Append 0 to default label names for single digit labels.

The default label names for the first 10 labels are (1-9). However, they should be (00, 01, ... 09). Otherwise, when dlib reads the XML files and reorders the labels in ascending order the labels get messed up. For instance, 13 labels from (0-12) are mapped like the following by dlib before training. The right column is the original label and order of the landmarks in the .XML files. The left column is how the dlib training code perceives as their order. For example, the original 10th point is mapped to the 2nd point, the original 11th to 3rd etc. This results due to the missing 0 in front of 0-9 labels.

I used 10 images as both training and testing dataset. I achieved zero MAE on both testings and training. However, the order of the landmarks was all messed up. As I was getting 0 MAE that means the problem was happening with the XML reader of the dlib training functions.

I manually added the 0s to the labels and then the training was correct.
I know I can just manually add the 0s when labelling images using the tool. However, when going for thousands of images, this is a very unnecessary waste of time. I might for now write an XML parser script that will append the zeros.

To Reproduce
Steps to reproduce the behavior:

1. Label a few images with the default labels. Use around 15 labels. Use the same images for training and testing.
2. Train a shape predictor using http://dlib.net/train_shape_predictor.py.html
3. Get zero MAE on both training and testing as we are just testing an overfitted model.
4. See that the correct key points were detected but the ordering of the landmarks are messed up.

Screenshots
Ground truth:

Predicted Landmarks:

But MAE was zero. So that means DLIB is reordering the landmarks after reading. And then using that sorted list as the new ground truth order of the landmarks.

Start in the image-labeling tool's default-label generation and reproduce the issue with around 15 labels, then inspect the XML consumed by train_shape_predictor.py. Done means single-digit default labels are written as 00 through 09 and landmark ordering remains correct when the XML is read for training.