SegNet on Pascal:: TypeError: default_collate: batch must contain tensors, numpy arrays, numbers, dicts or lists;

[farnaznouraei]

Hi. I am trying to train SegNet on a small subset of pascal VOC 2012. I made another data loader for pascal to overfit on it (since SegNet gave me very bad results on the full VOC dataset)- the only change I made is I made it read a shorter version of train.txt, val.txt and trainval.txt. I get the following error message after starting the training:

train_reduced.py:223: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
cfg = yaml.load(fp)
RUNDIR: runs/config_segnet./2000
sbd_path = /home/ubuntu/data/VOC/benchmark_RELEASE
expected number of files: 30
sbd_path = /home/ubuntu/data/VOC/benchmark_RELEASE
expected number of files: 30
image names: 2007_000250
image names: 2007_000039
image names: 2007_000063
image names: 2007_000068
image names: 2007_000243
image names: 2007_000032
image names: 2007_000121
image names: 2007_000170
image names: 2007_000256
Traceback (most recent call last):
File "train_reduced.py", line 234, in
image names: 2007_000241
train(cfg, writer, logger)
File "train_reduced.py", line 123, in train
for (images, labels) in trainloader:
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in next
data = self._next_data()
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 856, in _next_data
return self._process_data(data)
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 881, in _process_data
data.reraise()
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/torch/_utils.py", line 395, in reraise
raise self.exc_type(msg)
TypeError: Caught TypeError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 47, in fetch
return self.collate_fn(data)
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py", line 79, in default_collate
return [default_collate(samples) for samples in transposed]
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py", line 79, in
return [default_collate(samples) for samples in transposed]
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py", line 81, in default_collate
raise TypeError(default_collate_err_msg_format.format(elem_type))
TypeError: default_collate: batch must contain tensors, numpy arrays, numbers, dicts or lists; found <class 'PIL.JpegImagePlugin.JpegImageFile'>

My config looks like below:

# Model Configuration
model:
  arch: segnet

# Data Configuration
data:
  dataset: pascal
  train_split: train
  val_split: val
  img_rows: 318
  img_cols: 500
  path: /home/ubuntu/data/VOC/VOCdevkit/VOC2012
  sbd_path: /home/ubuntu/data/VOC/benchmark_RELEASE/

# Training Configuration
 training:
    n_workers: 1
    train_iters: 2000
    batch_size: 6
    val_interval: 3000
    print_interval: 50
loss:
    name: 'cross_entropy'
    size_average: False
    
# Optmizer Configuration
optimizer:
    name: 'sgd'
    lr: 1.0e-5

l_rate: 1.0e-5
lr_schedule:
  name: constant_lr
momentum: 0.99
weight_decay: 0.0005

# LR Schedule Configuration
lr_schedule:

# Resume from checkpoint  
resume: null

Could someone please help me with this?

[farnaznouraei]

Resolved. I had set the is_transform flag off, in train.py during data loading.