Clothing Classification with Capsule Networks
Keras (Backend: TF) implementation of FashionCapsNet
Accepted to International Journal of Informatics Technologies. Paper will be released soon!
Reference: Sara Sabour, Nicholas Frosst, Geoffrey E Hinton. Dynamic Routing Between Capsules. NIPS 2017
Base code for Capsule architecture: XifengGuo
Dataset: DeepFashion
contains 290K training, 40K validation and 40K test images with 46 fine-grained category labels for clothing images
Please feel free to open an issue or to send an e-mail to furkan.kinli@ozyegin.edu.tr
- NumPy 1.16.X
- Tensorflow 1.12.X
- Keras 2.2.X
- OpenCV 3.4.X
python main.py --args
Validation accuracy converges at 255. epoch.
Apprx. 15 days to complete train on 2 GTX1080Tis.
For running with different parameters, please view the config file!
python main.py -t -w ./result/t_model.h5
Test accuracy:
- Top-1: 63.61%
- Top-3: 83.18%
- Top-5: 89.83%
