data_iterators.py 文件源码

def generate(self):

        for pid in self.id2candidates_path.iterkeys():
            patient_path = self.id2patient_path[pid]
            print pid, patient_path
            img, pixel_spacing = utils_lung.read_dicom_scan(patient_path)

            print self.id2candidates_path[pid]
            candidates = utils.load_pkl(self.id2candidates_path[pid])
            print candidates.shape
            for candidate in candidates:
                y_batch = np.array(candidate, dtype='float32')
                patch_center = candidate[:3]
                batch = []
                for i in range(self.tta):
                    batch.append(np.float32(self.data_prep_fun(data=img,
                                                        patch_center=patch_center,
                                                        pixel_spacing=pixel_spacing)))
                x_batch = np.stack(batch)
                print x_batch.shape

                yield x_batch, y_batch, [pid]