Camelyon17-Prov-GigaPath-Features
- Citation Author(s):
-
Yonghuang Wu
- Submitted by:
- Yonghuang Wu
- Last updated:
- DOI:
- 10.21227/rgk8-d376
- Data Format:
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- Categories:
- Keywords:
Abstract
Feature extraction on the camelyon 17 dataset (https://camelyon17.grand-challenge.org/Data/) using the tile-level encoder of the Prov-GigaPath model (10.1038/s41586-024-07441-w) and the trident project (https://github.com/mahmoodlab/trident/).
Instructions:
```
h5_file = h5py.File('/path/to/h5_file', 'r')
data = {'features': torch.from_numpy(h5_file['features'][()]), 'coords': torch.from_numpy(h5_file['coords'][()]) }
```
Dataset Files
- The first center (center_0) in camelyon 17 dataset (Size: 2.12 GB)
- The first center (center_1) in camelyon 17 dataset (Size: 4.16 GB)
- The first center (center_2) in camelyon 17 dataset (Size: 4.27 GB)
- The first center (center_3) in camelyon 17 dataset (Size: 3.53 GB)
- The first center (center_4) in camelyon 17 dataset (Size: 3.42 GB)
