The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 159, in compute
compute_split_names_from_info_response(
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 131, in compute_split_names_from_info_response
config_info_response = get_previous_step_or_raise(kind="config-info", dataset=dataset, config=config)
File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 567, in get_previous_step_or_raise
raise CachedArtifactError(
libcommon.simple_cache.CachedArtifactError: The previous step failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 499, 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/folder_based_builder/folder_based_builder.py", line 175, in _split_generators
pa_metadata_table = self._read_metadata(downloaded_metadata_file, metadata_ext=metadata_ext)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 245, in _read_metadata
return paj.read_json(f)
File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0
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 75, 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 572, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 504, 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? Open a discussion for direct support.
Overview
This data set contains Beluga whales (Delphinapterus leucas) with pre-cropped images and individual animal identifications. This dataset represents a collaborative effort based on the data collection and population modeling efforts conducted in the Cook Inlet off the cost of Alaska from 2016-2019. The photos (5,902) and metadata from 1,617 unique encounters (within 1 hour) were collected from boat-based cameras and a camera looking down from above on an aerial drone. Images are annotated with full-image bounding boxes and viewpoints were labeled (top, left, right). A total of 788 individual Beluga whales were identified by hand by trained experts using scarring patterns and other visual markings. This dataset is being released in tandem with the “Where’s Whale-do?” ID competition hosted by DrivenData and is identical to the public training set used in that competition.
Data format
The training dataset is released in the Microsoft COCO .json format. We have collapsed the entire dataset into a single “train” label and have left “val” and “test” empty; we do this as an invitation to researchers to experiment with their own novel approaches for dealing with the unbalanced and chaotic distribution on the number of sightings per individual. All of the images in the dataset have been resized to have a maximum dimension of 1,200 pixels. The metadata for all animal sightings is defined by an axis-aligned bounding box and includes information on the viewpoint of the animal, a species (category) ID, a source image ID, an individual string ID name, and other miscellaneous values. The temporal ordering of the images can be determined from the metadata for each image.
Test data was added later, after the competition, and is thus in a different format. Contact the dataset owner for questions about the test data.
Citation, license, and contact information
For research or press contact, please direct all correspondence to Wild Me at info@wildme.org. Wild Me is a registered 501(c)(3) not-for-profit based in Portland, Oregon, USA and brings state-of-the-art computer vision tools to ecology researchers working around the globe on wildlife conservation.
- Downloads last month
- 0