covidprognosis/data/chexpert.py [131:145]:
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        image = self.open_image(filename)

        metadata = self.retrieve_metadata(idx, filename, exam)

        # retrieve labels while handling missing ones for combined data loader
        labels = np.array(exam.reindex(self.label_list)[self.label_list]).astype(
            np.float
        )

        sample = {"image": image, "labels": labels, "metadata": metadata}

        if self.transform is not None:
            sample = self.transform(sample)

        return sample
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covidprognosis/data/mimic_cxr.py [162:176]:
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        image = self.open_image(filename)

        metadata = self.retrieve_metadata(idx, filename, exam)

        # retrieve labels while handling missing ones for combined data loader
        labels = np.array(exam.reindex(self.label_list)[self.label_list]).astype(
            np.float
        )

        sample = {"image": image, "labels": labels, "metadata": metadata}

        if self.transform is not None:
            sample = self.transform(sample)

        return sample
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