Published January 10, 2021
| Version v2
Dataset
Open
HPA Cell Image Segmentation Dataset
- 1. Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
Contributors
Data curators:
- 1. Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
Description
This deposition contains an annotated image segmentation datasets and pretrained models.
This dataset includes annotated cell images obtained from the Human Protein Atlas (http://www.proteinatlas.org), each image contains 4 channels (Microtubules, ER, Nuclei and Protein of Interest). The cells in each image are annotated with polygons and saved into GeoJSON format produced with Kaibu(https://kaibu.org) annotation tool.
- hpa_cell_segmentation_dataset_v2_512x512_4train_159test.zip is an example dataset for running a deep learning-based interactive annotation tools in ImJoy (https://github.com/imjoy-team/imjoy-interactive-segmentation).
- hpa_dataset_v2.zip is a full annotate image segmentation dataset
- other files named *.pth are pytorch model weights which can be loaded via our deep learning library in Python: https://github.com/CellProfiling/HPA-Cell-Segmentation
Files
hpa_cell_segmentation_dataset_v2_512x512_4train_159test.zip
Files
(7.5 GB)
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md5:c6fb97ef29df086a3d7b66c2942e0ab6
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