cs231-capsule-yolo-traffic-sign-detection

Course project for CS231, modified YOLO architecture by adding capsule network for classification

put GTSRB and GTSDB data into data folder then run

python build_data.py

train model, modify the corresponding params.json file inside the experiment/model_name/ folder.

python main.py --model <'model_name'>

run tensorboardx:

tensorboard --logdir=<'path_to_log'>

Name		Name	Last commit message	Last commit date
Latest commit History 172 Commits
experiments		experiments
.gitignore		.gitignore
README.md		README.md
build_data.py		build_data.py
build_data_npy.py		build_data_npy.py
capsule_interpret.py		capsule_interpret.py
clean.sh		clean.sh
collect.sh		collect.sh
config.py		config.py
grid_search_class.py		grid_search_class.py
loss_fns.py		loss_fns.py
main.py		main.py
metrics.py		metrics.py
models.py		models.py
plot.py		plot.py
plot_cnn_capsule.py		plot_cnn_capsule.py
predict_fns.py		predict_fns.py
requirements.txt		requirements.txt
utils.py		utils.py

Cranial-XIX/cs231-capsule-yolo-traffic-sign-detection