange(xxx, HAND_MIN, HAND_MAX)
      6 cv2.imwrite(r"d:\my\res\test.jpg", new)

NameError: name 'xxx' is not defined

In [10]:

    

v = cv2.findContours(xxx, cv2.cv.CV_RETR_LIST, cv2.cv.CV_CHAIN_APPROX_SIMPLE )


    

In [16]:

    

cv2.imwrite(r'd:\my\fff.jpg', xxx)


    

    
Out[16]:





True

In [22]:

    

means


    

    
Out[22]:





[8.2429889231220663,
 19.396220290492959,
 38.830633802816898,
 56.808766138497653,
 71.771865830399065,
 84.384112749413148,
 92.556767165492957,
 99.501969630281693,
 104.76724251760564,
 109.80660944835681,
 113.34384903169014,
 117.09288989143192,
 118.14658890845071,
 119.89952501467135,
 120.73268779342723,
 121.94386003521127,
 122.54669894366197,
 123.68059712441314,
 56.128449603873243,
 39.524673562206573,
 37.968689480633806,
 36.804177670187791,
 28.887338615023474,
 27.593023767605633,
 26.59102296068075,
 25.758003227699529,
 25.521590742370893,
 27.957245818661971,
 31.519632115610328,
 40.711605046948357,
 67.879256528755874,
 94.128730193661966,
 96.103788879107981,
 76.77838725058686,
 67.680767678990605,
 62.804683832159625,
 59.450000000000003,
 55.498963835093896,
 51.999257262323944,
 31.110873312793426,
 30.099526848591548,
 29.803889744718308,
 28.066787705399062,
 28.576683538732393,
 44.364033157276992,
 45.463631528755869,
 46.494714642018778,
 47.614748386150232,
 71.221730120305168,
 73.941360401995311,
 76.262232247652577,
 86.397397667253514,
 164.79169600938968,
 168.02102589495306,
 139.92761883802817,
 137.85948686913144,
 138.59419747652584,
 97.531525088028175,
 46.167904562793424,
 43.603695349178402,
 41.934321816314551,
 31.282676789906102,
 29.763253741197182,
 28.593216329225353,
 27.884290639671363,
 27.463486649061032,
 27.069668794014085,
 27.294476232394366,
 27.433947696596245,
 27.313666373239435,
 28.377974618544602,
 29.023956499413146,
 30.268889377934272,
 31.315993617957748,
 32.278766872065731,
 33.21575154049296,
 34.509085240610325,
 37.005811693075117,
 40.23691864730047,
 44.40772997359155,
 48.753757702464789,
 51.812540346244134,
 53.877009976525819,
 54.061291446596243,
 52.081189480633803,
 48.436793940727696,
 45.1442011443662,
 42.881765331572772,
 39.990351745892021,
 37.294885196596248,
 34.791945422535214,
 32.691400748239438,
 31.170433538732393,
 29.924224251760563,
 27.03149207746479,
 24.371024061032863,
 21.687584360328639,
 19.321101085680752,
 17.545475718896714,
 17.784670261150236,
 17.904273034037558,
 18.721414686032865,
 20.119041593309859,
 21.799844116784037,
 24.864029489436621,
 33.745510563380279,
 41.986337294600936,
 66.088534330985922,
 70.401054504107975,
 73.637001173708924,
 76.186869131455396,
 73.476265404929578,
 66.734633582746483,
 58.674171068075118,
 41.140513130868541,
 34.966160504694834,
 28.384873826291081,
 24.637842943075118,
 22.063690214201877,
 19.794562426643193,
 18.445600425469483,
 27.04746552230047,
 27.193865536971831,
 46.389431117957749,
 45.70518449237089,
 44.212960313967137,
 43.944149794600939,
 46.914638350938965,
 51.176173708920189,
 52.40731367370892,
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 56.600386957159621,
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 58.852167693661968,
 59.649792767018781,
 61.37248752934272,
 62.918759169600939,
 63.866398914319248,
 63.887171728286383,
 64.533960534037561,
 66.389968456572774,
 69.296174442488265,
 84.342787191901408,
 109.05494791666666,
 101.42394549589201,
 81.17581059272301,
 60.83044490903756,
 55.55930897887324,
 57.203165346244134,
 53.074776261737092,
 53.674552523474176,
 52.926518485915494,
 47.805111135563379,
 45.096759463028171,
 43.551610181924886,
 43.425049515845068,
 42.641101819248824,
 41.657874853286387,
 41.034558392018781,
 40.896499046361505,
 40.939610842136148,
 41.34772410504695,
 41.99722527875587,
 42.995295994718312,
 44.430180824530517,
 46.048120231807509,
 48.24312646713615,
 50.524024354460096,
 52.779509609741787,
 55.197865316901407,
 57.437206572769952,
 60.076883436032865,
 62.287195569248823,
 64.014082673122061,
 63.470613262910796,
 64.573492517605629,
 63.788785578051645,
 61.418322696596242,
 58.213703051643193,
 55.43708370011737,
 54.812921801643192,
