bccd

• Description:

BCCD Dataset is a small-scale dataset for blood cells detection.

Thanks the original data and annotations from cosmicad and akshaylamba. The original dataset is re-organized into VOC format. BCCD Dataset is under MIT licence.

Data preparation is important to use machine learning. In this project, the Faster R-CNN algorithm from keras-frcnn for Object Detection is used. From this dataset, nicolaschen1 developed two Python scripts to make preparation data (CSV file and images) for recognition of abnormalities in blood cells on medical images.

export.py: it creates the file "test.csv" with all data needed: filename, class_name, x1,y1,x2,y2. plot.py: it plots the boxes for each image and save it in a new directory.

Image Type : jpeg(JPEG) Width x Height : 640 x 480

• Additional Documentation: Explore on Papers With Code north_east

• Homepage: https://github.com/Shenggan/BCCD_Dataset

• Source code: tfds.datasets.bccd.Builder

• Versions:

  • 1.0.0 (default): No release notes.

• Download size: 7.51 MiB

• Dataset size: 7.34 MiB

• Auto-cached (documentation): Yes

• Splits:

• Feature structure:

FeaturesDict({
    'image': Image(shape=(480, 640, 3), dtype=uint8),
    'image/filename': Text(shape=(), dtype=string),
    'objects': Sequence({
        'bbox': BBoxFeature(shape=(4,), dtype=float32),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=3),
    }),
})

• Feature documentation:

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

• Citation:

@ONLINE {BCCD_Dataset,
    author = "Shenggan",
    title  = "BCCD Dataset",
    year   = "2017",
    url    = "https://github.com/Shenggan/BCCD_Dataset"
}