--- a
+++ b/tools/data/activitynet/download.py
@@ -0,0 +1,148 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+# This scripts is copied from
+# https://github.com/activitynet/ActivityNet/blob/master/Crawler/Kinetics/download.py  # noqa: E501
+# The code is licensed under the MIT licence.
+import argparse
+import os
+import ssl
+import subprocess
+
+import mmcv
+from joblib import Parallel, delayed
+
+ssl._create_default_https_context = ssl._create_unverified_context
+data_file = '../../../data/ActivityNet'
+output_dir = f'{data_file}/videos'
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='ActivityNet downloader')
+    parser.add_argument(
+        '--bsn',
+        action='store_true',
+        help='download for BSN annotation or official one')
+    args = parser.parse_args()
+    return args
+
+
+def download_clip(video_identifier,
+                  output_filename,
+                  num_attempts=5,
+                  url_base='https://www.youtube.com/watch?v='):
+    """Download a video from youtube if exists and is not blocked.
+    arguments:
+    ---------
+    video_identifier: str
+        Unique YouTube video identifier (11 characters)
+    output_filename: str
+        File path where the video will be stored.
+    """
+    # Defensive argument checking.
+    assert isinstance(video_identifier, str), 'video_identifier must be string'
+    assert isinstance(output_filename, str), 'output_filename must be string'
+    assert len(video_identifier) == 11, 'video_identifier must have length 11'
+
+    status = False
+
+    if not os.path.exists(output_filename):
+        command = [
+            'youtube-dl', '--quiet', '--no-warnings', '--no-check-certificate',
+            '-f', 'mp4', '-o',
+            '"%s"' % output_filename,
+            '"%s"' % (url_base + video_identifier)
+        ]
+        command = ' '.join(command)
+        print(command)
+        attempts = 0
+        while True:
+            try:
+                subprocess.check_output(
+                    command, shell=True, stderr=subprocess.STDOUT)
+            except subprocess.CalledProcessError:
+                attempts += 1
+                if attempts == num_attempts:
+                    return status, 'Fail'
+            else:
+                break
+    # Check if the video was successfully saved.
+    status = os.path.exists(output_filename)
+    return status, 'Downloaded'
+
+
+def download_clip_wrapper(youtube_id, output_dir):
+    """Wrapper for parallel processing purposes."""
+    # we do this to align with names in annotations
+    output_filename = os.path.join(output_dir, 'v_' + youtube_id + '.mp4')
+    if os.path.exists(output_filename):
+        status = tuple(['v_' + youtube_id, True, 'Exists'])
+        return status
+
+    downloaded, log = download_clip(youtube_id, output_filename)
+    status = tuple(['v_' + youtube_id, downloaded, log])
+    return status
+
+
+def parse_activitynet_annotations(input_csv, is_bsn_case=False):
+    """Returns a list of YoutubeID.
+    arguments:
+    ---------
+    input_csv: str
+        Path to CSV file containing the following columns:
+          'video,numFrame,seconds,fps,rfps,subset,featureFrame'
+    returns:
+    -------
+    youtube_ids: list
+        List of all YoutubeIDs in ActivityNet.
+
+    """
+    if is_bsn_case:
+        lines = open(input_csv).readlines()
+        lines = lines[1:]
+        # YoutubeIDs do not have prefix `v_`
+        youtube_ids = [x.split(',')[0][2:] for x in lines]
+    else:
+        data = mmcv.load(anno_file)['database']
+        youtube_ids = list(data.keys())
+
+    return youtube_ids
+
+
+def main(input_csv, output_dir, anno_file, num_jobs=24, is_bsn_case=False):
+    # Reading and parsing ActivityNet.
+    youtube_ids = parse_activitynet_annotations(input_csv, is_bsn_case)
+
+    # Creates folders where videos will be saved later.
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+    # Download all clips.
+    if num_jobs == 1:
+        status_list = []
+        for index in youtube_ids:
+            status_list.append(download_clip_wrapper(index, output_dir))
+    else:
+        status_list = Parallel(n_jobs=num_jobs)(
+            delayed(download_clip_wrapper)(index, output_dir)
+            for index in youtube_ids)
+
+    # Save download report.
+    mmcv.dump(status_list, 'download_report.json')
+    annotation = mmcv.load(anno_file)
+    downloaded = {status[0]: status[1] for status in status_list}
+    annotation = {k: v for k, v in annotation.items() if downloaded[k]}
+
+    if is_bsn_case:
+        anno_file_bak = anno_file.replace('.json', '_bak.json')
+        os.rename(anno_file, anno_file_bak)
+        mmcv.dump(annotation, anno_file)
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    is_bsn_case = args.bsn
+    if is_bsn_case:
+        video_list = f'{data_file}/video_info_new.csv'
+        anno_file = f'{data_file}/anet_anno_action.json'
+    else:
+        video_list = f'{data_file}/activity_net.v1-3.min.json'
+        anno_file = video_list
+    main(video_list, output_dir, anno_file, 24, is_bsn_case)