| ## Video Augmented Texts Data | |
| ### VATEX | |
| Each video contains 10 captions. In `vatex.zip`, there are: | |
| * `test/`: a folder containing all available videos | |
| * `vatex_public_test_english_v1.1.json`: JSON file containing all captions | |
| Example data loading: | |
| ```py | |
| import os | |
| import json | |
| path = 'vatex_public_test_english_v1.1.json' | |
| d = json.load(open(path, 'r')) | |
| captions = {v['videoID']: v['enCap'] for v in d} | |
| for vname in captions: | |
| video_path = os.path.join('test', vname+'.mp4') # path to the video | |
| captions = captions[vname] # a list of 10 str | |
| ``` | |
| ### MSR-VTT | |
| Each video contains 1 caption. There are two files for MSR-VTT: | |
| * `MSRVTT.zip`: contains all videos | |
| * `MSRVTT_JSFUSION_test.csv`: contains all captions | |
| Example data loading: | |
| ```py | |
| import os | |
| import pandas as pd | |
| path = 'MSRVTT_JSFUSION_test.csv' | |
| df = pd.read_csv(path) | |
| vid_id_list = df['video_id'].tolist() | |
| caption_list = df['sentence'].tolist() | |
| for vid_id, caption in zip(vid_id_list, caption_list): | |
| video_path = os.path.join('MSRVTT', 'videos', 'all', vid_id+'.mp4') | |
| captions = [caption] # a list of 1 str | |
| ``` | |