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I'm running the pretrained models on 2no. patients scans. Here's the Log of error. starting preprocessing
b83ce5267f3fd41c7029b4e56724cd08 done
b7ef0e864365220b8c8bfb153012d09a done
end preprocessing
Traceback (most recent call last):
File "main.py", line 60, in
test_detect(test_loader, nod_net, get_pbb, bbox_result_path,config1,n_gpu=config_submit['n_gpu'])
File "/Users/bharath/Downloads/DSB2017-master/test_detect.py", line 24, in test_detect
for i_name, (data, target, coord, nzhw) in enumerate(data_loader):
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in next
data = self._next_data()
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 856, in _next_data
return self._process_data(data)
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 881, in _process_data
data.reraise()
File "/Users/bharath/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 "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/Users/bharath/Downloads/DSB2017-master/data_detector.py", line 125, in getitem
margin = self.split_comber.margin/self.stride)
File "/Users/bharath/Downloads/DSB2017-master/split_combine.py", line 37, in split
data = np.pad(data, pad, 'edge')
File "<array_function internals>", line 6, in pad
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/numpy/lib/arraypad.py", line 738, in pad
raise TypeError('pad_width must be of integral type.')
TypeError: pad_width must be of integral type.
Since Im running on macOS (cpu only) ,commented below lines in main.py
#torch.cuda.set_device(0)
#nod_net = nod_net.cuda()
#cudnn.benchmark = True
#nod_net = DataParallel(nod_net)
Please guide me how to run pre-trained models in my macOS with 2-3 patients dataset.
Thanks in Advance
The text was updated successfully, but these errors were encountered:
Hi @yusuke0324@shakjm
First of all pad_width error is due to float value passed as calculated.
cuda cant be run on cpu. since cuda supports only keras which is GPU supported.
I used Kaggle to run on GPU and got my results.!!!
Kaggle provides 30hrs of GPU & TPU access free for every account. You can upload your datasets and run easily.
I'm running the pretrained models on 2no. patients scans. Here's the Log of error.
starting preprocessing
b83ce5267f3fd41c7029b4e56724cd08 done
b7ef0e864365220b8c8bfb153012d09a done
end preprocessing
Traceback (most recent call last):
File "main.py", line 60, in
test_detect(test_loader, nod_net, get_pbb, bbox_result_path,config1,n_gpu=config_submit['n_gpu'])
File "/Users/bharath/Downloads/DSB2017-master/test_detect.py", line 24, in test_detect
for i_name, (data, target, coord, nzhw) in enumerate(data_loader):
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in next
data = self._next_data()
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 856, in _next_data
return self._process_data(data)
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 881, in _process_data
data.reraise()
File "/Users/bharath/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 "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/Users/bharath/Downloads/DSB2017-master/data_detector.py", line 125, in getitem
margin = self.split_comber.margin/self.stride)
File "/Users/bharath/Downloads/DSB2017-master/split_combine.py", line 37, in split
data = np.pad(data, pad, 'edge')
File "<array_function internals>", line 6, in pad
File "/Users/bharath/anaconda3/lib/python3.7/site-packages/numpy/lib/arraypad.py", line 738, in pad
raise TypeError('
pad_width
must be of integral type.')TypeError:
pad_width
must be of integral type.Since Im running on macOS (cpu only) ,commented below lines in main.py
#torch.cuda.set_device(0)
#nod_net = nod_net.cuda()
#cudnn.benchmark = True
#nod_net = DataParallel(nod_net)
Please guide me how to run pre-trained models in my macOS with 2-3 patients dataset.
Thanks in Advance
The text was updated successfully, but these errors were encountered: