| 6 | from common.generator import ChunkedGenerator |
| 7 | |
| 8 | class Fusion_3dhp(data.Dataset): |
| 9 | def __init__(self, opt, dataset, root_path, train=True): |
| 10 | |
| 11 | self.opt = opt |
| 12 | self.data_type = opt.dataset |
| 13 | self.train = train |
| 14 | self.keypoints_name = opt.keypoints |
| 15 | self.root_path = root_path |
| 16 | |
| 17 | self.train_list = opt.subjects_train.split(',') |
| 18 | self.test_list = opt.subjects_test.split(',') |
| 19 | self.action_filter = None if opt.actions == '*' else opt.actions.split(',') |
| 20 | self.downsample = opt.downsample |
| 21 | self.subset = opt.subset |
| 22 | self.stride = opt.stride |
| 23 | self.crop_uv = opt.crop_uv |
| 24 | self.test_aug = opt.test_augmentation |
| 25 | self.pad = opt.pad |
| 26 | if self.train: |
| 27 | self.keypoints, self.keypoints_GT = self.prepare_data(dataset, self.train_list) |
| 28 | self.cameras_train, self.poses_train, self.poses_train_2d, self.poses_train_2d_GT = \ |
| 29 | self.fetch(dataset, self.train_list, subset=self.subset) |
| 30 | self.generator = ChunkedGenerator(opt.batch_size, self.cameras_train, self.poses_train, |
| 31 | self.poses_train_2d, self.poses_train_2d_GT, |
| 32 | self.stride, pad=self.pad, |
| 33 | augment=opt.data_augmentation, |
| 34 | reverse_aug=opt.reverse_augmentation, |
| 35 | kps_left=self.kps_left, kps_right=self.kps_right, |
| 36 | joints_left=self.joints_left, |
| 37 | joints_right=self.joints_right, out_all=opt.out_all) |
| 38 | print('Training on {} frames'.format(self.generator.num_frames())) |
| 39 | else: |
| 40 | self.keypoints, self.keypoints_GT = self.prepare_data(dataset, self.test_list) |
| 41 | self.cameras_test, self.poses_test, self.poses_test_2d, self.poses_test_2d_GT = \ |
| 42 | self.fetch(dataset, self.test_list, subset=self.subset) |
| 43 | self.generator = ChunkedGenerator(opt.batch_size, self.cameras_test, self.poses_test, |
| 44 | self.poses_test_2d, self.poses_test_2d_GT, self.stride, |
| 45 | pad=self.pad, augment=False, kps_left=self.kps_left, |
| 46 | kps_right=self.kps_right, joints_left=self.joints_left, |
| 47 | joints_right=self.joints_right, out_all=opt.out_all) |
| 48 | self.key_index = self.generator.saved_index |
| 49 | print('Testing on {} frames'.format(self.generator.num_frames())) |
| 50 | |
| 51 | def prepare_data(self, dataset, folder_list): |
| 52 | for subject in folder_list: |
| 53 | for action in dataset[subject].keys(): |
| 54 | anim = dataset[subject][action] |
| 55 | |
| 56 | positions_3d = [] |
| 57 | for i in range(len(anim['positions'])): |
| 58 | pos_3d = anim['positions'][i] |
| 59 | |
| 60 | pos_3d[:, 1:] -= pos_3d[:, :1] |
| 61 | |
| 62 | positions_3d.append(pos_3d) |
| 63 | anim['positions_3d'] = positions_3d |
| 64 | |
| 65 | keypoints_pth = self.root_path + 'data_2d_' + self.data_type + '.npz' |