Compute metrics for each class

[delhomer]

Metrics (accuracy, IoU, dice_coef) are currently computed for the whole images, without any distinction between classes. To gain on description quality, and be able to compare with state-of-the-art results and contest leaderboards (see Mapillary, CityScapes, or AerialImage examples), we should add class-specific metric results in training_metrics.csv.

It should be interesting to add the best instance metrics in the best-instance-<img_size>-<aggregation>.json file (produced by paramoptim.py when exploring hyperparameters) as well.