 52.341033964201877,
 50.800309932511738,
 49.737424809272298,
 48.193584947183098,
 46.949845950704223,
 44.588787411971829,
 43.667156323356807,
 42.373140404929579,
 41.568102626173712,
 41.01792656983568,
 42.539612676056336,
 43.115768045774651,
 43.841364069835677,
 44.491323723591549,
 43.116459433685449,
 38.773525528169017,
 36.101395613262909,
 35.886276775234741,
 37.118253007629107,
 40.717358054577467,
 45.979658157276994,
 50.232328345070421,
 52.094474398474176,
 50.60510196596244,
 54.835996185446007,
 52.68805934565728,
 48.125625366784035,
 42.825102699530518,
 38.912131382042254,
 37.170930531103288,
 38.613719556924885,
 39.389097344483567,
 40.661579372065731,
 43.011856294014088,
 46.749567194835677,
 50.956473738262908,
 54.603150674882627,
 57.45828748532864,
 58.514874926643195,
 56.558929357394369,
 58.248613556338029,
 58.591041299882626,
 56.06602112676056,
 50.828526628521125,
 43.578849398474176,
 36.248466842723005,
 31.538429797535212,
 31.359884829812206,
 31.402046654929578,
 31.472126247065727,
 31.556435225938966,
 31.682856514084506,
 32.002767385563381,
 32.758118764671359,
 35.032315507629107,
 38.9769677963615,
 51.093537265258213,
 54.818964568661968,
 55.747029049295776,
 56.549979826877937,
 57.698248606220659,
 58.436375806924886,
 59.006077611502349,
 59.283208626760562,
 60.224554357394368,
 60.041329225352115,
 60.481235328638498,
 62.481073943661968,
 65.200429137323937,
 68.081666299882627,
 70.55231624119719,
 72.981150968309862,
 75.680136810446015,
 72.767216842723002,
 73.231959727112681,
 77.853570642605632,
 83.515527802230054,
 90.215028975938964,
 101.02956095950704,
 111.88268962734742,
 121.52527508802817,
 138.36645943368543,
 141.3922773620892,
 103.31854643485916,
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 89.325066021126759,
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 75.413090522300465,
 72.809910504694841,
 71.376621185446012,
 76.765845070422529,
 82.348426496478879,
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 73.536023694248826,
 67.211370305164323,
 61.130032276995308,
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 42.252209873826288,
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 42.242117811032863,
 48.055650308098592,
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 92.287091035798127,
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 90.052969116784041,
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 45.357977552816898,
 42.216877567488261,
 39.269111282276995,
 36.064056998239437,
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 27.04794784330986,
 24.807256822183099,
 22.013057511737088,
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 20.900485988849766,
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 27.315579151995305,
 32.272489363262913,
 39.299774427816899,
 56.256732321009387,
 91.002464788732397,
 93.78379364730047,
 71.65041996772301,
 54.212153389084506,
 49.730261517018782,
 41.574337954812208,
 33.932310005868544,
 23.688299589201879,
 22.680303697183099,
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 28.821731954225353,
 34.928040639671359,
 47.339135856807509,
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 71.377690360915494,
 71.64055714495305,
 51.802877420774649,
 38.051353433098591,
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 28.810484521713615,
 26.328280883215964,
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 28.142064627347416,
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 41.898708920187794,
 37.709664759389675,
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 97.766650161384973,
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 33.080090962441318,
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 35.038853433098595,
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 35.135258949530517,
 35.250827098004692,
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 35.939016651995303,
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 36.330078125,
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 36.407165126173709,
 36.426520319835682,
 36.260211267605634,
 36.338919454225355,
 36.734507042253519]

