The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label DLTD@269a57fa32bdc9e78bddc75885a851027ff617aa
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 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2240, in __iter__
example = _apply_feature_types_on_example(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2157, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2152, in encode_example
return encode_nested_example(self, example)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1437, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1143, in encode_example
example_data = self.str2int(example_data)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1080, in str2int
output = [self._strval2int(value) for value in values]
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1101, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label DLTD@269a57fa32bdc9e78bddc75885a851027ff617aaNeed 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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