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annotate run-superdsm.py @ 1:700ae37e5c69 draft

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planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 7db4b765fa5a1f526cc94cd1f65d963d1e047b27
author imgteam
date Thu, 06 Jul 2023 00:01:18 +0000
parents 1b0fc671187f
children 244f67290d28
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1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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1 """
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2 Copyright 2023 Leonid Kostrykin, Biomedical Computer Vision Group, Heidelberg University.
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3
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4 Distributed under the MIT license.
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5 See file LICENSE for detail or copy at https://opensource.org/licenses/MIT
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6
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7 """
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8
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9 import argparse
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10 import imghdr
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11 import os
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12 import pathlib
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13 import shutil
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14 import tempfile
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16 import ray
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17 import superdsm.automation
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18 import superdsm.io
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19 import superdsm.render
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21
1
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22 hyperparameters = [
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23 ('AF_scale', float),
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24 ('c2f_region_analysis/min_atom_radius', float),
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25 ('c2f_region_analysis_min_norm_energy_improvement', float),
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26 ('c2f_region_analysis_max_atom_norm_energy', float),
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27 ('c2f_region_analysis_max_cluster_marker_irregularity', float),
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28 ('dsm_alpha', float),
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29 ('dsm_AF_alpha', float),
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30 ('global_energy_minimization_betai', float),
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31 ('global_energy_minimization_AF_beta', float),
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32 ('postprocess_mask_max_distance', int),
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33 ('postprocess_mask_stdamp', float),
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34 ('postprocess_max_norm_energy', float),
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35 ('postprocess_min_contrast', float),
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36 ('postprocess_min_object_radius', float),
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37 ]
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38
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39
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40 def get_param_name(key):
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41 return key.replace('/', '_')
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42
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43
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44 def create_config(args):
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45 cfg = superdsm.config.Config()
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46 for key, _ in hyperparameters:
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47 value = getattr(args, get_param_name(key))
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48 if value is not None:
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49 cfg[key] = value
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50 return cfg
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51
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52
0
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53 if __name__ == "__main__":
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54 parser = argparse.ArgumentParser(description='Segmentation of cell nuclei in 2-D fluorescence microscopy images')
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55 parser.add_argument('image', help='Path to the input image')
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56 parser.add_argument('cfg', help='Path to the file containing the configuration')
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57 parser.add_argument('masks', help='Path to the file containing the segmentation masks')
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58 parser.add_argument('overlay', help='Path to the file containing the overlay of the segmentation results')
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59 parser.add_argument('seg_border', type=int)
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60 parser.add_argument('slots', type=int)
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61 for key, ptype in hyperparameters:
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62 parser.add_argument('--' + get_param_name(key), type=ptype, default=None)
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63 args = parser.parse_args()
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64
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65 if args.slots >= 2:
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66 num_threads_per_process = 2
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67 num_processes = args.slots // num_threads_per_process
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68 else:
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69 num_threads_per_process = 1
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70 num_processes = 1
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71
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72 os.environ['MKL_NUM_THREADS'] = str(num_threads_per_process)
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73 os.environ['OPENBLAS_NUM_THREADS'] = str(num_threads_per_process)
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74 os.environ['MKL_DEBUG_CPU_TYPE'] = '5'
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75
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76 ray.init(num_cpus=num_processes, log_to_driver=True)
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77
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78 with tempfile.TemporaryDirectory() as tmpdirname:
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79 tmpdir = pathlib.Path(tmpdirname)
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80 img_ext = imghdr.what(args.image)
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81 img_filepath = tmpdir / f'input.{img_ext}'
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82 shutil.copy(str(args.image), img_filepath)
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83
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84 pipeline = superdsm.pipeline.create_default_pipeline()
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85 cfg = create_config(args)
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86 img = superdsm.io.imread(img_filepath)
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87 data, cfg, _ = superdsm.automation.process_image(pipeline, cfg, img)
1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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88
1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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89 with open(args.cfg, 'w') as fp:
1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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90 cfg.dump_json(fp)
1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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91
1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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92 overlay = superdsm.render.render_result_over_image(data, border_width=args.seg_border, normalize_img=False)
1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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93 superdsm.io.imwrite(args.overlay, overlay)
1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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94
1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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95 masks = superdsm.render.rasterize_labels(data)
1b0fc671187f planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/superdsm/ commit 4d66ff6e8a2a842e44e8d0d7102dfb3ac78dca7e
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96 superdsm.io.imwrite(args.masks, masks)