Mercurial > repos > imgteam > superdsm
changeset 2:7fcd96cf0d52 draft
planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/superdsm/ commit 597cb3dc531963d02c5db0e4fc2596fcb06728dd
| author | imgteam |
|---|---|
| date | Wed, 17 Dec 2025 22:28:28 +0000 |
| parents | 680b866ba043 |
| children | c2412cb5fc2e |
| files | creators.xml run-superdsm.py superdsm.xml test-data/cfg-full.tsv test-data/cfg.tsv tests.xml |
| diffstat | 6 files changed, 487 insertions(+), 104 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/creators.xml Wed Dec 17 22:28:28 2025 +0000 @@ -0,0 +1,43 @@ +<macros> + + <xml name="creators/bmcv"> + <organization name="Biomedical Computer Vision Group, Heidelberg Universtiy" alternateName="BMCV" url="http://www.bioquant.uni-heidelberg.de/research/groups/biomedical_computer_vision.html" /> + <yield /> + </xml> + + <xml name="creators/kostrykin"> + <person givenName="Leonid" familyName="Kostrykin"/> + <yield/> + </xml> + + <xml name="creators/rmassei"> + <person givenName="Riccardo" familyName="Massei"/> + <yield/> + </xml> + + <xml name="creators/alliecreason"> + <person givenName="Allison" familyName="Creason"/> + <yield/> + </xml> + + <xml name="creators/bugraoezdemir"> + <person givenName="Bugra" familyName="Oezdemir"/> + <yield/> + </xml> + + <xml name="creators/thawn"> + <person givenName="Till" familyName="Korten"/> + <yield/> + </xml> + + <xml name="creators/pavanvidem"> + <person givenName="Pavan" familyName="Videm"/> + <yield/> + </xml> + + <xml name="creators/tuncK"> + <person givenName="Tunc" familyName="Kayikcioglu"/> + <yield/> + </xml> + +</macros>
--- 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)
--- a/superdsm.xml Thu Jul 06 00:01:07 2023 +0000 +++ b/superdsm.xml Wed Dec 17 22:28:28 2025 +0000 @@ -1,66 +1,137 @@ -<tool id="ip_superdsm" name="SuperDSM" version="0.1.3" profile="20.05"> - <description>globally optimal segmentation method based on superadditivity and deformable shape models for cell nuclei in fluorescence microscopy images</description> - <requirements> - <requirement type="package" version="0.1.3">superdsm</requirement> - <requirement type="package" version="1.6.0">ray-core</requirement> +<tool id="ip_superdsm" name="Perform segmentation using deformable shape models" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05"> + <description>with SuperDSM</description> + <macros> + <import>creators.xml</import> + <import>tests.xml</import> + <token name="@TOOL_VERSION@">0.2.0</token> + <token name="@VERSION_SUFFIX@">1</token> + </macros> + <creator> + <expand macro="creators/bmcv"/> + </creator> + <edam_operations> + <edam_operation>operation_3443</edam_operation> + </edam_operations> + <xrefs> + <xref type="bio.tools">superdsm</xref> + <xref type="biii">superdsm</xref> + </xrefs> + <requirements> + + <requirement type="package" version="@TOOL_VERSION@">superdsm</requirement> + <requirement type="package" version="0.1.1">giatools</requirement> + + <!-- + Pin the dependencies to specific versions for reproducibility: + https://github.com/BMCV/SuperDSM#dependency-version-considerations + --> + <requirement type="package" version="1.20">numpy</requirement> + <requirement type="package" version="1.6.3">scipy</requirement> <requirement type="package" version="0.18.1">scikit-image</requirement> - </requirements> - <command detect_errors="aggressive"> - <![CDATA[ - python '$__tool_directory__/run-superdsm.py' - '${dataset}' - 'cfg.json' - 'masks.png' - 'overlay.png' - $seg_border - \${GALAXY_SLOTS:-4} - #if str($config.AF_scale) != '': - --AF_scale '${config.AF_scale}' - #end if - #if str($config.c2f_region_analysis_min_atom_radius) != '': - --c2f_region_analysis_min_atom_radius '${config.c2f_region_analysis_min_atom_radius}' - #end if - #if str($config.c2f_region_analysis_min_norm_energy_improvement) != '': - --c2f_region_analysis_min_norm_energy_improvement '${config.c2f_region_analysis_min_norm_energy_improvement}' - #end if - #if str($config.c2f_region_analysis_max_atom_norm_energy) != '': - --c2f_region_analysis_max_atom_norm_energy '${config.c2f_region_analysis_max_atom_norm_energy}' - #end if - #if str($config.c2f_region_analysis_max_cluster_marker_irregularity) != '': - --c2f_region_analysis_max_cluster_marker_irregularity '${config.c2f_region_analysis_max_cluster_marker_irregularity}' - #end if - #if str($config.dsm_alpha) != '': - --dsm_alpha '${config.dsm_alpha}' - #end if - #if str($config.dsm_AF_alpha) != '': - --dsm_AF_alpha '${config.dsm_AF_alpha}' - #end if - #if str($config.global_energy_minimization_beta) != '': - --global_energy_minimization_beta '${config.global_energy_minimization_beta}' - #end