Toatal Frames: 527599
Label | Count |
---|---|
0 | 6332 |
1 | 6919 |
2 | 228 |
3 | 11679 |
4 | 16131 |
5 | 756 |
6 | 94847 |
7 | 21017 |
8 | 171437 |
9 | 198253 |
- TSNE
Visulization
- Confusion Matrix
- Skeleton & Predicted label
- Accuracy curve
Model Candidates
- LSTM / GRU 25 frames * 2 sample rate
- TCN Non Causal largest I can fit, it is fully conventional
- TCN Causal
- Bi-Directional RNN all models take the most simple structure no drop out
- Fully Connected Layer
Evaluation Metrics
- Cross-Validation
- S5 Only
to make the parameter number the same
csv to HDF5 http://docs.h5py.org/en/latest/
refer: https://discuss.pytorch.org/t/how-to-speed-up-the-data-loader/13740/2
refer LMDB (Lightning Memory-mapped Database)