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.
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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)
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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
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The
JPEGImages
:- Image Type : jpeg(JPEG)
- Width x Height : 640 x 480
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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>