  We apply Faster R-CNN to the detection of characters in namecard, in order to
solve the problem of a small amount of data and the inbalance between different
class, we designed the data augmentation and the 'fake' data generalizer to
generate more data for the training of network. Without using data
augmentation, the average IoU in correct samples could be no less than 80% and
the mAP result of 80% was also achieved with Faster R-CNN. By applying the data
augmentation, the variance of mAP is decreased and both of the IoU and mAP
score has increased a little.