if - #if str($config.global_energy_minimization_AF_beta) != '': - --global_energy_minimization_AF_beta '${config.global_energy_minimization_AF_beta}' - #end if - #if str($config.postprocess_mask_max_distance) != '': - --postprocess_mask_max_distance '${config.postprocess_mask_max_distance}' - #end if - #if str($config.postprocess_mask_stdamp) != '': - --postprocess_mask_stdamp '${config.postprocess_mask_stdamp}' - #end if - #if str($config.postprocess_max_norm_energy) != '': - --postprocess_max_norm_energy '${config.postprocess_max_norm_energy}' - #end if - #if str($config.postprocess_min_contrast) != '': - --postprocess_min_contrast '${config.postprocess_min_contrast}' - #end if - #if str($config.postprocess_min_object_radius) != '': - --postprocess_min_object_radius '${config.postprocess_min_object_radius}' - #end if - ]]> - </command> - <inputs> + <requirement type="package" version="1.2.6">cvxopt</requirement> + <requirement type="package" version="1.1.13">cvxpy</requirement> + <requirement type="package" version="1.6.0">ray-core</requirement> + + <!-- + 2020.0 is the last version of MKL which supports the "MKL_DEBUG_CPU_TYPE" environment variable. + --> + <requirement type="package" version="2020.0">mkl</requirement> + + <!-- + Using MKL instead of other BLAS can significantly improve performance on some hardware: + https://stackoverflow.com/questions/62783262/why-is-numpy-with-ryzen-threadripper-so-much-slower-than-xeon + + Pinning BLAS to version 1.0 is required for reproducibility: + https://github.com/BMCV/SuperDSM#dependency-version-considerations + --> + <requirement type="package" version="1.0=mkl">blas</requirement> + + </requirements> + <command detect_errors="aggressive"> + <![CDATA[ + python '$__tool_directory__/run-superdsm.py' + '${dataset}' + \${GALAXY_SLOTS:-4} + #if 'masks' in $outputs: + --do-masks 'masks.png' + #end if + #if 'cfg' in $outputs: + --do-cfg 'cfg.tsv' + #end if + #if 'overlay' in $outputs: + --do-overlay 'overlay.png' + #if $seg_border.value % 2 == 1: + #set $seg_border = "%d" % ($seg_border.value + 1) + --do-overlay-border $seg_border + #else: + --do-overlay-border $seg_border + #end if + #end if + #if str($config.AF_scale) != '': + --AF_scale '${config.AF_scale}' + #end if + #if str($config.c2f_region_analysis_min_atom_radius) != '': + --c2f_region_analysis_min_atom_radius '${config.c2f_region_analysis_min_atom_radius}' + #end if + #if str($config.c2f_region_analysis_min_norm_energy_improvement) != '': + --c2f_region_analysis_min_norm_energy_improvement '${config.c2f_region_analysis_min_norm_energy_improvement}' + #end if + #if str($config.c2f_region_analysis_max_atom_norm_energy) != '': + --c2f_region_analysis_max_atom_norm_energy '${config.c2f_region_analysis_max_atom_norm_energy}' + #end if + #if str($config.c2f_region_analysis_max_cluster_marker_irregularity) != '': + --c2f_region_analysis_max_cluster_marker_irregularity '${config.c2f_region_analysis_max_cluster_marker_irregularity}' + #end if + #if str($config.dsm_alpha) != '': + --dsm_alpha '${config.dsm_alpha}' + #end if + #if str($config.dsm_AF_alpha) != '': + --dsm_AF_alpha '${config.dsm_AF_alpha}' + #end if + --global_energy_minimization_pruning '${global_energy_minimization_pruning}' + #if str($config.global_energy_minimization_beta) != '': + --global_energy_minimization_beta '${config.global_energy_minimization_beta}' + #end if + #if str($config.global_energy_minimization_AF_beta) != '': + --global_energy_minimization_AF_beta '${config.global_energy_minimization_AF_beta}' + #end if + #if str($config.postprocess_mask_max_distance) != '': + --postprocess_mask_max_distance '${config.postprocess_mask_max_distance}' + #end if + #if str($config.postprocess_mask_stdamp) != '': + --postprocess_mask_stdamp '${config.postprocess_mask_stdamp}' + #end if + #if str($config.postprocess_max_norm_energy) != '': + --postprocess_max_norm_energy '${config.postprocess_max_norm_energy}' + #end if + #if str($config.postprocess_min_contrast) != '': + --postprocess_min_contrast '${config.postprocess_min_contrast}' + #end if + #if str($config.postprocess_min_object_radius) != '': + --postprocess_min_object_radius '${config.postprocess_min_object_radius}' + #end if + ]]> + </command> + <environment_variables> + + <!