Comments (4)
hi,
I encountered similar problems before, the reason is that the dimension of read video data is not consistent with the settings in placeholder, so you can check the dimension of your read video data.
Hope to help you
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Hi,
I am using the dataset ucf101, does it still bound to have dimension error as the author also used the same dataset. What changes did you make in this case?
from c3d-tensorflow.
Your error message shows that there is a problem with the batch of the read data, so you can print out the dimension of the read data to check if it's the same as the dimension set by the placeholder.My problem is that I can't read the data which is a liitle different with yours
from c3d-tensorflow.
hi,
i have same problem, you have solved it, could you tell me what you have changed?
from c3d-tensorflow.
Related Issues (20)
- Before about the reshape of dimension transform issues HOT 1
- ValueError: Cannot feed value of shape (11, 16, 160, 160, 3) for Tensor 'Placeholder:0', which has shape '(12, 16, 160, 160, 3)' HOT 1
- train_c3d_ucf101.py
- predict_c3d_ucf101.py
- very very big loss values
- Could you give me a list as example? HOT 1
- ValueError: setting an array element with a sequence. HOT 1
- What is the difference between clip accuracy and video accuracy?
- Train with last checkpoint
- ERROR when using conv3d
- about how to use .meta or index
- about preprocessing HOT 7
- ResourceExhaustedError in train_c3d_ucf101.py HOT 2
- UnboundLocalError: local variable 'img_datas' referenced before assignment HOT 2
- the accuracy is always 0 HOT 2
- overfitting HOT 1
- prototxt file for conv3d_deepnetA_sport1m_iter_1900000.caffemodel
- missunderstanding about .model file type HOT 1
- hou ge niubility HOT 1
- pi zhu is watching you
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