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fix random_flip setting #30
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parser.add_argument('--random_flip', default=True, type=bool,
help='if horizontally flip images when training')
as new script's line 252
parser.add_argument('--random_flip', default=True, type=lambda x:bool(strtobool(x)),
help='if horizontally flip images when training')
let it be available to set bool option in .sh
wudonghao
commented
May 9, 2018
I CAN'T RUN IT FOR
File "train.py", line 314, in
main(args)
File "train.py", line 200, in main
train(segmentation_module, iterator_train, optimizers, history, epoch, args)
File "train.py", line 37, in train
loss, acc = segmentation_module(batch_data)
File "/home/wdh/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, **kwargs)
File "/home/wdh/PycharmProjects/Semantic Segmentation/pytorch-semantic-segmentation-master by hangzhaomit/models/models.py", line 34, in forward
pred = self.decoder(self.encoder(feed_dict['img_data'], return_feature_maps=True))
TypeError: list indices must be integers or slices, not str
shlykov2
commented
Mar 25, 2019
I CAN'T RUN IT FOR
File "train.py", line 314, in
main(args)
File "train.py", line 200, in main
train(segmentation_module, iterator_train, optimizers, history, epoch, args)
File "train.py", line 37, in train
loss, acc = segmentation_module(batch_data)
File "/home/wdh/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, **kwargs)
File "/home/wdh/PycharmProjects/Semantic Segmentation/pytorch-semantic-segmentation-master by hangzhaomit/models/models.py", line 34, in forward
pred = self.decoder(self.encoder(feed_dict['img_data'], return_feature_maps=True))
TypeError: list indices must be integers or slices, not str
had the same issue, fixed with adding "feed_dict = feed_dict[0]" at the start of forward function in SegmentationModule class in models.py. Could please some1 tell me whether it spoils the training?
wjqqy
commented
Apr 25, 2019
i also meet the problem,but i fix the feed_dict['img_data'] to feed_dict[0]['img_data']
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parser.add_argument('--random_flip', default=True, type=bool,
help='if horizontally flip images when training')
random_flip will always be True, although we run 'python train.py --random_flip False'