get_imdisp = lambda ax: ax.get_images()[0]
fig, axes = plt.subplots(1,2)
axes = dict(zip(['raw','skin'],axes.ravel()))
for k,ax in axes.items(): ax.set_title(k)
cap = FrameBuffer.from_argv()
curr = cap.read()
axes['raw'].imshow(curr)
axes['skin'].imshow(curr,cmap=mpl.cm.get_cmap('gray'))
fig.tight_layout()
hdetect = ConvexityHandDetector()
smseg = GaussianSkinSegmenter()
app = VideoApp(fig,cap)
fig.show()
while app:
curr = blur(cap.read())
dispimg = curr.copy()
mask = smseg(curr)
detected = hdetect(mask)
if detected:
hull_pts = hdetect.hull
com = (np.sum(hull_pts[:,0,:],axis=0,dtype=float)/len(hull_pts)).astype(int)
cv2.circle(dispimg,tuple(com),5,color=(0,255,0),thickness=-1)
color = (255,0,0) if detected else (0,0,255)
cv2.drawContours(dispimg,[hdetect.hull],0,color,3)
