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Data---
This model is trained using the DeepFashion database
https://drive.google.com/drive/folders/0B7EVK8r0v71pWGplNFhjc01NbzQ
In case the above link is removed, try navigate through the follwing link
http://mmlab.ie.cuhk.edu.hk/projects/DeepFashion.html
Models---
model_w_label: this model only trains the cloth category directly
model_w_bbox_n_label: this model aims to train a bounding box area first and use that to assist the category training.
Instructions---
For detailed instructions on data preparation of LMDB and HDF5 check under Docs/
Once you got the data prepared, here's what you need for training.
Training---
Eg.
train with ResNet-50 weight initialization(optional) and subtrain1 data set, and save the log
../../../../build/tools/caffe train -solver solver.prototxt -weights ResNet-50-model.caffemodel 2>&1 | tee subtrain1.log
Note: The ResNet-50 weight file is too big to upload. Refer to He et al.'s ResNet git repo listed under 'Reference'
Testing---
Eg.
test with subtrain2 data set and save log file (subtrain2 has 52292 data points and 6536.5 batch, test itself round to 6535)
../../../../../build/tools/caffe test -model train.prototxt -weights caffenet_train_iter_60000.caffemodel -gpu 0 -iterations 6537 2>&1 | tee subtrain2.log