Saak-Transform
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Reinplementation of the paper On Data-Driven Saak Transform
Saak Transform
This is a reimplementation of the paper On Data-Driven Saak Transform (https://arxiv.org/abs/1710.04176), maintained by Jiali Duan and Yueru Chen.

psnr metric: 104.294772826

psnr metric: 105.637763477

psnr metric: 105.513759179

psnr metric: 106.509034118
Table of Content
-
[Dataset] ( Hand-written digits classification)
- [MNIST] ( train set: 60000, 28x28. We used the same with downloaded from http://yann.lecun.com/exdb/mnist/)
-
[Installation] (sklearn and Pytorch)
- [Sklearn Installation] Refer to http://scikit-learn.org/stable/install.html)
- [Pytorch Installation] (Refer to http://pytorch.org)
- [Optional: Jupyter Notebook] (Refer to http://jupyter.org/install.html)
-
[How to] (Forward and Inverse Transform
- Command
python multi-stage_saak_v2.py - Forward Transform:
multi_stage_saak_trans - Inverse Transform:
toy_recon(outputs,filters) - Detailed params:
- Command
usage: multi-stage_saak_v2.py [-h] [--loadSize LOADSIZE]
[--train_batch_size TRAIN_BATCH_SIZE]
[--test_batch_size TEST_BATCH_SIZE]
[--size SIZE] [--windsize WINDSIZE]
[--stride STRIDE] [--save_path SAVE_PATH]
[--recStage RECSTAGE] [--visNum VISNUM]
[--use_SP]
optional arguments:
-h, --help show this help message and exit
--loadSize LOADSIZE Number of samples to be loaded
--train_batch_size TRAIN_BATCH_SIZE
Batch size for loading
--test_batch_size TEST_BATCH_SIZE
Batch size for loading
--size SIZE Size of the input
--windsize WINDSIZE Size of moving window
--stride STRIDE Stride to take during convolution
--save_path SAVE_PATH
Path to save result
--recStage RECSTAGE Reconstruction start stage
--visNum VISNUM Number of visualizations
--use_SP Use S/P conversion
-
[To-do list]
- [x] One-stage Saak Transform
- [x] Multi-stage Saak Transform
- [x] Inverse Transform
- [x] S/P Conversion (multi-stage_saak_v2.py)
n alternative view about the Cascade of kernel augmentation and ReLU operation 5,-3) -> (5, 0, 0, 3) -
[Other Code]
- [notebook] multi-stage_saak_v2.ipynb
- [dataset I/O] datasets.py, utils.py
-
Contact Me
Contact me
Jiali Duan (Email: [email protected])
Yueru Chen (Email: [email protected])