Update the cooper scripts

Author: constantinpape

scripts/cooper/README.md

@@ -19,9 +19,9 @@ $ micromamba activate sam
 The segmentation scripts (`run_..._segmentation.py`) all work similarly and can either run segmentation for a single mrc file or for all mrcs in a folder structure.
 For example, you can run vesicle segmentation like this:
 ```
-$ python run_vesicle_segmentation.py -i /path/to/input_folder -o /path/to/output_folder -m /path/to/vesicle_model.pt
+$ python run_vesicle_segmentation.py -i /path/to/input_folder -o /path/to/output_folder
 ```
-The filepath after `-i` specifices the location of the folder with the mrcs to be segmented, the segmentation results will be stored (as tifs) in the folder following `-o` and `-m` is used to specify the path to the segmentation model.
+The filepath after `-i` specifices the location of the folder with the mrcs to be segmented and the segmentation results will be stored (as tifs) in the folder following `-o`.
 To segment vesicles with an additional mask, you can use the `--mask_path` option.
 
 The segmentation scripts accept additional parameters, e.g. `--force` to overwrite existing segmentations in the output folder (by default these are skipped to avoid unnecessary computation) and `--tile_shape <TILE_Z> <TILE_Y> <TILE_X>` to specify a different tile shape (which may be necessary to avoid running out of GPU memory).

scripts/cooper/run_compartment_segmentation.py

@@ -2,13 +2,20 @@
 from functools import partial
 
 from synapse_net.inference.compartments import segment_compartments
+from synapse_net.inference.inference import get_model_path
 from synapse_net.inference.util import inference_helper, parse_tiling
 
 
 def run_compartment_segmentation(args):
     tiling = parse_tiling(args.tile_shape, args.halo)
+
+    if args.model is None:
+        model_path = get_model_path("compartments")
+    else:
+        model_path = args.model
+
     segmentation_function = partial(
-        segment_compartments, model_path=args.model_path, verbose=False, tiling=tiling, scale=[0.25, 0.25, 0.25]
+        segment_compartments, model_path=model_path, verbose=False, tiling=tiling, scale=[0.25, 0.25, 0.25]
     )
     inference_helper(
         args.input_path, args.output_path, segmentation_function, force=args.force, data_ext=args.data_ext
@@ -26,7 +33,7 @@ def main():
         help="The filepath to directory where the segmentation will be saved."
     )
     parser.add_argument(
-        "--model_path", "-m", required=True, help="The filepath to the compartment model."
+        "--model", "-m", help="The filepath to the compartment model."
     )
     parser.add_argument(
         "--force", action="store_true",

scripts/cooper/run_mitochondria_segmentation.py

@@ -2,13 +2,19 @@
 from functools import partial
 
 from synapse_net.inference.mitochondria import segment_mitochondria
+from synapse_net.inference.inference import get_model_path
 from synapse_net.inference.util import inference_helper, parse_tiling
 
 
 def run_mitochondria_segmentation(args):
+    if args.model is None:
+        model_path = get_model_path("mitochondria")
+    else:
+        model_path = args.model
+
     tiling = parse_tiling(args.tile_shape, args.halo)
     segmentation_function = partial(
-        segment_mitochondria, model_path=args.model_path, verbose=False, tiling=tiling, scale=[0.5, 0.5, 0.5]
+        segment_mitochondria, model_path=model_path, verbose=False, tiling=tiling, scale=[0.5, 0.5, 0.5]
     )
     inference_helper(
         args.input_path, args.output_path, segmentation_function,
@@ -27,7 +33,7 @@ def main():
         help="The filepath to directory where the segmentation will be saved."
     )
     parser.add_argument(
-        "--model_path", "-m", required=True, help="The filepath to the mitochondria model."
+        "--model", "-m", help="The filepath to the mitochondria model."
     )
     parser.add_argument(
         "--force", action="store_true",

scripts/cooper/run_vesicle_segmentation.py

@@ -2,13 +2,19 @@
 from functools import partial
 
 from synapse_net.inference.vesicles import segment_vesicles
+from synapse_net.inference.inference import get_model_path
 from synapse_net.inference.util import inference_helper, parse_tiling
 
 
 def run_vesicle_segmentation(args):
+    if args.model is None:
+        model_path = get_model_path("vesicles_3d")
+    else:
+        model_path = args.model
+
     tiling = parse_tiling(args.tile_shape, args.halo)
     segmentation_function = partial(
-        segment_vesicles, model_path=args.model_path, verbose=False, tiling=tiling,
+        segment_vesicles, model_path=model_path, verbose=False, tiling=tiling,
         exclude_boundary=not args.include_boundary
     )
     inference_helper(
@@ -28,7 +34,7 @@ def main():
         help="The filepath to directory where the segmentations will be saved."
     )
     parser.add_argument(
-        "--model_path", "-m", required=True, help="The filepath to the vesicle model."
+        "--model_path", "-m", help="The filepath to the vesicle model."
     )
     parser.add_argument(
         "--mask_path", help="The filepath to a tif file with a mask that will be used to restrict the segmentation."