In [17]:

    

history = 200 # default 200
nmixtures = 5 # 5
backgroundRatio =  0.2 # 0.7
noiseSigma= 8000 # 15.0
learning = 100 # 0

RES_FILE =RESULTS_DIR + "BMOG_hist_%d_backratio_%r_nmixture_%d_noise_%r_learning_%r.mov" % (history, backgroundRatio, nmixtures, noiseSigma, learning) 

# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), False)

assert res_video.isOpened()

# make bacground video


fgbg = cv2.BackgroundSubtractorMOG(history, nmixtures, backgroundRatio, noiseSigma)
i = 1

while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break

    fgmask = fgbg.apply(frame, learning)
    res_video.write(fgmask & fgmask)
    if frame is None:
        print 'break2 !' , frame
        break

    # cv2.imwrite(r"d:\my\res\fram_%d.jpg" % i, fgmask)
    i = i + 1

video.release()
res_video.release()


    

    




True
break ! False

In [8]:

    

plt.plot(x)


    

    
Out[8]:





[<matplotlib.lines.Line2D at 0x65f8c30>]






    

In [100]:

    

# http://docs.opencv.org/modules/video/doc/motion_analysis_and_object_tracking.html#backgroundsubtractormog
learning = 0 # 0

history = 0 # 500
varThreshold = 160 # 4.0f * 4.0f ??
bShadowDetection =  False


RES_FILE =RESULTS_DIR + "MOG2_history_%d_vtrshould_%r_shadow_detect_%r_learning_%r.mov" % (history, varThreshold, bShadowDetection, learning)

# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), False)

assert res_video.isOpened()

# make bacground video


fgbg = cv2.BackgroundSubtractorMOG2(history, varThreshold, bShadowDetection)
i = 1

while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break

    fgmask = fgbg.apply(frame, learning)
    res_video.write(fgmask & fgmask)
    if frame is None:
        print 'break2 !' , frame
        break

    # cv2.imwrite(r"d:\my\res\fram_%d.jpg" % i, fgmask)
    i = i + 1

video.release()
res_video.release()


    

    




True
break ! False

In [44]:

    

RESULTS_DIR


    

    
Out[44]:





'D:\\my\\tamtam\\experiments\\results\\samsung-s3-front__'

In [52]:

    

cv2.imwrite(RESULTS_DIR + "foo.jpg", frame)


    

    
Out[52]:





False

In [8]:

    

# http://docs.opencv.org/modules/video/doc/motion_analysis_and_object_tracking.html#backgroundsubtractormog
learning = 0 # 0

history = 0 # 500
varThreshold = 160 # 4.0f * 4.0f ??
bShadowDetection =  False


RES_FILE =RESULTS_DIR + "C_MOG2_history_%d_vtrshould_%r_shadow_detect_%r_learning_%r.mov" % (history, varThreshold, bShadowDetection, learning)

# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), False)

assert res_video.isOpened()

# make bacground video


fgbg = cv2.BackgroundSubtractorMOG2(history, varThreshold, bShadowDetection)
i = 1

while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break
        
    fgmask = fgbg.apply(frame, learning)
    contours, hierarchy = cv2.findContours(fgmask,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    cv2.drawContours(frame,contours,-1,(0,255,0),3)

    res_video.write(frame)
    if frame is None:
        print 'break2 !' , frame
        break

    # cv2.imwrite(r"d:\my\res\fram_%d.jpg" % i, fgmask)
    i = i + 1

video.release()
res_video.release()


    

