diff run-superdsm.py @ 2:7fcd96cf0d52 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/superdsm/ commit 597cb3dc531963d02c5db0e4fc2596fcb06728dd

--- a/run-superdsm.py	Thu Jul 06 00:01:07 2023 +0000
+++ b/run-superdsm.py	Wed Dec 17 22:28:28 2025 +0000
@@ -7,38 +7,35 @@
 """
 
 import argparse
+import csv
 import imghdr
 import os
 import pathlib
 import shutil
 import tempfile
 
-import ray
-import superdsm.automation
-import superdsm.io
-import superdsm.render
-
 
 hyperparameters = [
     ('AF_scale', float),
-    ('c2f_region_analysis/min_atom_radius', float),
-    ('c2f_region_analysis_min_norm_energy_improvement', float),
-    ('c2f_region_analysis_max_atom_norm_energy', float),
-    ('c2f_region_analysis_max_cluster_marker_irregularity', float),
-    ('dsm_alpha', float),
-    ('dsm_AF_alpha', float),
-    ('global_energy_minimization_betai', float),
-    ('global_energy_minimization_AF_beta', float),
-    ('postprocess_mask_max_distance', int),
-    ('postprocess_mask_stdamp', float),
-    ('postprocess_max_norm_energy', float),
-    ('postprocess_min_contrast', float),
-    ('postprocess_min_object_radius', float),
+    ('c2f-region-analysis/min_atom_radius', float),
+    ('c2f-region-analysis/min_norm_energy_improvement', float),
+    ('c2f-region-analysis/max_atom_norm_energy', float),
+    ('c2f-region-analysis/max_cluster_marker_irregularity', float),
+    ('dsm/alpha', float),
+    ('dsm/AF_alpha', float),
+    ('global-energy-minimization/pruning', str),
+    ('global-energy-minimization/beta', float),
+    ('global-energy-minimization/AF_beta', float),
+    ('postprocess/mask_max_distance', int),
+    ('postprocess/mask_stdamp', float),
+    ('postprocess/max_norm_energy', float),
+    ('postprocess/min_contrast', float),
+    ('postprocess/min_object_radius', float),
 ]
 
 
 def get_param_name(key):
-    return key.replace('/', '_')
+    return key.replace('/', '_').replace('-', '_')
 
 
 def create_config(args):
@@ -50,14 +47,25 @@
     return cfg
 
 
+def flatten_dict(d, sep='/'):
+    result = {}
+    for key, val in d.items():
+        if isinstance(val, dict):
+            for sub_key, sub_val in flatten_dict(val, sep=sep).items():
+                result[f'{key}{sep}{sub_key}'] = sub_val
+        else:
+            result[key] = val
+    return result
+
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description='Segmentation of cell nuclei in 2-D fluorescence microscopy images')
-    parser.add_argument('image', help='Path to the input image')
-    parser.add_argument('cfg', help='Path to the file containing the configuration')
-    parser.add_argument('masks', help='Path to the file containing the segmentation masks')
-    parser.add_argument('overlay', help='Path to the file containing the overlay of the segmentation results')
-    parser.add_argument('seg_border', type=int)
+    parser.add_argument('image', type=str, help='Path to the input image')
     parser.add_argument('slots', type=int)
+    parser.add_argument('--do-masks', type=str, default=None, help='Path to the file containing the segmentation masks')
+    parser.add_argument('--do-cfg', type=str, default=None, help='Path to the file containing the configuration')
+    parser.add_argument('--do-overlay', type=str, default=None, help='Path to the file containing the overlay of the segmentation results')
+    parser.add_argument('--do-overlay-border', type=int)
     for key, ptype in hyperparameters:
         parser.add_argument('--' + get_param_name(key), type=ptype, default=None)
     args = parser.parse_args()
@@ -71,26 +79,54 @@
 
     os.environ['MKL_NUM_THREADS'] = str(num_threads_per_process)
     os.environ['OPENBLAS_NUM_THREADS'] = str(num_threads_per_process)
-    os.environ['MKL_DEBUG_CPU_TYPE'] = '5'
+
+    import giatools.io
+    import ray
+    import superdsm.automation
+    import superdsm.io
+    import superdsm.render
 
-    ray.init(num_cpus=num_processes, log_to_driver=True)
+    # The explicit `dir` and `prefix` is to avoid breaking the 107 byte limit for socket paths in Biocontainers
+    # See for details: https://github.com/BMCV/galaxy-image-analysis/pull/178
+    with tempfile.TemporaryDirectory(dir='/tmp', prefix='superdsm') as tmpdirname:
+        tmpdir = pathlib.Path(tmpdirname)
+        ray.init(num_cpus=num_processes, log_to_driver=True, _temp_dir=str(tmpdir / 'ray'))
 
-    with tempfile.TemporaryDirectory() as tmpdirname:
-        tmpdir = pathlib.Path(tmpdirname)
         img_ext = imghdr.what(args.image)
         img_filepath = tmpdir / f'input.{img_ext}'
         shutil.copy(str(args.image), img_filepath)
 
         pipeline = superdsm.pipeline.create_default_pipeline()
         cfg = create_config(args)
-        img = superdsm.io.imread(img_filepath)
-        data, cfg, _ = superdsm.automation.process_image(pipeline, cfg, img)
+        img = giatools.io.imread(img_filepath, impl=superdsm.io.imread)
 
-        with open(args.cfg, 'w') as fp:
-            cfg.dump_json(fp)
+        # Create configuration if it is required:
+        if args.do_cfg or args.do_overlay or args.do_masks:
+            cfg, _ = superdsm.automation.create_config(pipeline, cfg, img)
+
+        # Perform segmentation if it is required:
+        if args.do_overlay or args.do_masks:
+            print('Performing segmentation')
+            data, cfg, _ = pipeline.process_image(img, cfg)
 
-        overlay = superdsm.render.render_result_over_image(data, border_width=args.seg_border, normalize_img=False)
-        superdsm.io.imwrite(args.overlay, overlay)
+        # Write configuration used for segmentation, or the automatically created one, otherwise:
+        if args.do_cfg:
+            print(f'Writing config to: {args.do_cfg}')
+            with open(args.do_cfg, 'w') as fp:
+                tsv_out = csv.writer(fp, delimiter='\t')
+                tsv_out.writerow(['Hyperparameter', 'Value'])
+                rows = sorted(flatten_dict(cfg.entries).items(), key=lambda item: item[0])
+                for key, value in rows:
+                    tsv_out.writerow([key, value])
 
-        masks = superdsm.render.rasterize_labels(data)
-        superdsm.io.imwrite(args.masks, masks)
+        # Write the overlay image:
+        if args.do_overlay:
+            print(f'Writing overlay to: {args.do_overlay}')
+            overlay = superdsm.render.render_result_over_image(data, border_width=args.do_overlay_border, normalize_img=False)
+            superdsm.io.imwrite(args.do_overlay, overlay)
+
+        # Write the label map:
+        if args.do_masks:
+            print(f'Writing masks to: {args.do_masks}')
+            masks = superdsm.render.rasterize_labels(data)
+            superdsm.io.imwrite(args.do_masks, masks)