language:en license:mit size_categories:10K<n<100K modality:image region:us
---
license: mit
language:
- en
size_categories:
- 10K<n<100K
---
# 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

<!-- This section describes suitable use cases for the dataset. -->
Liquid height estimation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->
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

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
DTLD was collected using the Intel Realsense D435 depth camera.

#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
 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

zhongry17@gmail.com