Arnab Mondal comments

Results 7 comments of


                                            Arnab Mondal

Incorporate into related toolkits

Thanks a lot for your suggestion. We are looking forward to doing something similar.

Incorporate into related toolkits

Hi, What I meant is that at some point we will consider integrating the code in those toolkits.

Use which command to test the proposed model? I thibk there are some fauts in the text. It should be $ python main.py --testing not $ python main_unet.py --testing, is it right?

Thanks a lot for pointing that out. I have fixed it.

I appreciate this is a great work, I'd like to konw what data used to train the model? 1 labeled subject and another one unlabeled subject, is it right? and the unlabeled subject also used to train the GAN?

The link to the dataset has been given in the dataset section of the readme file. The unlabeled data is used to train using the adversarial part of the loss.

when I 'run main.py --testing' have some errors FailedPreconditionError (see above for traceback): Attempting to use uninitialized value D/d_up3_deconv/g [[node D/d_up3_deconv/g/read (defined at ../lib/operations.py:87) = Identity[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"](D/d_up3_deconv/g)]] [[{{node ArgMax/_3}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_491_ArgMax", tensor_type=DT_INT64, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

Hi, Firstly, I would request you not to open a new issue everytime you face a problem. You can continue posting on the same issue with new comments. Also please...

how to train the model on CPU ??

I hope you have figured out by now. You can do it using gpu_ids = ''(an empty string). Sorry for not getting back earlier. I'll also try to provide a...

RuntimeError: Given groups=1, weight of size [64, 1, 7, 7], expected input[5, 64, 70, 70] to have 1 channels, but got 64 channels instead

Hi, It seems like your number of input channels doesn't match with the convolution filter you defined. Try to match the input channels with the channels you defined in the...