The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label DLTD@4bd98f54fd2015ec9ffde663c6bf5f719dda641a
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2543, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2092, in _iter_arrow
pa_table = cast_table_to_features(pa_table, self.features)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2197, in cast_table_to_features
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1795, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1995, in cast_array_to_feature
return feature.cast_storage(array)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1169, in cast_storage
[self._strval2int(label) if label is not None else None for label in storage.to_pylist()]
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1098, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label DLTD@4bd98f54fd2015ec9ffde663c6bf5f719dda641aNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for Dataset Name
The Dual Transparent Liquid Dataset collection utilizes a RealSense D435 stereo depth camera to simultaneously capture RGB and depth data at a resolution of 1280×720 at 30 FPS. It consists of 27,678 images captured in three laboratory scenarios, focusing on four commonly used types of cell culture tubes in biomedical experiments.
Dataset Details
For each frame in the dataset, there is:
A RGB image (1280*720 pixels),
A corresponding depth image (1280*720 pixels),
Annotation.
Dataset Description
The dataset has the following file structure and the annotation files contain the following information:
/path/to/DTLD_dataset/
000000/
rgb/
000000.png
000001.png
…
depth/
000000.png
000001.png
…
mask/
000000_000000.png
000000_000001.png
…
000001_000000.png
000001_000001.png
…
mask_visib/
000000_000000.png
000000_000001.png
…
000001_000000.png
000001_000001.png
…
scene_camera.json
scene_gt.json
scene_gt_info.json
scene_gt_liquid.json
…
000013/
Data Fields
scene_camera.json:
cam_K: Camera intrinsic parameters
cam_R_w2c: Camera rotation from world to camera coordinates.
cam_t_w2c: Camera translation from world to camera coordinates.
depth_scale: Depth scale factor. The depth unit of the depth map is in millimeters.
scene_gt.json:
cam_R_m2c: Camera rotation from model to camera coordinates.
cam_t_m2c: Camera translation from model to camera coordinates.
obj_id: 15: Object identifier (T25 Flask; 16: T75 Flask; 17: T175 Flask; 19: G-rex).
scene_gt_info.json:
bbox_obj: Object bounding box.
bbox_visib: Visible bounding box.
px_count_all: Total pixel count.
px_count_valid: Valid pixel count.
px_count_visib: Visib pixel count.
visib_fract: Visual scale of target object.
scene_gt_liquid.json:
liquid_h: The level of liquid in the container (mm).
liquid_label: Liquid level marked key point pixel position.
Dataset Sources [optional]
- Repository: [More Information Needed]
- Paper [optional]: [More Information Needed]
- Demo [optional]: [More Information Needed]
Uses
The DTLD dataset can be used for various purposes, including but not limited to:
Liquid height estimation
6D pose estimation
Object Segmentation
Direct Use
Liquid height estimation
Curation Rationale
To facilitate the realization of intelligent biopharmaceutical laboratories and assist computers in accurately identifying the liquid level height inside cell culture containers, we have created the DTLD dataset
Data Collection and Processing
DTLD was collected using the Intel Realsense D435 depth camera.
Annotation process
The 6D poses were annotated using the Progresslabeller tool, while the liquid level positions were annotated using the Labelme tool.
Personal and Sensitive Information
None.
Dataset Card Authors
Ruiyun Zhong
Dataset Card Contact
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