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feature_extraction
feature_extraction
 
 
README.md
README.md
 
 
c3d_ucf101_deploy.prototxt
c3d_ucf101_deploy.prototxt
 
 
c3d_ucf101_solver.prototxt
c3d_ucf101_solver.prototxt
 
 
c3d_ucf101_test.prototxt
c3d_ucf101_test.prototxt
 
 
c3d_ucf101_test_split1.txt
c3d_ucf101_test_split1.txt
 
 
c3d_ucf101_train_loss_accuracy.png
c3d_ucf101_train_loss_accuracy.png
 
 
c3d_ucf101_train_split1.txt
c3d_ucf101_train_split1.txt
 
 
c3d_ucf101_train_test.prototxt
c3d_ucf101_train_test.prototxt
 
 
check_data_and_model.py
check_data_and_model.py
 
 
extract_UCF-101_frames.sh
extract_UCF-101_frames.sh
 
 
test_ucf101.sh
test_ucf101.sh
 
 
train_ucf101.sh
train_ucf101.sh
 
 
ucf101_train_mean.binaryproto
ucf101_train_mean.binaryproto
 
 

README.md

UCF-101 training demo

Follow the steps in README.md

Files in this directory

  • train_ucf101.sh: a main script to run for training C3D on UCF-101 data
  • c3d_ucf101_solver.prototxt: a solver specifications -- SGD parameters, testing parametesr, etc
  • c3d_ucf101_test_split1.txt, c3d_ucf101_train_split1.txt: lists of testing/training video clips in ("video directory", "starting frame num", "label") format
  • c3d_ucf101_train_test.prototxt: training/testing network model
  • ucf101_train_mean.binaryproto: a mean cube calculated from UCF101 training set
  • c3d_ucf101_train_loss_accuracy.png: a sample plot of training iteration vs loss and accuracy