|
## 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 |
|
``` |
|
|