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---
dataset_info:
features:
- name: image_id
dtype: string
- name: image
dtype: image
- name: annotations
struct:
- name: image
dtype: string
- name: prefix
dtype: string
- name: suffix
dtype: string
splits:
- name: train
num_bytes: 5485463
num_examples: 255
- name: test
num_bytes: 769705
num_examples: 36
- name: validation
num_bytes: 1564659
num_examples: 73
download_size: 7720170
dataset_size: 7819827
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
license: cc-by-4.0
---
# Dataset Card for roboflow-bccd-florrence2
## Dataset Description
- **Repository:** https://huggingface.co/datasets/dwb2023/roboflow-bccd-florence2
- **Paper:** https://arxiv.org/pdf/2311.06242
### Dataset Summary
This dataset, roboflow-bccd-paligemma, is a modified version of the BCCD (Blood Cell Count and Detection) dataset. It contains blood cell images annotated for object detection tasks, specifically targeting three types of blood cells:
1. Platelets
2. Red Blood Cells (RBC)
3. White Blood Cells (WBC)
Key features of the dataset:
- Total of 364 annotated images across train, validation, and test splits
- Bounding box annotations for each detected cell
- Labels identifying the cell types
The dataset is structured to support object detection tasks in the medical imaging domain, particularly for blood cell analysis.
It's crucial to note that this dataset is a derivative work based on the original BCCD dataset. When using this dataset, proper attribution is essential. Please use the citation provided at the end of this card in any work that utilizes this data.
### Supported Tasks and Leaderboards
- **Tasks:** Object Detection
### Languages
The dataset uses English labels.
## Dataset Structure
### Data Instances
A typical data instance contains:
- An image of blood cells
- Bounding box annotations for detected cells
- Labels identifying the cell types (Platelets, RBC, WBC)
### Data Fields
- `image_id`: Unique identifier for each image
- `image`: The blood cell image
- `annotations`: Contains annotation details
The `annotations` field has the following structure:
| Field Name | Description | Data Type |
|------------|-------------|-----------|
| image | Identifier for the image being annotated | string |
| prefix | Standard prefix for all annotations, typically "detect Platelets ; RBC ; WBC" | string |
| suffix | Contains the actual annotation data, including bounding box coordinates and cell type labels | string |
The `suffix` field contains multiple annotations for each image, separated by semicolons. Each annotation typically follows this format:
`CellType<loc_x1><loc_y1><loc_x2><loc_y2>`
Where:
- `<loc_x1><loc_y1><loc_x2><loc_y2>` represent the bounding box coordinates
- `CellType` is one of: RBC, WBC, or Platelets
Example of a complete annotation:
```
{
"image": "BloodImage_00343_jpg.rf.d8c56063ce5e40c50efb00a7e0c83c3b.jpg",
"prefix": "<OD>",
"suffix": "RBC<loc_756><loc_406><loc_958><loc_631>RBC<loc_820><loc_623><loc_995><loc_825>RBC<loc_150><loc_327><loc_355><loc_508>RBC<loc_283><loc_685><loc_283><loc_685>RBC<loc_400><loc_417><loc_588><loc_640>RBC<loc_817><loc_2><loc_999><loc_248>RBC<loc_50><loc_10><loc_208><loc_204>RBC<loc_206><loc_46><loc_314><loc_302>RBC<loc_528><loc_677><loc_670><loc_925>Platelets<loc_2><loc_752><loc_75><loc_854>Platelets<loc_109><loc_429><loc_184><loc_531>WBC<loc_286><loc_2><loc_664><loc_319>"
}
```
### Data Splits
The dataset is divided into three splits:
- Train: 255 images
- Validation: 73 images
- Test: 36 images
## Considerations for Using the Data
### Social Impact of Dataset
This dataset could potentially aid in automating blood cell counting and classification, which may improve efficiency in medical diagnostics. However, as with any medical-related AI application, care must be taken to ensure accuracy and proper validation before clinical use.
## Additional Information
### Licensing Information
This dataset is licensed under Apache 2.0.
### Citation Information
If you use this dataset in your research, please cite it as:
```
@misc{
bccd-ouzjz_dataset,
title = { bccd Dataset },
type = { Open Source Dataset },
author = { Roboflow 100 },
howpublished = { \url{ https://universe.roboflow.com/roboflow-100/bccd-ouzjz } },
url = { https://universe.roboflow.com/roboflow-100/bccd-ouzjz },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { may },
note = { visited on 2024-08-02 },
}
``` |