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Traceback (most recent call last):
File "tools/train_net.py", line 147, in <module>
main()
File "tools/train_net.py", line 127, in main
train_loader = make_train_data_loader(datasets, is_distributed=args.distributed, start_iter=scheduler.iteration)
File "/data/home/v_julhugoye/human_parsing/RP-R-CNN/rcnn/datasets/dataset.py", line 121, in make_train_data_loader
sampler = make_data_sampler(datasets, shuffle, is_distributed)
File "/data/home/v_julhugoye/human_parsing/RP-R-CNN/rcnn/datasets/dataset.py", line 66, in make_data_sampler
sampler = torch.utils.data.sampler.RandomSampler(dataset)
File "/data/home/v_julhugoye/.conda/envs/ParsingRCNN/lib/python3.6/site-packages/torch/utils/data/sampler.py", line 94, in __init__
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0
Segmentation fault
So thanks for your help
The text was updated successfully, but these errors were encountered:
def has_valid_annotation(anno, ann_types, filter_crowd=True):
# if it's empty, there is no annotation
if len(anno) == 0:
return False
if filter_crowd:
# if image only has crowd annotation, it should be filtered
if 'iscrowd' in anno[0]:
anno = [obj for obj in anno if obj["iscrowd"] == 0]
if len(anno) == 0:
return False
# if all boxes have close to zero area, there is no annotation
if _has_only_empty_bbox(anno):
return False
return False
Hello!
I am trying to train RP-R-CNN, but I encounter a problem when runing the training command following the Readme.md. When running
I am getting the following message:
So thanks for your help
The text was updated successfully, but these errors were encountered: