def evaluation_RBM(self, dr, scale, k):
rbm = RBM(self.layers[k], self.layers[k+1], self.weightLayers[k], 0)
for i in range(scale):
im = dr.readOne(i)
for p in range(len(im)):
if im[p] >= 128:
rbm.v_layer.outs[p] = 1.0
else:
rbm.v_layer.outs[p] = 0.0
rbm.update_total_error()
#just for testing
size = [28, 28]
image = Image.new("L", size)
for p in range(len(self.layers[k].outs)):
if self.layers[k].outs[p] == 1.0:
image.putpixel([p%28, p/28], 255)
else:
image.putpixel([p%28, p/28], 0)
image.show()
rbm.print_average_error(k)
