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

BCCD Dataset

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.

You can download the .rec format for mxnet directly. The .rec file can be load by mxnet.image.ImageDetIter.

Overview of dataset

  • You can see a example of the labeled cell image.

    We have three kind of labels :

    • RBC (Red Blood Cell)
    • WBC (White Blood Cell)
    • Platelets (血小板)

    example

  • The structure of the BCCD_dataset

    ├── BCCD
    │   ├── Annotations
    │   │       └── BloodImage_00XYZ.xml (364 items)
    │   ├── ImageSets       # Contain four Main/*.txt which split the dataset
    │   └── JPEGImages
    │       └── BloodImage_00XYZ.jpg (364 items)
    ├── dataset
    │   └── mxnet           # Some preprocess scripts for mxnet
    ├── scripts
    │   ├── split.py        # A script to generate four .txt in ImageSets
    │   └── visualize.py    # A script to generate labeled img like example.jpg
    ├── example.jpg         # A example labeled img generated by visualize.py
    ├── LICENSE
    └── README.md
    
  • The JPEGImages:

    • Image Type : jpeg(JPEG)
    • Width x Height : 640 x 480
  • The Annotations : The VOC format .xml for Object Detection, automatically generate by the label tools. Below is an example of .xml file.

    <annotation>
    	<folder>JPEGImages</folder>
    	<filename>BloodImage_00000.jpg</filename>
    	<path>/home/pi/detection_dataset/JPEGImages/BloodImage_00000.jpg</path>
    	<source>
    		<database>Unknown</database>
    	</source>
    	<size>
    		<width>640</width>
    		<height>480</height>
    		<depth>3</depth>
    	</size>
    	<segmented>0</segmented>
    	<object>
    		<name>WBC</name>
    		<pose>Unspecified</pose>
    		<truncated>0</truncated>
    		<difficult>0</difficult>
    		<bndbox>
    			<xmin>260</xmin>
    			<ymin>177</ymin>
    			<xmax>491</xmax>
    			<ymax>376</ymax>
    		</bndbox>
    	</object>
        ...
    	<object>
    		...
    	</object>
    </annotation>
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