def set_img(self, img):
"""
read an rgb image, set the gpu copy to be the lab image
"""
if img.shape[0] != self.dimy or img.shape[1] != self.dimx:
raise ValueError(img.shape, self.dimy, self.dimx)
if img.ndim == 1:
nChannels = 1
isNaN = np.isnan(img)
elif img.ndim == 3:
nChannels = 3
img_isNaN_r = np.isnan(img[:, :, 0])
img_isNaN_g = np.isnan(img[:, :, 1])
img_isNaN_b = np.isnan(img[:, :, 2])
isNaN = np.logical_or(img_isNaN_r, np.logical_or(img_isNaN_g, img_isNaN_b))
else:
raise NotImplementedError()
self.img = CpuGpuArray(arr=img)
self.img_isNaN = CpuGpuArray(arr=isNaN)
print('self.img', self.img)
print('self.img_isNaN', self.img_isNaN)
if nChannels == 3:
rgb_to_lab(img_gpu=self.img.gpu)
def set_img(self,img):
"""
read an rgb image, set the gpu copy to be the lab image
"""
if img.shape[0] != self.dimy or img.shape[1] != self.dimx:
raise ValueError(img.shape,self.dimy,self.dimx)
if img.ndim == 1:
nChannels = 1
isNaN = np.isnan( img)
elif img.ndim == 3:
nChannels = 3
img_isNaN_r = np.isnan( img[:,:,0] )
img_isNaN_g = np.isnan( img[:,:,1] )
img_isNaN_b = np.isnan( img[:,:,2] )
isNaN = np.logical_or(img_isNaN_r, np.logical_or(img_isNaN_g,img_isNaN_b))
else:
raise NotImplementedError(nChannels)
self.img = CpuGpuArray(arr=img)
self.img_isNaN = CpuGpuArray(arr=isNaN)
print 'self.img',self.img
print 'self.img_isNaN',self.img_isNaN
if nChannels==3:
rgb_to_lab(img_gpu=self.img.gpu)
def set_img(self, img):
"""
read an rgb image, set the gpu copy to be the lab image
"""
if img.shape[0] != self.dimy or img.shape[1] != self.dimx:
raise ValueError(img.shape, self.dimy, self.dimx)
if img.ndim == 2:
nChannels = 1
elif img.ndim == 3:
nChannels = 3
else:
raise NotImplementedError(nChannels)
self.img = CpuGpuArray(arr=img.astype(np.float))
if nChannels == 3:
rgb_to_lab(img_gpu=self.img.gpu)
def set_img(self,img):
"""
read an rgb image, set the gpu copy to be the lab image
"""
if img.shape[0] != self.dimy or img.shape[1] != self.dimx:
raise ValueError(img.shape,self.dimy,self.dimx)
if img.ndim == 2:
nChannels = 1
elif img.ndim == 3:
nChannels = 3
else:
raise NotImplementedError(nChannels)
self.img = CpuGpuArray(arr=img.astype(np.float))
if nChannels==3:
rgb_to_lab(img_gpu=self.img.gpu)
