Google Cloud Video Intelligence API in Python - Unable to run object tracking on multiple videos in a folder

I'm trying to run object tracking on a folder containing multiple videos. There are 5 videos in my bucket and following the documentation from here, it suggests using the wildcard (*) operator. However, when I run the entire script, only 1 video gets annotated and not the entire folder containing 5 videos. Also, response2.json does not get created as the output_uri in my GCS bucket.

To identify multiple videos, a video URI may include wildcards in the object-id. Supported wildcards: ' * ' to match 0 or more characters; ‘?’ to match 1 character. https://googleapis.dev/python/videointelligence/latest/gapic/v1/types.html

Which is what I've done in my input_uri bit of the code:

gcs_uri = 'gs://video_intel/*'

If you check the screenshot, it should the bucket id name and shows multiple videos in the same folder.

Can anyone pls help with this question. Thanks.

Full script:

import os
os.environ['GOOGLE_APPLICATION_CREDENTIALS']='poc-video-intelligence-da5d4d52cb97.json'
"""Object tracking in a video stored on GCS."""
from google.cloud import videointelligence

video_client = videointelligence.VideoIntelligenceServiceClient()
features = [videointelligence.enums.Feature.OBJECT_TRACKING]
gcs_uri = 'gs://video_intel/*'
output_uri = 'gs://video_intel/response2.json'

operation = video_client.annotate_video(input_uri=gcs_uri, features=features, output_uri=output_uri)
print("\nProcessing video for object annotations.")

result = operation.result(timeout=300)
print("\nFinished processing.\n")

# The first result is retrieved because a single video was processed.
object_annotations = result.annotation_results[0].object_annotations

for object_annotation in object_annotations:
    print("Entity description: {}".format(object_annotation.entity.description))
    if object_annotation.entity.entity_id:
        print("Entity id: {}".format(object_annotation.entity.entity_id))

    print(
        "Segment: {}s to {}s".format(
            object_annotation.segment.start_time_offset.seconds
            + object_annotation.segment.start_time_offset.nanos / 1e9,
            object_annotation.segment.end_time_offset.seconds
            + object_annotation.segment.end_time_offset.nanos / 1e9,
        )
    )

    print("Confidence: {}".format(object_annotation.confidence))

    # Here we print only the bounding box of the first frame in the segment
    frame = object_annotation.frames[0]
    box = frame.normalized_bounding_box
    print(
        "Time offset of the first frame: {}s".format(
            frame.time_offset.seconds + frame.time_offset.nanos / 1e9
        )
    )
    print("Bounding box position:")
    print("\tleft  : {}".format(box.left))
    print("\ttop   : {}".format(box.top))
    print("\tright : {}".format(box.right))
    print("\tbottom: {}".format(box.bottom))
    print("\n")

please modify 'gcs_uri = 'gs://video_intel/'' to gcs_uri = 'gs://video_intel/.*'