Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 289, in get_dataset_config_info
for split_generator in builder._split_generators(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 55, in _get_pipeline_from_tar
current_example[field_name] = cls.DECODERS[data_extension](current_example[field_name])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 318, in torch_loads
return torch.load(io.BytesIO(data), weights_only=True)
File "/src/services/worker/.venv/lib/python3.9/site-packages/torch/serialization.py", line 1548, in load
raise pickle.UnpicklingError(_get_wo_message(str(e))) from None
_pickle.UnpicklingError: Weights only load failed. In PyTorch 2.6, we changed the default value of the `weights_only` argument in `torch.load` from `False` to `True`. Re-running `torch.load` with `weights_only` set to `False` will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source.
Please file an issue with the following so that we can make `weights_only=True` compatible with your use case: WeightsUnpickler error: Unsupported operand 149
Check the documentation of torch.load to learn more about types accepted by default with weights_only https://pytorch.org/docs/stable/generated/torch.load.html.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 343, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 294, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
OVMOT Detections
OVMOT Detections provides detailed results on open-vocabulary multi-object tracking benchmarks. The dataset is tailored for researchers and practitioners focusing on novel object detection and tracking challenges.
Dataset Overview
- Name: OVMOT Detections
- Task: Open-Vocabulary Multi-Object Tracking
- Data Type: Detection results
- Processing Note: All detection results are post processed with NMS 50
- Detector: GLEE Plus
- Benchmark: BFT, OVT-B, and OVTAO
Intended Use
This dataset is designed for:
- Evaluating and benchmarking multi-object tracking algorithms.
- Research on open-vocabulary object tracking.
- Development of new tracking methods in real-world scenarios.
Dataset Structure
- Files: The dataset includes detection results alongside potential metadata and annotations.
- Others: Please refer to https://github.com/George-Zhuang/LBM for dataset structure.
Limitations
- The use of a non-max suppression threshold of 50 may impact detection performance.
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