Datasets:
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Error code: JWTInvalidSignature
Exception: InvalidSignatureError
Message: Signature verification failed
Traceback: Traceback (most recent call last):
File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
decoded = jwt.decode(
jwt=token,
...<2 lines>...
options=options,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
decoded = self.decode_complete(
jwt,
...<8 lines>...
leeway=leeway,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
decoded = self._jws.decode_complete(
jwt,
...<3 lines>...
detached_payload=detached_payload,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
self._verify_signature(
~~~~~~~~~~~~~~~~~~~~~~^
signing_input,
^^^^^^^^^^^^^^
...<4 lines>...
options=merged_options,
^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
raise InvalidSignatureError("Signature verification failed")
jwt.exceptions.InvalidSignatureError: Signature verification failedNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Reconstruction as a Bridge for Event-Based Visual Question Answering
This is the EvQA benchmark from the paper "Reconstruction as a Bridge for Event-Based Visual Question Answering".
The corresponding code can be found at https://github.com/HYLZ-2019/EvQA.
Dataset format
The questions directory contains the annotation files in JSON format, named as questions/{dataset_name}.json. Each JSON file contains metadata for the dataset and a list of questions. The metadata includes the dataset name and description. Each entry in the question list contains the question ID, file path to the corresponding H5 file, camera type, resolution, question type, duration, keywords, and text for the questions, answers and multiple-choice options (in both English and Chinese).
The h5_files directory contains the event data files and license information, organized by dataset name. Specifically, for each dataset, the structure is h5_files/{dataset_name}/{question_id}.h5 and h5_files/{dataset_name}/LICENSE.txt.
The event data is stored in HDF5 (.h5) format, generated using h5py with compression enabled. Each H5 file contains the event stream and optional image frames.
The file attributes store essential metadata, including:
sensor_resolution: The spatial resolution (H, W) of the sensor.num_events: The total number of events.num_imgs: The number of intensity images (0 if unavailable).duration: The duration of the recording in seconds.camera_type: The model of the event camera.data_source: The name of the source dataset.base_time: The absolute timestamp (epoch time) of the start of the recording. If the original timestamps are relative, this is set to 0.0. The timestamps in the file are relative to this base time (i.e., starting from 0).
The events are stored separately within the H5 file:
events/xs: X-coordinates of the events (uint16).events/ys: Y-coordinates of the events (uint16).events/ts: Timestamps of the events in microseconds (uint64), withts[0] == 0. We useuint64to avoid overflow for recordings longer than approximately 1.19 hours.events/ps: Polarity of the events (uint8), taking values of 0 or 1.
If intensity images are available, they are stored as separate datasets named images/image{idx:09d}, where idx is the image index. Each image dataset has the following attributes:
event_idx: The index of the event corresponding to the image timestamp.timestamp: The timestamp of the image (uint64), aligned with the timestamps of the event stream.
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