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 "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 246, in _split_generators
                  raise ValueError(
                      "`file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files"
                  )
              ValueError: `file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files
              
              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 68, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, 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.

Pillar Drill Hole Quality Dataset

A multimodal dataset of holes drilled through aluminium extrusion offcuts on a pillar drill, for defect detection. Each example pairs a photograph of the finished hole with the audio recorded while it was drilled, and carries a clip-level normal/abnormal label, a per-window audio label, and a spatial grid label on the image.

Summary


Examples	307
Clip label	220 normal, 87 abnormal
Audio	48 kHz, mono, 16-bit PCM; 1.0–19.0 s (median 4.0 s)
Image	RGB JPEG, width 236–601 px, height 214–597 px

Abnormal holes are of a few loose kinds — a failed pierce that does not break through the far wall, a partly pierced cratered hole left shallow and dented, and a dent struck into the surface beside the hole. They are not separated into classes.

Layout

metadata.csv
example_0001/
    image.jpg
    audio.wav
    audio_label.npy
    image_label.npy
example_0002/
    ...

Files

image.jpg — photograph of the workpiece after drilling, cropped to the hole region.

audio.wav — the sound recorded while the hole was drilled. Single channel, 48 kHz, 16-bit PCM.

audio_label.npy — int8 array of shape [T], one entry per consecutive 1 s window of audio.wav (T = ceil(duration / 1), the final window may be shorter). Values: 0 normal, 1 defect.

image_label.npy — int8 array of shape [16, 16], a grid laid over image.jpg in row-major order (cell = row * 16 + col). Values: 1 defect, 0 clean surface, -1 ignore (outside the workpiece or not annotated). Normal examples are all 0.

metadata.csv

column	description
`example_id`	directory name, `example_0001` … `example_0307`
`label`	`normal` or `abnormal`
`duration_s`	length of `audio.wav` in seconds

Loading

import csv, numpy as np, soundfile as sf
from pathlib import Path

root = Path("Drilling_Final_Dataset")
meta = {r["example_id"]: r for r in csv.DictReader(open(root / "metadata.csv"))}

ex = root / "example_0001"
audio, sr = sf.read(ex / "audio.wav")          # (N,) float64, sr = 48000
y_audio = np.load(ex / "audio_label.npy")      # (T,)  int8
y_image = np.load(ex / "image_label.npy")      # (16, 16) int8
clip_label = meta["example_0001"]["label"]

Label notes

About 27% of audio windows in the dataset are defect.
In image_label.npy, treat -1 as an ignore index. Abnormal examples always contain at least one 1 cell; normal examples are all 0.
Every normal clip has an all-0 audio_label.npy and image_label.npy. Every abnormal clip has at least one 1 cell in image_label.npy and at least one 1 window in audio_label.npy.

Downloads last month: 233

Total file size:

150 MB