from SimpleCV import Camera, Image, Color, TemporalColorTracker, ROI, Display
import matplotlib.pyplot as plt
cam = Camera(1)
tct = TemporalColorTracker()
img = cam.getImage()
roi = ROI(img.width * 0.45, img.height * 0.45, img.width * 0.1,
img.height * 0.1, img)
tct.train(cam, roi=roi, maxFrames=250, pkWndw=20)
# Matplot Lib example plotting
plotc = {'r': 'r', 'g': 'g', 'b': 'b', 'i': 'm', 'h': 'y'}
for key in list(tct.data.keys()):
plt.plot(tct.data[key], plotc[key])
for pt in tct.peaks[key]:
plt.plot(pt[0], pt[1], 'r*')
for pt in tct.valleys[key]:
plt.plot(pt[0], pt[1], 'b*')
plt.grid()
plt.show()
disp = Display((800, 600))
while disp.isNotDone():
img = cam.getImage()
result = tct.recognize(img)
plt.plot(tct._rtData, 'r-')
plt.grid()
plt.savefig('temp.png')
plt.clf()
plotImg = Image('temp.png')
negTotal = 0
negcount = 5
negdir = './negs/'
if not os.path.exists(negdir):
os.mkdir(negdir)
disp = Display()
iset = ImageSet('data')
for img in iset:
img.save(disp)
face = img.findHaarFeatures('face.xml')
if( face is not None and len(face) > 0 ):
face[-1].draw(width=3)
img.applyLayers().save(disp)
fname = outdir + 'Face' + str(count)+'.png'
face[-1].crop().resize(sz,sz).toGray().save(fname)
print "Saving: " + fname
count = count + 1
ncount = 0
while ncount < negcount:
pt = 256*np.random.rand(1,2)
roi = ROI(np.round((img.width-sz)*np.random.rand(1))[0],np.round((img.height-sz)*np.random.rand(1))[0],sz,sz,img)
#print roi.toXYWH()
if( not face[-1].overlaps(roi) ):
#roi.draw(width=3)
#img.applyLayers().save(disp)
fname = negdir+"Neg"+str(negTotal)+".png"
roi.crop().toGray().save(fname)
ncount += 1
negTotal += 1
from SimpleCV import Camera, Image, Color, TemporalColorTracker, ROI, Display
import matplotlib.pyplot as plt
cam = Camera(1)
tct = TemporalColorTracker()
img = cam.getImage()
roi = ROI(img.width*0.45,img.height*0.45,img.width*0.1,img.height*0.1,img)
tct.train(cam,roi=roi,maxFrames=250,pkWndw=20)
# Matplot Lib example plotting
plotc = {'r':'r','g':'g','b':'b','i':'m','h':'y'}
for key in tct.data.keys():
plt.plot(tct.data[key],plotc[key])
for pt in tct.peaks[key]:
plt.plot(pt[0],pt[1],'r*')
for pt in tct.valleys[key]:
plt.plot(pt[0],pt[1],'b*')
plt.grid()
plt.show()
disp = Display((800,600))
while disp.isNotDone():
img = cam.getImage()
result = tct.recognize(img)
plt.plot(tct._rtData,'r-')
plt.grid()
plt.savefig('temp.png')
plt.clf()
plotImg = Image('temp.png')
roi = ROI(img.width*0.45,img.height*0.45,img.width*0.1,img.height*0.1,img)
if not os.path.exists(negdir):
os.mkdir(negdir)
disp = Display()
iset = ImageSet('data')
for img in iset:
img.save(disp)
face = img.findHaarFeatures('face.xml')
if (face is not None and len(face) > 0):
face[-1].draw(width=3)
img.applyLayers().save(disp)
fname = outdir + 'Face' + str(count) + '.png'
face[-1].crop().resize(sz, sz).toGray().save(fname)
print "Saving: " + fname
count = count + 1
ncount = 0
while ncount < negcount:
pt = 256 * np.random.rand(1, 2)
roi = ROI(
np.round((img.width - sz) * np.random.rand(1))[0],
np.round((img.height - sz) * np.random.rand(1))[0], sz, sz,
img)
#print roi.toXYWH()
if (not face[-1].overlaps(roi)):
#roi.draw(width=3)
#img.applyLayers().save(disp)
fname = negdir + "Neg" + str(negTotal) + ".png"
roi.crop().toGray().save(fname)
ncount += 1
negTotal += 1
