watershed added

src/methods_segmentation/watershed/config.vsh.yaml

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+name: watershed
+label: "watershed Segmentation"
+summary: "Output of the segmantation methot watershed"
+description: "Output of the segmantation methot watershed"
+links:
+  documentation: "https://github.com/theislab/txsim"
+  repository: "https://github.com/BennyStrobes/Watershed"
+references:
+  doi: "10.1109/34.87344"
+
+
+__merge__: /src/api/comp_method_segmentation.yaml 
+
+arguments:
+- name: --normalize_func
+  type: string
+  default: "gamma"
+- name: --normalize_gamma
+  type: integer
+  default: 1
+- name: --normalize_gain
+  type: integer
+  default: 1
+- name: --normalize_inv
+  type: boolean
+  default: False
+- name: --normalize_cutoff
+  type: double
+  default: 0.5
+- name: --contrast_adjustment_func
+  type: string
+  default: "equalize_adapthist"
+- name: --contrast_adjustment_kernel_size
+  type: string
+  default: "None"
+- name: --contrast_adjustment_clip_limit
+  type: double
+  default: 0.01
+- name: --contrast_adjustment_nbins
+  type: integer
+  default: 256
+- name: --contrast_adjustment_mask
+  type: string
+  default: "None"
+- name: --contrast_adjustment_in_range
+  type: string
+  default: "image"
+- name: --contrast_adjustment_out_range
+  type: string
+  default: "dtype"
+- name: --blur_func
+  type: string
+  default: "gaussian"
+- name: --blur_sigma
+  type: integer
+  default: 1
+- name: --blur_output
+  type: string
+  default: "None"
+- name: --blur_mode
+  type: string
+  default: "nearest"
+- name: --blur_cval
+  type: double
+  default: 0.0
+- name: --blur_preserve_range
+  type: boolean
+  default: False
+- name: --blur_truncate #keep as double
+  type: double
+  default: 4.0
+- name: --threshold_func
+  type: string
+  default: "local_otsu"
+- name: --threshold_nbins
+  type: integer
+  default: 256
+- name: --threshold_hist
+  type: string
+  default: "None"
+- name: --threshold_out
+  type: string
+  default: "None"
+- name: --threshold_mask
+  type: string
+  default: "None"
+- name: --threshold_shift_x
+  type: boolean
+  default: False
+- name: --threshold_shift_y
+  type: boolean
+  default: False
+- name: --threshold_shift_z
+  type: boolean
+  default: False
+- name: --threshold_footprint
+  type: string
+  default: "square"
+- name: --threshold_footprint_size
+  type: integer
+  default: 50
+- name: --distance_transform_func
+  type: string
+  default: "distance_transform_edt"
+- name: --distance_transform_sampling
+  type: string
+  default: "None"
+- name: --distance_transform_return_distances
+  type: boolean
+  default: True
+- name: --distance_transform_return_indices
+  type: boolean
+  default: False
+- name: --distance_transform_distances
+  type: string
+  default: "None"
+- name: --distance_transform_indices
+  type: string
+  default: "None"
+- name: --local_maxima_func
+  type: string
+  default: "find_local_maxima"
+- name: --local_maxima_min_distance
+  type: integer
+  default: 5
+- name: --post_processing_func_1
+  type: string
+  default: "remove_small_objects"
+- name: --post_processing_min_size_1
+  type: integer
+  default: 64
+- name: --post_processing_connectivity_1
+  type: integer
+  default: 1
+- name: --post_processing_out_1
+  type: string
+  default: "None"
+- name: --post_processing_func_2
+  type: string
+  default: "remove_small_holes"
+- name: --post_processing_area_threshold_2
+  type: integer
+  default: 64
+- name: --post_processing_connectivity_2
+  type: integer
+  default: 1
+- name: --post_processing_out_2
+  type: string
+  default: "None"
+- name: --bg_intensity_filter_bg_factor
+  type: double
+  default: 0.3
+- name: --bg_intensity_filter_window_size
+  type: integer
+  default: 1000
+- name: --bg_intensity_filter_bg_size
+  type: integer
+  default: 2000
+
+resources:
+  - type: python_script
+    path: script.py
+
+engines:
+  - type: docker
+    image: openproblems/base_python:1.0.0
+    setup:
+      - type: python
+        pypi: spatialdata
+    __merge__: 
+      - /src/base/setup_txsim_partial.yaml
+  - type: native
+
+runners:
+  - type: executable
+  - type: nextflow
+    directives:
+      label: [ midtime, lowcpu, lowmem ]
+

src/methods_segmentation/watershed/script.py

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+import txsim as tx
+import numpy as np
+import os
+import yaml
+import spatialdata as sd
+import anndata as ad
+import shutil
+import numpy as np
+from spatialdata.models import Labels2DModel
+import xarray as xr
+
+
+def convert_to_lower_dtype(arr):
+    max_val = arr.max()
+    if max_val <= np.iinfo(np.uint8).max:
+        new_dtype = np.uint8
+    elif max_val <= np.iinfo(np.uint16).max:
+        new_dtype = np.uint16
+    elif max_val <= np.iinfo(np.uint32).max:
+        new_dtype = np.uint32
+    else:
+        new_dtype = np.uint64
+
+    return arr.astype(new_dtype)
+
+## VIASH START
+par = {
+  "input": "../task_ist_preprocessing/resources_test/common/2023_10x_mouse_brain_xenium/dataset.zarr",
+  "output": "segmentation.zarr"
+}
+
+## VIASH END
+
+hyperparameters = par.copy()
+
+hyperparameters = {k:(v if v != "None" else None) for k,v in hyperparameters.items()}
+del hyperparameters['input']
+del hyperparameters['output']
+
+sdata = sd.read_zarr(par["input"])
+image = sdata['morphology_mip']['scale0'].image.compute().to_numpy()
+transformation = sdata['morphology_mip']['scale0'].image.transform.copy()
+
+sd_output = sd.SpatialData()
+image = sdata['morphology_mip']['scale0'].image.compute().to_numpy()
+transformation = sdata['morphology_mip']['scale0'].image.transform.copy()
+img_arr = tx.preprocessing.segment_watershed(image[0], hyperparameters) 
+image = convert_to_lower_dtype(img_arr)
+data_array = xr.DataArray(image, name=f'segmentation', dims=('y', 'x'))
+parsed_data = Labels2DModel.parse(data_array, transformations=transformation)
+sd_output.labels['segmentation'] = parsed_data
+
+print("Writing output", flush=True)
+if os.path.exists(par["output"]):
+  shutil.rmtree(par["output"])
+sd_output.write(par["output"])
+