tqvinhcs / c3d-tensorflow Goto Github PK
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Action recognition with C3D network implemented in tensorflow
Hi,
Is this file still hosted anywhere? The version on dropbox has been deleted.
It would be much appreciated if I could get hold of it somehow.
Line 312 in 6267a14
Why 96.6? What is the purpose of that number please?
Traceback (most recent call last):
File "<ipython-input-4-a459e8a3dd1f>", line 1, in <module>
runfile('D:/Hajra/C3D/m_c3d_Mhuhavi_Finetune.py', wdir='D:/Hajra/C3D')
File "C:\Users\c2vr\AppData\Local\conda\conda\envs\tensorflow_env\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 786, in runfile
execfile(filename, namespace)
File "C:\Users\c2vr\AppData\Local\conda\conda\envs\tensorflow_env\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "D:/Hajra/C3D/m_c3d_Mhuhavi_Finetune.py", line 359, in <module>
demo_finetune()
File "D:/Hajra/C3D/m_c3d_Mhuhavi_Finetune.py", line 341, in demo_finetune
voxel, cls = read_train(tr_file)
File "D:/Hajra/C3D/m_c3d_Mhuhavi_Finetune.py", line 201, in read_train
start = np.random.randint(int(frm) - FRAMES)
where Frames = 16 and BATCH_SIZE = 32
Hi, is there any instructions or preparations of the input dataset?
I am trying to extract 3D features of UCF50 dataset. Is it necessary to run demo_finetune since you have provided pretrained weights?
I cloned the repository and tried to run m_c3d.py. I got the following error.
File "m_c3d.py", line 357, in
demo_test()
File "m_c3d.py", line 245, in demo_test
logits = c3d_ucf101(inputs=inputs, training=training, weights=weights)
File "m_c3d.py", line 109, in c3d_ucf101
net = tf.layers.flatten(net)
AttributeError: 'module' object has no attribute 'flatten'
But my tensorflow version is 1.3.0.
Not sure the reason of the error. Appreciated for any suggestions.
Can you please share with us the code for realtime prediction?
Hello
I just want to know that which code you have used for generating c3d_train.txt and c3d_val.txt?
could you please share that code?
Thanks
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