    




True






    




---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
<ipython-input-8-02eac90781f9> in <module>()
     42     fgmask = fgbg.apply(frame, learning)
     43     contours, hierarchy = cv2.findContours(fgmask,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
---> 44     cv2.drawContours(frame,contours,-1,(0,255,0),3)
     45 
     46     res_video.write(frame)

KeyboardInterrupt: 

In [12]:

    

for h,cnt in enumerate(contours):
    mask = np.zeros(frame.shape,np.uint8)
    cv2.drawContours(mask,[cnt],0,255,-1)
    cv2.imwrite(RESULTS_DIR + "X%d.jpg" % h, mask)


    

In [64]:

    

x = cv2.findContours(xxx, cv2.cv.CV_RETR_LIST , cv2.cv.CV_CHAIN_APPROX_NONE )
cv2.drawContours(xxx ,x[0], -1, (0,255,0),-1)
cv2.imwrite(RESULTS_DIR+ 'X.jpg', xxx)


    

    
Out[64]:





True

In [79]:

    

cc[1]


    

    
Out[79]:





array([[[  1,  -1,  -1,  -1],
        [  2,   0,  -1,  -1],
        [  3,   1,  -1,  -1],
        [  4,   2,  -1,  -1],
        [  5,   3,  -1,  -1],
        [  6,   4,  -1,  -1],
        [  7,   5,  -1,  -1],
        [  8,   6,  -1,  -1],
        [  9,   7,  -1,  -1],
        [ 10,   8,  -1,  -1],
        [ 11,   9,  -1,  -1],
        [ 12,  10,  -1,  -1],
        [ 13,  11,  -1,  -1],
        [ 14,  12,  -1,  -1],
        [ 15,  13,  -1,  -1],
        [ 16,  14,  -1,  -1],
        [ 17,  15,  -1,  -1],
        [ 18,  16,  -1,  -1],
        [ 19,  17,  -1,  -1],
        [ 20,  18,  -1,  -1],
        [ 21,  19,  -1,  -1],
        [ 22,  20,  -1,  -1],
        [ 23,  21,  -1,  -1],
        [ 24,  22,  -1,  -1],
        [ 25,  23,  -1,  -1],
        [ 26,  24,  -1,  -1],
        [ 27,  25,  -1,  -1],
        [ 28,  26,  -1,  -1],
        [ 29,  27,  -1,  -1],
        [ 30,  28,  -1,  -1],
        [ 31,  29,  -1,  -1],
        [ 32,  30,  -1,  -1],
        [ 33,  31,  -1,  -1],
        [ 34,  32,  -1,  -1],
        [ 35,  33,  -1,  -1],
        [ 36,  34,  -1,  -1],
        [ 37,  35,  -1,  -1],
        [ 38,  36,  -1,  -1],
        [ 39,  37,  -1,  -1],
        [ 40,  38,  -1,  -1],
        [ 41,  39,  -1,  -1],
        [ 42,  40,  -1,  -1],
        [ 43,  41,  -1,  -1],
        [ 44,  42,  -1,  -1],
        [ 45,  43,  -1,  -1],
        [ 46,  44,  -1,  -1],
        [ 47,  45,  -1,  -1],
        [ 48,  46,  -1,  -1],
        [ 49,  47,  -1,  -1],
        [ 50,  48,  -1,  -1],
        [ 51,  49,  -1,  -1],
        [ 52,  50,  -1,  -1],
        [ 53,  51,  -1,  -1],
        [ 54,  52,  -1,  -1],
        [ 55,  53,  -1,  -1],
        [ 56,  54,  -1,  -1],
        [ 57,  55,  -1,  -1],
        [ 58,  56,  -1,  -1],
        [ 59,  57,  -1,  -1],
        [ 60,  58,  -1,  -1],
        [ 61,  59,  -1,  -1],
        [ 62,  60,  -1,  -1],
        [ 63,  61,  -1,  -1],
        [ 64,  62,  -1,  -1],
        [ 65,  63,  -1,  -1],
        [ 66,  64,  -1,  -1],
        [ 67,  65,  -1,  -1],
        [ 68,  66,  -1,  -1],
        [ 69,  67,  -1,  -1],
        [ 70,  68,  -1,  -1],
        [ 71,  69,  -1,  -1],
        [ 72,  70,  -1,  -1],
        [ 73,  71,  -1,  -1],
        [ 74,  72,  -1,  -1],
        [ 75,  73,  -1,  -1],
        [ 76,  74,  -1,  -1],
        [ 77,  75,  -1,  -1],
        [ 78,  76,  -1,  -1],
        [ 79,  77,  -1,  -1],
        [ 80,  78,  -1,  -1],
        [ 81,  79,  -1,  -1],
        [ 82,  80,  -1,  -1],
        [ 83,  81,  -1,  -1],
        [ 84,  82,  -1,  -1],
        [ 85,  83,  -1,  -1],
        [ 86,  84,  -1,  -1],
        [ 87,  85,  -1,  -1],
        [ 88,  86,  -1,  -1],
        [ 89,  87,  -1,  -1],
        [ 90,  88,  -1,  -1],
        [ 91,  89,  -1,  -1],
        [ 92,  90,  -1,  -1],
        [ 93,  91,  -1,  -1],
        [ 94,  92,  -1,  -1],
        [ 95,  93,  -1,  -1],
        [ 96,  94,  -1,  -1],
        [ 97,  95,  -1,  -1],
        [ 98,  96,  -1,  -1],
        [ 99,  97,  -1,  -1],
        [100,  98,  -1,  -1],
        [101,  99,  -1,  -1],
        [102, 100,  -1,  -1],
        [103, 101,  -1,  -1],
        [104, 102,  -1,  -1],
        [105, 103,  -1,  -1],
        [106, 104,  -1,  -1],
        [107, 105,  -1,  -1],
        [ -1, 106,  -1,  -1]]])

