🧑💻 pre-commit autoupdate #916
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updates: - [github.com/astral-sh/ruff-pre-commit: v0.9.4 → v0.9.9](astral-sh/ruff-pre-commit@v0.9.4...v0.9.9)
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shaneahmed
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Mar 4, 2025
mbasheer04
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Mar 27, 2025
Removing large files Removing unneccessary files Fixing pre-commit [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci Fixing PR issues :technologist: pre-commit autoupdate (TissueImageAnalytics#910) * 🧑💻 pre-commit autoupdate updates: - [github.com/executablebooks/mdformat: 0.7.21 → 0.7.22](hukkin/mdformat@0.7.21...0.7.22) - [github.com/astral-sh/ruff-pre-commit: v0.8.6 → v0.9.4](astral-sh/ruff-pre-commit@v0.8.6...v0.9.4) * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * 📌 Update `ruff` dependency * 🔥 TIAToolbox does not support Python > 3.12 yet - There is no need for this check as this will be tested while upgrading to Python 3.13 * ♻️ Refactor `typing` to `type_hints`. * 🐛 Fix `mypy` workflow --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Shan E Ahmed Raza <[email protected]> 📝 Update Documentation Structure (TissueImageAnalytics#909) - Use `Python 3.12` for docs build - Update `copyright` year to `2025` - Landing page now shows text from README - Update documentation structure - Update `readthedocs` Build - Remove `usage.rst` - Rename Jupyter Notebooks to Usage Examples - Show README for Usage Examples instead of TOC - Reduce TOC depth for basic functionalities and pipelines - Improve `README` quality. 🐛 Fix in `test_arch_mapde` and `test_arch_sccnn` (TissueImageAnalytics#911) - If cuda is available model should be moved to cuda otherwise tests will fail as test data is moved to cuda. [skip ci] 📝 Improve Documentation (TissueImageAnalytics#913) - Update CONTRIBUTING.rst - Bug fix in conf.py to fix notebook links - Update `examples/README.md` - Update `docs/installation.rst` - Update `docs/visualization.rst` --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: adamshephard <[email protected]> :bug: Fix `MapDe` `dist_filter` Shape (TissueImageAnalytics#914) - Fix `dist_filter` in `MapDe` model for multi-class output. Explanation: Previously, if we set `num_class` to more than 1, the model would still output 1 channel. This was because the `dist_filter` always had size of 1 in its first dimension, however the first dimension determines the number of output channels in the tensor produced by `torch.functional.F.conv2d`. This PR changes this by repeating the filters the match the number of output classes. :technologist: pre-commit autoupdate (TissueImageAnalytics#916) * 🧑💻 pre-commit autoupdate updates: - [github.com/astral-sh/ruff-pre-commit: v0.9.4 → v0.9.9](astral-sh/ruff-pre-commit@v0.9.4...v0.9.9) * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * 🔨 Update `ruff` version * 🔨 Update noqa for Unused static method argument --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Shan E Ahmed Raza <[email protected]> Add FsspecJsonWSIReader class. (TissueImageAnalytics#897) The `FsspecJsonWSIReader` reads fsspec json file which represents SVS or TIFF whole slide image. The images are accessible by HTTP range requests, eg: `https://api.gdc.cancer.gov/data/73c69d24-6f9e-44e2-bfe5-a608d4cf5c27` The whole image can be downloaded like: `curl -C - -o TCGA-22-1017-01Z-00-DX1.9562FE79-A261-42D3-B394-F3E0E2FF7DDA.svs https://api.gdc.cancer.gov/data/73c69d24-6f9e-44e2-bfe5-a608d4cf5c27` The `FsspecJsonWSIReader` class has a `_zarr_store` field which is created by reading json file using `fsspec`: ``` mapper = fsspec.get_mapper( "reference://", fo=str(input_img), target_protocol="file" ) self._zarr_array = zarr.open(mapper, mode="r") self._zarr_store = self._zarr_array.store self._zarr_lru_cache = zarr.LRUStoreCache(self._zarr_store, max_size=cache_size) self._zarr_group = zarr.open(self._zarr_lru_cache) ``` This is equivalent to `TIFFWSIReader` code: ``` self._zarr_store = tifffile.imread( self.input_path, series=self.series_n, aszarr=True, ) self._zarr_lru_cache = zarr.LRUStoreCache(self._zarr_store, max_size=cache_size) self._zarr_group = zarr.open(self._zarr_lru_cache) ``` Both FsspecJsonWSIReader and TIFFWSIReader forward calls to `read_bounds` and `read_rect` methods of the`TIFFWSIReaderDelegate` delegate instance. The method `_info` of the`TIFFWSIReaderDelegate` reads SVS metadata which is stored in the root group metadata like: ``` { ".zattrs": { "multiscales": [ { "metadata": { "objective_power": 40, "vendor": "Aperio", "mpp": [0.2525, 0.2525] } } ] } } ``` To test, execute from the root dir: ``` pip install -r requirements/requirements_dev.txt mkdir -p samples/slides mkdir -p samples/fsspec cd samples/slides curl -C - -o TCGA-22-1017-01Z-00-DX1.9562FE79-A261-42D3-B394-F3E0E2FF7DDA.svs https://api.gdc.cancer.gov/data/73c69d24-6f9e-44e2-bfe5-a608d4cf5c27 cd ../../ cp tiatoolbox/utils/tiff_to_fsspec.py . python tiff_to_fsspec.py "samples/slides/TCGA-22-1017-01Z-00-DX1.9562FE79-A261-42D3-B394-F3E0E2FF7DDA.svs" "samples/fsspec/73c69d24-6f9e-44e2-bfe5-a608d4cf5c27_fsspec.json" "https://api.gdc.cancer.gov/data/73c69d24-6f9e-44e2-bfe5-a608d4cf5c27" ``` Create `tileserver.py` inside of the project root: ``` from flask_cors import CORS from tiatoolbox.visualization import TileServer from tiatoolbox.wsicore.wsireader import FsspecJsonWSIReader wsi = FsspecJsonWSIReader.open( "./samples/fsspec/73c69d24-6f9e-44e2-bfe5-a608d4cf5c27_fsspec.json" ) tile_server = TileServer( title="Tiatoolbox TileServer", layers={"layer": wsi}, ) CORS(tile_server, send_wildcard=True) tile_server.run(host="127.0.0.1", port=5000) ``` Open `http://127.0.0.1:5000/` and verify that it works. --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Shan E Ahmed Raza <[email protected]> ✨ Support for Additional Foundation Models (TissueImageAnalytics#906) - Add support for additional foundation models as feature extractors using the TimmBackbone. - Added models include: UNI2, Virchow, Virchow2, kaiko and H-optimus-1. - Add more information to docstrings. - Allow foundation models with additional parameters. --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Shan E Ahmed Raza <[email protected]> Fixing PR issues
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updates: