Hi
i tried to follow the guideline (jetson-inference/pytorch-collect-detection.md at master · dusty-nv/jetson-inference · GitHub) to train my own object detection model
After collecting the images of different classes, i run the command below:
python3 train_ssd.py --dataset-type=voc --data=data/phone --model-dir=models/phone --batch-size=2 --workers=1 --epochs=1
and here is my log with error (ran out of input)
Namespace(balance_data=False, base_net=None, base_net_lr=0.001, batch_size=2, checkpoint_folder=‘models/phone’, dataset_type=‘voc’, datasets=[‘data/phone’], debug_steps=10, extra_layers_lr=None, freeze_base_net=False, freeze_net=False, gamma=0.1, lr=0.01, mb2_width_mult=1.0, milestones=‘80,100’, momentum=0.9, net=‘mb1-ssd’, num_epochs=1, num_workers=1, pretrained_ssd=‘models/mobilenet-v1-ssd-mp-0_675.pth’, resume=None, scheduler=‘cosine’, t_max=100, use_cuda=True, validation_epochs=1, weight_decay=0.0005)
Prepare training datasets.
VOC Labels read from file: (‘BACKGROUND’, ‘APPLE’, ‘HUAWEI’)
Stored labels into file models/phone/labels.txt.
Train dataset size: 314
Prepare Validation datasets.
VOC Labels read from file: (‘BACKGROUND’, ‘APPLE’, ‘HUAWEI’)
Validation dataset size: 39
Build network.
Init from pretrained ssd models/mobilenet-v1-ssd-mp-0_675.pth
Traceback (most recent call last):
File “train_ssd.py”, line 311, in
net.init_from_pretrained_ssd(args.pretrained_ssd)
File “/jetson-inference/python/training/detection/ssd/vision/ssd/ssd.py”, line 119, in init_from_pretrained_ssd
state_dict = torch.load(model, map_location=lambda storage, loc: storage)
File “/usr/local/lib/python3.6/dist-packages/torch/serialization.py”, line 580, in load
return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
File “/usr/local/lib/python3.6/dist-packages/torch/serialization.py”, line 750, in _legacy_load
magic_number = pickle_module.load(f, **pickle_load_args)
EOFError: Ran out of input
Would you please help identify what could be the possible root causes? thanks.