def step(self):
self.dev.Read()
if (self.yuv):
y=numpy.ndarray(shape=(self.h,self.w),
buffer=self.dev.buffer,dtype=numpy.uint8).copy()
off=self.h*self.w
len=(self.h//2)*(self.w//2)
u=numpy.ndarray(shape=(self.h//2,self.w//2),
buffer=self.dev.buffer[off:off+len],dtype=numpy.uint8)
v=numpy.ndarray(shape=(self.h//2,self.w//2),
buffer=self.dev.buffer[off+len:],dtype=numpy.uint8)
for yy in range(self.h):
for xx in range(self.w):
vv=y[yy,xx]
self.img[yy,xx,0]=vv
self.img[yy,xx,1]=vv
self.img[yy,xx,2]=vv
else:
self.img=numpy.ndarray(shape=(self.h,self.w,self.nc),
buffer=self.dev.buffer,dtype=numpy.uint8)
if (self.bgr):
rgb2bgr(self.img)
if (self.observer):
self.observer(self.img.copy())
return True
def step(self):
frame = highgui.cvQueryFrame(self.capture)
img = Ipl2NumPyFast(frame)
if self.bgr:
# zs=img.shape
# img=numpy.array(zip(img[:,:,2].flat,img[:,:,1].flat,img[:,:,0].flat)) ## slow !!!
rgb2bgr(img) # let use cython
# img.shape=zs
if self.obs:
self.obs(img)
return True
def __getitem__(self, x):
frame = highgui.cvQueryFrame(self.capture)
img = Ipl2NumPyFast(frame)
if self.bgr:
rgb2bgr(img)
return img
