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Data loaders for pretrain and downstream tasks (retrieval and caption).

Preprocess on HowTo100M

For pretrain, you need to prepare 3 parts,

1. s3d features pretrained on HowTo100M

Download raw videos from the HowTo100M webpage and extract s3d (howto100m) features. You can refer to VideoFeatureExtractor.

2. HowTo100M.csv

Note: this file is different from HowTo100M_v1.csv as in README.txt

The csv format contains two columns. The first column is the video id, and the second is the feature file (sub-path of the npy, which will post append to --features_path (refer to pretrain part in README) to find the npy file when reading).

video_id,feature_file
Z8xhli297v8,Z8xhli297v8.npy
...

video_id: used to match the caption or transcript feature_file: used to find the feature file after joining with --features_path

3. caption.pickle

This pickle file is generated from raw_caption.json in raw_caption.zip introduced in README.txt

The format of this file is:

{
    'video_id 1':{
        'start': array([0.08, 7.37, 15.05, ...], dtype=object),
        'end': array([9.96, 16.98, 27.9, ...], dtype=object),
        'text': array(['sentence 1 placehodolder',
                    'sentence 2 placehodolder',
                    'sentence 3 placehodolder', ...], dtype=object)
    },
    ...
}

Keep the start is a sorted array.

Preprocess on YoucookII

The s3d feature extraction is the same as HowTo100M introduced above.

Generate youcookii_data.pickle

This file is generated from youcookii_annotations_trainval.json, which can be downloaded from official webpage.

The format of this file is (similar to caption.pickle introduced above, but one more key transcript. The transcript needs to generated by extra ASR tool from speech.):

{
    'video_id 1':{
        'start': array([0.08, 7.37, 15.05, ...], dtype=object),
        'end': array([9.96, 16.98, 27.9, ...], dtype=object),
        'text': array(['sentence 1 placehodolder',
                    'sentence 2 placehodolder',
                    'sentence 3 placehodolder', ...], dtype=object)
        'transcript': array(['transcript 1 placehodolder',
                    'transcript 2 placehodolder',
                    'transcript 3 placehodolder', ...], dtype=object)
    },
    ...
}

If you want to test on retrieval or caption w/o transcript tasks, you can set transcript with array(['NONE', 'NONE', 'NONE', ...], dtype=object).

Format of csv

video_id,feature_file
Z8xhli297v8,Z8xhli297v8
...

Note: The video_id and feature_file are the same for the consistency and our historical compatibility. We use feature_file to get the feature from feature pickle.

Preprocess on MSRVTT

The s3d feature extraction is the same as HowTo100M introduced above. The data can be downloaded in: https://github.com/microsoft/UniVL/releases/download/v0/msrvtt.zip