mazcallu

shouldn´t it be this instead? Labels are contained in y_ and logits are the output from the neural net presence_loss = tf.nn.sigmoid_cross_entropy_with_logits(labels=y_[:, :1], logits= y[:, :1])

I get a detection rate in videos that vary from 50% to 90%, I fine tuned the algorithm for detecting european plates in specific conditions, the detection can also be...

Hi Abduoit, I think that is only for the doreport when printing out the labeled license plates and the predictions in any case since batch_size = 50 your two lines...

Please refer to this tutorial in order to understand how a similar program to train.py works: https://pythonprogramming.net/tensorflow-neural-network-session-machine-learning-tutorial/ Once you understand this completely, go back to train.py and you should understand...

Images are generated on the fly so there is no need for that, the number of images is unlimited

The image is too small or too big in both cases, that is why it is p = 0 in all of them

I think there is an error with the get_loss function: def get_loss(y, y_): # Calculate the loss from digits being incorrect. Don't count loss from # digits that are in...