Skip to content

Latest commit

 

History

History
36 lines (23 loc) · 1.29 KB

README.md

File metadata and controls

36 lines (23 loc) · 1.29 KB

Training

Preparation:

We use the LaMem dataset for training. Please download LaMem.

We use pre-trained MoCo v2 weights as our initialization, please download it here.

Labels of both machine memorability scores and human memorability scores are provided in this repo.

Commands:

Train a MachineMem predictor, run:

python main_predictor.py --inter_aug [path to lamem]

For HumanMem predictor, run:

python main_predictor.py --inter_aug --label_filename ./humanmem_scores.txt  [path to lamem]

Please note that the folder with images should be a subfolder of your path folder.

Evaluation (prediction)

python main_predictor.py -e --resume [path to predictor]  [path to your dataset] 

Results will be saved to ./test_result.txt.

If you only have few images to evaluate, you might try our demo at project page or hugging face.

Pre-trained models

We provide our pre-trained MachineMem/HumanMem predictors at this link.