models/py_utils/kp_utils.py about centernet HOT 6 OPEN

@wu-yy I also encountered the same problem, have you solved it?

from centernet.

@Duankaiwen Can you help me with this?

loading all datasets...
using 4 threads
loading from cache file: cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=13.40s)
creating index...
index created!
loading from cache file: cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=13.10s)
creating index...
index created!
loading from cache file: cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=12.44s)
creating index...
index created!
loading from cache file: cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=13.10s)
creating index...
index created!
loading from cache file: cache/coco_minival2014.pkl
loading annotations into memory...
Done (t=0.38s)
creating index...
index created!
system config...
{'batch_size': 1,
'cache_dir': 'cache',
'chunk_sizes': [1],
'config_dir': 'config',
'data_dir': '/home/zbh/Projects/centernet/data',
'data_rng': <mtrand.RandomState object at 0x7fbfdd16f9d8>,
'dataset': 'MSCOCO',
'decay_rate': 10,
'display': 5,
'learning_rate': 0.00025,
'max_iter': 480000,
'nnet_rng': <mtrand.RandomState object at 0x7fbfdd16fa20>,
'opt_algo': 'adam',
'prefetch_size': 6,
'pretrain': None,
'result_dir': 'results',
'sampling_function': 'kp_detection',
'snapshot': 5000,
'snapshot_name': 'CenterNet-104',
'stepsize': 450000,
'test_split': 'testdev',
'train_split': 'trainval',
'val_iter': 500,
'val_split': 'minival',
'weight_decay': False,
'weight_decay_rate': 1e-05,
'weight_decay_type': 'l2'}
db config...
{'ae_threshold': 0.5,
'border': 128,
'categories': 80,
'data_aug': True,
'gaussian_bump': True,
'gaussian_iou': 0.7,
'gaussian_radius': -1,
'input_size': [511, 511],
'kp_categories': 1,
'lighting': True,
'max_per_image': 100,
'merge_bbox': False,
'nms_algorithm': 'exp_soft_nms',
'nms_kernel': 3,
'nms_threshold': 0.5,
'output_sizes': [[128, 128]],
'rand_color': True,
'rand_crop': True,
'rand_pushes': False,
'rand_samples': False,
'rand_scale_max': 1.4,
'rand_scale_min': 0.6,
'rand_scale_step': 0.1,
'rand_scales': array([0.6, 0.7, 0.8, 0.9, 1. , 1.1, 1.2, 1.3]),
'special_crop': False,
'test_scales': [1],
'top_k': 70,
'weight_exp': 8}
len of db: 118287
start prefetching data...
shuffling indices...
start prefetching data...
shuffling indices...
start prefetching data...
shuffling indices...
start prefetching data...
shuffling indices...
start prefetching data...
building model...
module_file: models.CenterNet-104
shuffling indices...
total parameters: 210062960
setting learning rate to: 0.00025
training start...
0%| | 0/480000 [00:00<?, ?it/s]/home/zbh/Anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/modules/upsampling.py:122: UserWarning: nn.Upsampling is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.Upsampling is deprecated. Use nn.functional.interpolate instead.")
Traceback (most recent call last):
File "/home/zbh/Projects/centernet/train.py", line 206, in
train(training_dbs, validation_db, args.start_iter)
File "/home/zbh/Projects/centernet/train.py", line 138, in train
training_loss, focal_loss, pull_loss, push_loss, regr_loss = nnet.train(**training)
File "/home/zbh/Projects/centernet/nnet/py_factory.py", line 82, in train
loss_kp = self.network(xs, ys)
File "/home/zbh/Anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/zbh/Projects/centernet/models/py_utils/data_parallel.py", line 70, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/home/zbh/Projects/centernet/models/py_utils/data_parallel.py", line 80, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/home/zbh/Anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 77, in parallel_apply
raise output
File "/home/zbh/Anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 53, in _worker
output = module(*input, **kwargs)
File "/home/zbh/Anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/zbh/Projects/centernet/nnet/py_factory.py", line 21, in forward
loss_kp = self.loss(preds, ys, **kwargs)
File "/home/zbh/Anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/zbh/Projects/centernet/models/py_utils/kp.py", line 339, in forward
pull, push = self.ae_loss(tl_tag, br_tag, gt_mask)
File "/home/zbh/Projects/centernet/models/py_utils/kp_utils.py", line 217, in _ae_loss
dist = tag_mean.unsqueeze(1) - tag_mean.unsqueeze(2)
RuntimeError: Dimension out of range (expected to be in range of [-2, 1], but got 2)

from centernet.

@Dawning23 #20

from centernet.

@Duankaiwen That's really helpful,thanks a lot!

from centernet.

Dimension out of range (expected to be in range of [-2, 1], but got 2)
can you help me?

from centernet.

@songjiaojie #20

from centernet.