In [27]:

    

# http://docs.opencv.org/modules/video/doc/motion_analysis_and_object_tracking.html#backgroundsubtractormog
learning = 0 # 0

history = 0 # 500
varThreshold = 160 # 4.0f * 4.0f ??
bShadowDetection =  False

kernel_size = 20
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(kernel_size,kernel_size))
 


RES_FILE =RESULTS_DIR + "MOG2_history_%d_vtrshould_%r_shadow_detect_%r_learning_%r_opening_kernel_%d.mov" % (history, varThreshold, bShadowDetection, learning, kernel_size)

# open video

video = cv2.VideoCapture()
print ORIGINAL_VIDEO
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), False)

assert res_video.isOpened()

# make bacground video


fgbg = cv2.BackgroundSubtractorMOG2(history, varThreshold, bShadowDetection)
i = 1

while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break

    fgmask = fgbg.apply(frame, learning)
        
    
    clean_frame = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
    res_video.write(clean_frame)
    if frame is None:
        print 'break2 !' , frame
        break

    # cv2.imwrite(r"d:\my\res\fram_%d.jpg" % i, fgmask)
    i = i + 1

video.release()
res_video.release()


    

    




C:\android\android_workspace\tamtam\experiments\videos\tom.mp4
False






    




---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-27-3010f19ee5de> in <module>()
     30 print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height), False)
     31 
---> 32 assert res_video.isOpened()
     33 
     34 # make bacground video

AssertionError: 

In [11]:

    

kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(15,15))
yyy = cv2.morphologyEx(xxx, cv2.MORPH_OPEN, kernel) 
                 

cv2.imwrite(RESULTS_DIR + "opening2.jpg" , yyy)


    

    
Out[11]:





True

In [51]:

    

# http://docs.opencv.org/doc/tutorials/imgproc/histograms/back_projection/back_projection.html#back-projection
RES_FILE =RESULTS_DIR + "back_projection.mov"

# open video

video = cv2.VideoCapture()
video.open(ORIGINAL_VIDEO)
assert video.isOpened(), "failled to open video!"

# open video writer

four_cc = cv2.cv.CV_FOURCC(*'XVID')
fps = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_size = int(video.get(cv2.cv.CV_CAP_PROP_FPS))
frame_width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
frame_height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
res_video = cv2.VideoWriter()
print RES_FILE
print res_video.open(RES_FILE, four_cc, fps, (frame_width, frame_height))

assert res_video.isOpened()


sample = cv2.imread(r"C:\android\android_workspace\tamtam\experiments\videos\hand.jpg")
mask =cv2.imread(r"C:\android\android_workspace\tamtam\experiments\videos\mask.jpg", 0)
hsv = cv2.cvtColor(sample, cv2.cv.CV_BGR2HSV)

roihist = cv2.calcHist([hsv],[0, 1], mask, [180, 256], [0, 180, 0, 256] )
cv2.normalize(roihist,roihist,0,255,cv2.NORM_MINMAX)

i =0
while(1):
    if i % 1000 == 0: print "farme ", i
    ret, frame = video.read()
    if not ret:
        print 'break !' , ret 
        break
        
    hsvt = cv2.cvtColor(frame, cv2.cv.CV_BGR2HSV)

    # normalize histogram and apply backprojection
    dst = cv2.calcBackProject([hsvt],[0,1],roihist,[0,180,0,256],1)

    # Now convolute with circular disc
    disc = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))
    cv2.filter2D(dst,-1,disc,dst)

    # threshold and binary AND
    ret,thresh = cv2.threshold(dst,50,255,0)
    thresh = cv2.merge((thresh,thresh,thresh))
    res = cv2.bitwise_and(frame,thresh)

    res_video.write(res)
    
    i = i + 1

video.release()
res_video.release()


    

    




C:\android\android_workspace\tamtam\experiments\results\samsung-s4-front__back_projection.mov
True
farme  0
break ! False

In [50]:

    

cv2.imread??


    

In [33]:

    

frame= xxx
# hsv_clean = np.array(np.uint)
# hsv_clean = cv2.cv.CreateImage((frame_width, frame_height), 8, 1)
# hsv = cv2.cvtColor(frame, hsv_clean, cv2.cv.CV_BGR2HSV)
hsvt = cv2.cvtColor(frame, cv2.cv.CV_BGR2HSV)

sample = cv2.imread(r"D:\my\tamtam\experiments\results\hand_sample2.png")
hsv = cv2.cvtColor(sample, cv2.cv.CV_BGR2HSV)



# calculating object histogram
roihist = cv2.calcHist([hsv],[0, 1], None, [180, 256], [0, 180, 0, 256] )
 
# normalize histogram and apply backprojection
cv2.normalize(roihist,roihist,0,255,cv2.NORM_MINMAX)
dst = cv2.calcBackProject([hsvt],[0,1],roihist,[0,180,0,256],1)
 
# Now convolute with circular disc
disc = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))
cv2.filter2D(dst,-1,disc,dst)
 
# threshold and binary AND
ret,thresh = cv2.threshold(dst,50,255,0)
thresh = cv2.merge((thresh,thresh,thresh))
res = cv2.bitwise_and(frame,thresh)
 
# res = np.vstack((frame,thresh,res))
cv2.imwrite('res.jpg',res)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-33-415d7411cdaf> in <module>()
----> 1 frame= xxx
      2 # hsv_clean = np.array(np.uint)
      3 # hsv_clean = cv2.cv.CreateImage((frame_width, frame_height), 8, 1)
      4 # hsv = cv2.cvtColor(frame, hsv_clean, cv2.cv.CV_BGR2HSV)
      5 hsvt = cv2.cvtColor(frame, cv2.cv.CV_BGR2HSV)

NameError: name 'xxx' is not defined

In [89]:

    




    

    




[[[101  98 114]
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 [[100  97 113]
  [101  98 114]
  [101  98 114]
  ..., 
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 [[ 98  97 113]
  [ 98  97 113]
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  ..., 
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  [227 216 208]]

 ..., 
 [[184 187 192]
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 [[184 187 192]
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 [[184 187 191]
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  ..., 
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  [176 175 184]]]
D:\my\tamtam\experiments\results\samsung-s3-front__hand_sample.png