rle_ensemble_loader.py 文件源码

def __getitem__(self, idx):

        img_name = self.img_names[idx]

        ensembled_mask = np.zeros((const.img_size[0], const.img_size[1]))

        for i, submission in enumerate(self.submissions):

            rle = submission[img_name]
            mask = run_length.decode(rle)
            weighted_mask = np.multiply(mask, self.weights[i])
            ensembled_mask = np.add(ensembled_mask, weighted_mask)

        ensembled_mask[ ensembled_mask > 0.5 ] = 1
        ensembled_mask[ ensembled_mask <= 0.5 ] = 0

        # plt.imshow(ensembled_mask)
        # plt.show()

        ensembled_rle = run_length.encode(ensembled_mask)

        return img_name, ensembled_rle