Runtime Error Warning

[clu5]

MacBook-Pro:deconvfaces-master CJL$ python faces.py train grey_scaled/ Using TensorFlow backend. Found 0 instances with 0 identities (5, 4) height: 5 width: 4 Built model with: Deconv layers: 5 Output shape: (320, 256, 3) Loading data... 0it [00:00, ?it/s] Training... Epoch 1/100 /Users/CJL/anaconda/lib/python3.5/site-packages/keras/callbacks.py:286: RuntimeWarning: Can save best model only with loss available, skipping. 'skipping.' % (self.monitor), RuntimeWarning) /Users/CJL/anaconda/lib/python3.5/site-packages/keras/callbacks.py:370: RuntimeWarning: Early stopping requires loss available! (self.monitor), RuntimeWarning) Traceback (most recent call last): File "faces.py", line 127, in <module> cmd() File "faces.py", line 65, in train verbose = True, File "/Users/CJL/Downloads/deconvfaces-master/faces/train.py", line 182, in train_model callbacks=callbacks, shuffle=True, verbose=1) File "/Users/CJL/anaconda/lib/python3.5/site-packages/keras/engine/training.py", line 1124, in fit callback_metrics=callback_metrics) File "/Users/CJL/anaconda/lib/python3.5/site-packages/keras/engine/training.py", line 862, in _fit_loop callbacks.on_epoch_end(epoch, epoch_logs) File "/Users/CJL/anaconda/lib/python3.5/site-packages/keras/callbacks.py", line 42, in on_epoch_end callback.on_epoch_end(epoch, logs) File "/Users/CJL/anaconda/lib/python3.5/site-packages/keras/callbacks.py", line 372, in on_epoch_end if self.monitor_op(current - self.min_delta, self.best): TypeError: unsupported operand type(s) for -: 'NoneType' and 'int'

I am using a folder of PNG files and getting this error during training. What kinds of image files does it use? How much images did you use to train?

[flynnmd]

Hmm that's odd...

1. It says it found 0 instances and 0 identities -- which dataset are you using? This only supports RaFD and Yale Faces (the latter you need to give a flag when you run it, see which with python3 faces.py train -h)
2. Which version of Keras are you using? It looks like the model compiled without monitoring the loss (which it should by default), but the callbacks I use to save the model and stop it early need it to work.

[nmgzjf]

@clu2033 @zo7 I guess clu2033 use early_stopping in a merge model. It seems that Keras does not provide val_acc and val_loss in merge model, so the monitor only can be set to acc or loss. So if merge model is adopted, please modify the value of monitor.