Method next_batch_test

misc/datasets.py:166–198

Return the next `batch_size` examples from this data set.

(self, batch_size, start, max_captions)

        return ret_list

    def next_batch_test(self, batch_size, start, max_captions):
        """Return the next `batch_size` examples from this data set."""
        if (start + batch_size) > self._num_examples:
            end = self._num_examples
            start = end - batch_size
        else:
            end = start + batch_size

        sampled_images = self._images[start:end]
        sampled_images = sampled_images.astype(np.float32)
        # from [0, 255] to [-1.0, 1.0]
        sampled_images = sampled_images * (2. / 255) - 1.
        sampled_images = self.transform(sampled_images)

        sampled_embeddings = self._embeddings[start:end]
        _, embedding_num, _ = sampled_embeddings.shape
        sampled_embeddings_batchs = []

        sampled_captions = []
        sampled_filenames = self._filenames[start:end]
        sampled_class_id = self._class_id[start:end]
        for i in range(len(sampled_filenames)):
            captions = self.readCaptions(sampled_filenames[i],
                                         sampled_class_id[i])
            # print(captions)
            sampled_captions.append(captions)

        for i in range(np.minimum(max_captions, embedding_num)):
            batch = sampled_embeddings[:, i, :]
            sampled_embeddings_batchs.append(np.squeeze(batch))

        return [sampled_images, sampled_embeddings_batchs,
                self._saveIDs[start:end], sampled_captions]


class TextDataset(object):