Closed ghost closed 5 years ago
Hi @reaktr4 Could you share the solution?I also encounter this issue. Thank you.
Hi @reaktr4 Could you share the solution?I also encounter this issue. Thank you.
Hi @keishatsai I solved it by specifying n_workers under the training section of the yaml file. Here is the sample config
model:
arch: icnet
data:
dataset: cityscapes
train_split: train
val_split: val
img_rows: 512
img_cols: 1024
path: D:\Workspace\datasets\nn\cityscapes
training:
train_iters: 85000
batch_size: 2
n_workers: 2 # a sample value
val_interval: 500
print_interval: 25
optimizer:
lr: 1.0e-2
l_rate: 1.0e-2
l_schedule:
momentum: 0.99
weight_decay: 0.0005
resume: icnet_cityscapes_best_model.pkl
visdom: False
loss:
name: cross_entropy
Hope this helps!
That is the big help. Thank you.
Now I got another error to fix.
That is the big help. Thank you.
Now I got another error to fix.
Glad to be of help! Did you manage to solve all the issues?
does using cross_entropy as the loss while training icnet work for you ?
Tried to run the train.py for ICNet using the README guide with Cityscapes dataset. Windows 10 CUDA 10.1 GPU: Nvidia GEFORCE GTX 1050Ti Using the Conda virtual environment. Issued the following command to train on the cityscapes dataset:
python train.py --config configs\icnet_cityscapes.yml
The output from the PowerShell windowThe config file