def draw_conv_series(self, x, shape=None): x = np.array(x) for xx in x: VisUtil.show_img(VisUtil.trans_img(xx, shape), "Original") for i, (layer, ac) in enumerate( zip( self._layers, self._get_acts( np.array([xx.transpose(1, 2, 0)], dtype=np.float32)))): if len(ac.shape) == 4: VisUtil.show_batch_img( ac[0].transpose(2, 0, 1), "Layer {} ({})".format(i + 1, layer.name)) else: ac = ac[0] length = sqrt(np.prod(ac.shape)) if length < 10: continue (height, width) = xx.shape[1:] if shape is None else shape[1:] sqrt_shape = sqrt(height * width) oh, ow = int(length * height / sqrt_shape), int( length * width / sqrt_shape) VisUtil.show_img(ac[:oh * ow].reshape(oh, ow), "Layer {} ({})".format(i + 1, layer.name))
def draw_conv_weights(self): with self._sess.as_default(): for i, (name, weight) in enumerate(zip(self.layer_names, self._tf_weights)): weight = weight.eval() if len(weight.shape) != 4: continue for j, _w in enumerate(weight.transpose(2, 3, 0, 1)): VisUtil.show_batch_img(_w, "{} {} filter {}".format(name, i + 1, j + 1))
def draw_conv_weights(self): with self._sess.as_default(): for i, (name, weight) in enumerate(zip(self.layer_names, self._tf_weights)): weight = weight.eval() if len(weight.shape) != 4: continue for j, _w in enumerate(weight.transpose(2, 3, 0, 1)): VisUtil.show_batch_img(_w, "{} {} filter {}".format(name, i + 1, j + 1))
def draw_conv_series(self, x, shape=None): x = np.asarray(x) for xx in x: VisUtil.show_img(VisUtil.trans_img(xx, shape), "Original") for i, (layer, ac) in enumerate(zip( self._layers, self._get_acts(np.array([xx.transpose(1, 2, 0)], dtype=np.float32)))): if len(ac.shape) == 4: VisUtil.show_batch_img(ac[0].transpose(2, 0, 1), "Layer {} ({})".format(i + 1, layer.name)) else: ac = ac[0] length = sqrt(np.prod(ac.shape)) if length < 10: continue (height, width) = xx.shape[1:] if shape is None else shape[1:] sqrt_shape = sqrt(height * width) oh, ow = int(length * height / sqrt_shape), int(length * width / sqrt_shape) VisUtil.show_img(ac[:oh * ow].reshape(oh, ow), "Layer {} ({})".format(i + 1, layer.name))