Updated use-case figures

Author: constantinpape

case2/README.md

@@ -43,3 +43,21 @@ And images of application in QuPath:
 
 See the result of stardist applied in deepImageJ
 <img src="images/deepimagej_stardist.png" alt="drawing" width="1200"/>
+
+
+## Apply the model in stardist python
+
+- `run_stardist_python.py`
+
+<img src="images/stardist-python.png" alt="drawing" width="1200"/>
+
+
+## Apply the model in zero-cost
+
+- Open the stardist 2d notebook: https://colab.research.google.com/github/esgomezm/ZeroCostDL4Mic/blob/master/Colab_notebooks/BioImage.io%20notebooks/StarDist_2D_ZeroCostDL4Mic_BioImageModelZoo_export.ipynb
+    - will be on the main zero cost once https://github.com/HenriquesLab/ZeroCostDL4Mic/pull/181 is merged
+- Start the notebook and go to `Loading weights from a pre-trained notebook`
+    - Select `pretrained_model_choice: BioImage Model Zoo`
+    - Enter the doi (10.5281/zenodo.6338614) in `bioimageio_model`
+- Go to `Error mapping and quality metrics estimation` to run the model on data from your google drive
+    - TODO: still need to do this, can't load the model right now because zenodo is down

case2/images/stardist-python.png

@@ -0,0 +1,38 @@
+import os
+from pathlib import Path
+
+import imageio
+import stardist
+import napari
+from csbdeep.utils import normalize
+from stardist.models import StarDist2D
+
+
+def run_stardist(image, scale=2):
+
+    # download the H&E stardist model from bioimage.io
+    model_doi = "10.5281/zenodo.6338614"
+    model_folder = Path("./he-model-pretrained")
+    if not os.path.exists(model_folder):
+        stardist.import_bioimageio(model_doi, model_folder)
+    model = StarDist2D(None, model_folder.name, model_folder.parent)
+
+    # prepare the image and run prediction with stardist
+    input_ = normalize(image, 1.0, 99.8)
+    nuclei, _ = model.predict_instances(input_, scale=2)
+    return nuclei
+
+
+def main():
+    input_path = "/home/pape/Work/data/lizard/train_images/consep_13.png"
+    image = imageio.imread(input_path)
+    nuclei = run_stardist(image)
+
+    v = napari.Viewer()
+    v.add_image(image)
+    v.add_labels(nuclei)
+    napari.run()
+
+
+if __name__ == "__main__":
+    main()