Classifier¶
PixelwiseSoftmaxClassifier¶
-
class
chainercv.links.
PixelwiseSoftmaxClassifier
(predictor, ignore_label=-1, class_weight=None)[source]¶ A pixel-wise classifier.
It computes the loss based on a given input/label pair for semantic segmentation.
Parameters: - predictor (Link) – Predictor network.
- ignore_label (int) – A class id that is going to be ignored in evaluation. The default value is -1.
- class_weight (array) – An array
that contains constant weights that will be multiplied with the
loss values along with the channel dimension. This will be
used in
chainer.functions.softmax_cross_entropy()
.
-
__call__
(x, t)[source]¶ Computes the loss value for an image and label pair.
Parameters: - x (Variable) – A variable with a batch of images.
- t (Variable) – A variable with the ground truth image-wise label.
Returns: Loss value.
Return type: Variable
-
to_cpu
()[source]¶ Copies parameter variables and persistent values to CPU.
This method does not handle non-registered attributes. If some of such attributes must be copied to CPU, the link implementation must override this method to do so.
Returns: self
-
to_gpu
(device=None)[source]¶ Copies parameter variables and persistent values to GPU.
This method does not handle non-registered attributes. If some of such attributes must be copied to GPU, the link implementation must override this method to do so.
Parameters: device – Target device specifier. If omitted, the current device is used. Returns: self