Firstly, thank you for sharing your great works and sorry for my poor English.
I have a question about smallimageNet. Pictures pixels are 64*64 ,I change train_imagenet.sh the 19 line's raw_size to 64,then run train_imagenet.sh ,some mistakes happened in follows:
Pre-sized data not found (./data/imagenet64); using original data: ./data/imagenet
Traceback (most recent call last):
File "train_gan.py", line 262, in
dataset = data.Dataset(args)
File "/home/hddsj/bigan-master/data.py", line 453, in init
max_images=args.max_images)
File "/home/hddsj/bigan-master/data.py", line 210, in imagenet_data_providers
assert 0 <= num_test <= len(data['val'])
AssertionError
Then run resize_imageset.py some errors appears,in follows:
usage: resize_imageset.py [-h] [-c] [-f FORMAT] [-q] [-j JOBS] [-r] [-o]
size input_directory output_directory
resize_imageset.py: error: too few arguments
How can I input these arguments ???
What does the following code in Readme mean ???
SIZE=72 # or SIZE=128 for generalized BiGAN experiments
Firstly, thank you for sharing your great works and sorry for my poor English.
I have a question about smallimageNet. Pictures pixels are 64*64 ,I change train_imagenet.sh the 19 line's raw_size to 64,then run train_imagenet.sh ,some mistakes happened in follows: Pre-sized data not found (./data/imagenet64); using original data: ./data/imagenet Traceback (most recent call last): File "train_gan.py", line 262, in
dataset = data.Dataset(args)
File "/home/hddsj/bigan-master/data.py", line 453, in init
max_images=args.max_images)
File "/home/hddsj/bigan-master/data.py", line 210, in imagenet_data_providers
assert 0 <= num_test <= len(data['val'])
AssertionError
Then run resize_imageset.py some errors appears,in follows:
usage: resize_imageset.py [-h] [-c] [-f FORMAT] [-q] [-j JOBS] [-r] [-o]
size input_directory output_directory
resize_imageset.py: error: too few arguments
How can I input these arguments ???
What does the following code in Readme mean ??? SIZE=72 # or SIZE=128 for generalized BiGAN experiments
"-j 4" uses 4 resizing processes
python resize_imageset.py -r -j 4 ${SIZE} ./data/imagenet ./data/imagenet${SIZE}