2nd Place Team's Solution for Fashion IQ Challenge 2020
- CodaLab: https://competitions.codalab.org/competitions/22946#results
- Workshop page: https://sites.google.com/view/cvcreative2020/fashion-iq
- Prepare Data:
Download Dataset from here
Image download script has been added. (12/07/2020)
run_download_image.shThe data structure should look like:
cd ./ours/train
dataset
├──image_splits
│ ├──split.dress.train.json
│ ├──...
│ ├──split.toptee.test.json
│
├──captions
│ ├──cap.dress.train.json
│ ├──...
│ ├──cap.toptee.test.json
│
├──images
├──B000OHM9FI.jpg
├──...
├──B000M89C40.jpg
- Install required packages using virtualenv
python3 -m virtualenv --python=python3 py3
. py3/bin/activate
pip install -r requirements.txt
- Download required files: word2vec, sentence_embedding, image_emedding
Download from here: google drive
cd ./ours/train
tar -xvf assets.tar
Run the script below.
overall score curve
loss curve
cd ours/train
python3 main.py \
--warmup \
--gpu_id '0' \
--method 'tirg' \
--text_method 'lstm-gru' \
--expr_name 'devel' \
--data_root './dataset' \
--backbone 'resnet152' \
--fdims 2048 \
--epochs 100 \
--batch_size 32 \
--image_size 224 \
--normalize_scale 5.0 \
--lr 0.00011148 \
--lrp 0.48 \
--lr_decay_steps "10,20,30,40,50,60,70" \
--lr_decay_factor 0.4747
(i) get the score output on test/val:
cd ours/tools
python3 get_score.py --data_root './dataset' --expr_name 'devel'
(ii) get emsemble score using Bayesian Optimization provided by hyperopt:
Check the name of output score saved in ours/tools/output_score.
if the candidate models are: ['20200605122245_devel', '20200605152325_devel']
python3 optimize_score.py --data_root './dataset' --repos '20200605122245_devel,20200605152325_devel'