Utils.py 文件源码

def adjust_prediction(self, probability, image):
        crf = dcrf.DenseCRF(np.prod(probability.shape), 2)
        # crf = dcrf.DenseCRF(np.prod(probability.shape), 1)

        binary_prob = np.stack((1 - probability, probability), axis=0)
        unary = unary_from_softmax(binary_prob)
        # unary = unary_from_softmax(np.expand_dims(probability, axis=0))
        crf.setUnaryEnergy(unary)

        # per dimension scale factors
        sdims = [self.sdims] * 3
        smooth = create_pairwise_gaussian(sdims=sdims, shape=probability.shape)
        crf.addPairwiseEnergy(smooth, compat=2)

        if self.schan:
            # per channel scale factors
            schan = [self.schan] * 6
            appearance = create_pairwise_bilateral(sdims=sdims, schan=schan, img=image, chdim=3)
            crf.addPairwiseEnergy(appearance, compat=2)

        result = crf.inference(self.iter)
        crf_prediction = np.argmax(result, axis=0).reshape(probability.shape).astype(np.float32)

        return crf_prediction