| # SODA | |
| This repository is the imprimentation of "SODA: Story Oriented Dense Video Captioning Evaluation Flamework" published at ECCV 2020 [pdf](https://fujiso.github.io/publications/ECCV2020_soda.pdf). | |
| SODA measures the performance of video story description systems. | |
| ## Update | |
| v1.1 (2021/5) | |
| * Added new option "--multi_reference" to deal with multiple reference. | |
| SODA selects the reference that has the maximum f1 for each video, and returns macro averaged scores. | |
| * Fixed BertScore import | |
| ## Requirements | |
| python 3.6+ (developed with 3.7) | |
| * Numpy | |
| * tqdm | |
| * [pycocoevalcap (Python3 version)](https://github.com/salaniz/pycocoevalcap) | |
| * BERTScore (optional) | |
| ## Usage | |
| You can run SODA by specifying the path of system output and that of ground truth. | |
| Both files should be the json format for ActivityNet Captions. | |
| ```bash | |
| python soda.py -s path/to/submission.json -r path/to/ground_truth.json | |
| ``` | |
| You can run on the multiple reference setting, with `--multi_reference` option. | |
| ```bash | |
| python soda.py --multi_reference -s path/to/submission.json -r path/to/ground_truth1.json path/to/ground_truth2.json | |
| ``` | |
| You can try other sentence evaluation metrics, e.g. CIDEr and BERTScore, with `-m` option. | |
| ```bash | |
| python soda.py -s path/to/submission.json -m BERTScore | |
| ``` | |
| ## Sample input file | |
| Please use the same format as [ActivityNet Challenge](http://activity-net.org/index.html) | |
| ``` | |
| { | |
| version: "VERSION 1.0", | |
| results: { | |
| "sample_id" : [ | |
| { | |
| sentence: "This is a sample caption.", | |
| timestamp: [1.23, 4.56] | |
| }, | |
| { | |
| sentence: "This is a sample caption 2.", | |
| timestamp: [7.89, 19.87] | |
| } | |
| ] | |
| } | |
| external_data: { | |
| used: False, | |
| } | |
| } | |
| ``` | |
| ## Reference | |
| ``` | |
| @inproceedings{Fujita2020soda, | |
| title={SODA: Story Oriented Dense Video Captioning Evaluation Flamework}, | |
| author={Soichiro Fujita and Tsutomu Hirao and Hidetaka Kamigaito and Manabu Okumura and Masaaki Nagata}, | |
| booktitle={Proceedings of the European Conference on Computer Vision (ECCV)}, | |
| month={August}, | |
| year={2020}, | |
| } | |
| ``` | |
| ## LICENSE | |
| NTT License | |
| According to the license, it is not allowed to create pull requests. | |
| Please feel free to send issues. | |