| | |
|---|
| | | |
|---|
| | | # We get the pose in radians |
|---|
| | | pose = utils.get_ypr_from_mat(os.path.join(self.data_dir, self.y_train[index] + self.annot_ext)) |
|---|
| | | # And convert to positive degrees. |
|---|
| | | pose = pose * 180 / np.pi + 90 |
|---|
| | | # And convert to degrees. |
|---|
| | | pitch = pose[0] * 180 / np.pi |
|---|
| | | yaw = pose[1] * 180 / np.pi |
|---|
| | | roll = pose[2] * 180 / np.pi |
|---|
| | | # Bin values |
|---|
| | | bins = np.array(range(-99, 102, 3)) |
|---|
| | | labels = torch.LongTensor(np.digitize([yaw, pitch, roll], bins) - 1) |
|---|
| | | |
|---|
| | | label = torch.FloatTensor(pose) |
|---|
| | | if self.transform is not None: |
|---|
| | | img = self.transform(img) |
|---|
| | | |
|---|
| | | return img, labels, self.X_train[index] |
|---|
| | | |
|---|
| | | def __len__(self): |
|---|
| | | # 122,450 |
|---|
| | | return self.length |
|---|
| | | |
|---|
| | | class AFLW2000_binned(Dataset): |
|---|
| | | def __init__(self, data_dir, filename_path, transform, img_ext='.jpg', annot_ext='.mat'): |
|---|
| | | self.data_dir = data_dir |
|---|
| | | self.transform = transform |
|---|
| | | self.img_ext = img_ext |
|---|
| | | self.annot_ext = annot_ext |
|---|
| | | |
|---|
| | | filename_list = get_list_from_filenames(filename_path) |
|---|
| | | |
|---|
| | | self.X_train = filename_list |
|---|
| | | self.y_train = filename_list |
|---|
| | | self.length = len(filename_list) |
|---|
| | | |
|---|
| | | def __getitem__(self, index): |
|---|
| | | img = Image.open(os.path.join(self.data_dir, self.X_train[index] + self.img_ext)) |
|---|
| | | img = img.convert('RGB') |
|---|
| | | |
|---|
| | | # We get the pose in radians |
|---|
| | | pose = utils.get_ypr_from_mat(os.path.join(self.data_dir, self.y_train[index] + self.annot_ext)) |
|---|
| | | # And convert to degrees. |
|---|
| | | pitch, yaw, roll = pose * 180 / np.pi |
|---|
| | | # Bin values |
|---|
| | | bins = np.array(range(-99, 102, 3)) |
|---|
| | | binned_pitch = torch.DoubleTensor(np.digitize(pitch, bins) - 1) |
|---|
| | | binned_yaw = torch.DoubleTensor(np.digitize(yaw, bins) - 1) |
|---|
| | | binned_roll = torch.DoubleTensor(np.digitize(roll, bins) - 1) |
|---|
| | | |
|---|
| | | label = binned_yaw, binned_pitch, binned_roll |
|---|
| | | |
|---|
| | | if self.transform is not None: |
|---|
| | | img = self.transform(img) |
|---|
| | |
|---|
| | | return img, label, self.X_train[index] |
|---|
| | | |
|---|
| | | def __len__(self): |
|---|
| | | # 122,450 |
|---|
| | | # 2,000 |
|---|
| | | return self.length |
|---|
| | | |
|---|
| | | def get_list_from_filenames(file_path): |
|---|
