| # MME-Emotion | |
| MME-Emotion is a multimodal emotion benchmark designed for evaluating | |
| emotion understanding and reasoning under diverse settings. | |
| ## Contents | |
| Each subset consists of: | |
| - A JSON annotation file | |
| - A ZIP archive containing corresponding video clips | |
| Due to privacy considerations, raw videos are distributed only in compressed form. | |
| ### Subsets | |
| - ER_Lab / ER_Wild | |
| - FG_ER / FG_SA | |
| - IR | |
| - ML_ER | |
| - Noise_ER | |
| - SA | |
| Additional audio-based explanations are provided in `audio_clue/`. | |
| ## Usage | |
| ```python | |
| import json | |
| from zipfile import ZipFile | |
| with open("ER_Lab.json") as f: | |
| data = json.load(f) | |
| video_id = data[0]["video_id"] # ER_Lab/xxx.mp4 | |