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C3D Model for Keras

C3D Model for Keras

This is the C3D model used with a fork of Caffe to the Sports1M dataset migrated to Keras. Details about the network architecture can be found in the following arXiv paper:

Tran, Du, et al. "Learning Spatiotemporal Features With 3D Convolutional Networks." Proceedings of the IEEE International Conference on Computer Vision. 2015.


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supun-kanda commented Jan 23, 2019

The links on weights and model to keras model you gave have some issues. Or my versions should be missmatched. Here are my libraries and versions

  • caffe-gpu=1.0=py36h51fbcb3_4
  • cudatoolkit=9.2=0
  • cudnn=7.2.1=cuda9.2_0
  • cupti=9.2.148=0
  • ffmpeg=4.0=hcdf2ecd_0
  • freeglut=3.0.0=hf484d3e_5
  • gast=0.2.0=py36_0
  • gflags=2.2.2=he6710b0_0
  • jasper=2.0.14=h07fcdf6_1
  • keras-applications=1.0.6=py36_0
  • keras-base=2.2.4=py36_0
  • keras-gpu=2.2.4=0
  • keras-preprocessing=1.0.5=py36_0
  • libboost=1.67.0=h46d08c1_4
  • libglu=9.0.0=hf484d3e_1
  • libopencv=3.4.2=hb342d67_1
  • libopus=1.3=h7b6447c_0
  • libprotobuf=3.6.1=hd408876_0
  • lmdb=0.9.22=hf484d3e_1
  • markdown=3.0.1=py36_0
  • protobuf=3.6.1=py36he6710b0_0
  • py-boost=1.67.0=py36h04863e7_4
  • py-opencv=3.4.2=py36hb342d67_1
  • python-gflags=3.1.2=py36_0
  • python-leveldb=0.194=py36_1
  • tensorboard=1.12.0=py36hf484d3e_0
  • tensorflow=1.12.0=gpu_py36he74679b_0
  • tensorflow-base=1.12.0=gpu_py36had579c0_0
  • tensorflow-gpu=1.12.0=h0d30ee6_0
  • termcolor=1.1.0=py36_1
  • conda=4.5.12=py36_0
  • conda-build=3.17.6=py36_0
  • conda-env=2.6.0=1
  • jupyter=1.0.0=py36_7
  • jupyter_client=5.2.4=py36_0
  • jupyter_console=6.0.0=py36_0
  • jupyter_core=4.4.0=py36_0
  • jupyterlab=0.35.3=py36_0
  • jupyterlab_server=0.2.0=py36_0
  • numpy=1.15.4=py36h7e9f1db_0
  • numpy-base=1.15.4=py36hde5b4d6_0
  • pillow=5.3.0=py36h34e0f95_0
  • pip=18.1=py36_0
  • python=3.6.7=h0371630_0
  • scikit-image=0.14.1=py36he6710b0_0
  • scikit-learn=0.20.1=py36hd81dba3_0
  • scipy=1.1.0=py36h7c811a0_2
  • pip:
    • keras==2.2.4

When using json model here is the error
ValueError: Improper config format:

When using previously created model (by adding layers manually) to lead h5 file weights here is the error
ValueError: You are trying to load a weight file containing 0 layers into a model with 11 layers.

Looks like the weights files cant be decoded properly. Any Idea on what to do?

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aslucki commented Feb 5, 2019

@supun-kanda Based on this project:
I created an updated version of the model (for keras 2.2.4):
and weights.

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iriyagupta commented Sep 10, 2019

Hi, I am facing this error. Did anyone else face this issue?

AttributeError Traceback (most recent call last)
22 weights_b = np.array(layer.blobs[1].data, dtype=np.float32)
23 weights_p = np.array(layer.blobs[0].data, dtype=np.float32).reshape(
---> 24 layer.blobs[0].num, layer.blobs[0].channels, layer.blobs[0].length,
25 layer.blobs[0].height, layer.blobs[0].width
26 )

AttributeError: length

I am new to caffe and getting attributes from blob using hpp files is sort of not understandable to me here.
Thanks in advance.

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Is there any training code for the sports-1m dataset?

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how can we use the C3D features to model violence detection on videos?

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