-- + This enables accelerated CPU instruction sets on AMD hardware, does nothing in Intel hardware, thus no need to change this: + --> + <environment_variable name="MKL_DEBUG_CPU_TYPE">5</environment_variable> + + </environment_variables> + <inputs> <param name="dataset" type="data" format="tiff,png" label="Dataset" /> - <param name="seg_border" type="integer" min="1" value="8" label="Width of the outlines (in pixels) of the segmentation results (overlays)" /> + <param argument="--global_energy_minimization_pruning" type="select" label="Graph pruning for global energy minimization" help="Exact graph pruning corresponds to the original algorithm, which provably yields globally optimal results. Robust graph pruning is more greedy and has a provably bounded approximation error. Depending on the data, this can be significantly faster than exact graph pruning, without degrading the segmentation or cluster splitting performance."> + <option value="exact">Exact graph pruning (Kostrykin and Rohr, TPAMI 2023)</option> + <option value="isbi24" selected="true">Robust graph pruning (Kostrykin and Rohr, ISBI 2024)</option> + </param> + <param name="outputs" type="select" label="Tool outputs" multiple="true" optional="false" help="Note that if neither a segmentation overlay nor a label map is created, segmentation and cluster splitting will not be performed. As a consequence, hyperparameters which are determined automatically during segmentation and cluster splitting will not be reported, even if "Report all hyperparameters" is selected."> + <option value="overlay" selected="true">Create a segmentation overlay</option> + <option value="masks">Create a label map (e.g., for further processing)</option> + <option value="cfg">Report all hyperparameters (manually set and automatically determined values)</option> + </param> + <param name="seg_border" type="integer" min="1" value="8" label="Width of the outlines (in pixels)" help="This parameter is only used for segmentation overlays (see above)." /> <section name="config" title="Hyperparameters" expanded="false"> <param argument="--AF_scale" optional="true" type="float" value="" min="0" label="scale σ" help="The scale of the objects to be segmented. Leave empty to use the automatically determined value." /> <param argument="--c2f_region_analysis_min_atom_radius" optional="true" type="float" value="" min="0" label="min_atom_radius" help="No region determined by the Coarse-to-fine region analysis scheme is smaller than a circle of this radius (in terms of the surface area). Leave empty to use the automatically determined value." /> @@ -79,22 +150,60 @@ </section> </inputs> <outputs> - <data format="json" name="cfg" from_work_dir="cfg.json" label="${tool.name} on ${on_string}: cfg" /> - <data format="png" name="masks" from_work_dir="masks.png" label="${tool.name} on ${on_string}: masks" /> - <data format="png" name="overlay" from_work_dir="overlay.png" label="${tool.name} on ${on_string}: overlay" /> + <data format="png" name="masks" from_work_dir="masks.png" label="${tool.name} on ${on_string}: masks"> + <filter>'masks' in outputs</filter> + </data> + <data format="tsv" name="cfg" from_work_dir="cfg.tsv" label="${tool.name} on ${on_string}: cfg"> + <filter>'cfg' in outputs</filter> + </data> + <data format="png" name="overlay" from_work_dir="overlay.png" label="${tool.name} on ${on_string}: overlay"> + <filter>'overlay' in outputs</filter> + </data> </outputs> <tests> - <test> + <test expect_num_outputs="3"> <param name="dataset" value="BBBC033_C2_z28.png" /> - <output name="overlay" value="overlay.png" ftype="png" compare="sim_size" /> + <param name="global_energy_minimization_pruning" value="exact" /> + <param name="outputs" value="overlay,masks,cfg" /> + <expand macro="tests/intensity_image_diff" name="overlay" value="overlay.png" ftype="png"/> + <output name="cfg" value="cfg-full.tsv" ftype="tsv" compare="diff" /> + <output name="masks" ftype="png"> + <assert_contents> + + <has_image_width width="1024"/> + <has_image_height height="1344"/> + <has_image_channels channels="1"/> + <has_image_n_labels n="16"/><!-- 15 objects plus the background --> + + </assert_contents> + </output> + </test> + <test expect_num_outputs="1"> + <param name="dataset" value="BBBC033_C2_z28.png" /> + <param name="global_energy_minimization_pruning" value="exact" /> + <param name="outputs" value="cfg" /> + <output name="cfg" value="cfg.tsv" ftype="tsv" compare="diff" /> </test> </tests> <help> - This tool permits the segmentation of cell nuclei in 2-D fluorescence microscopy images. + + **Performs segmentation of 2-D fluorescence microscopy images using deformable shape models and superadditivity.** - You can either use an individual input image (PNG, TIF) or a collection of such images. + SuperDSM is a globally optimal method for cell nuclei segmentation using deformable shape models and their inherent law of superadditivity. + + You can either use an individual input image (PNG, TIFF) or a collection of such images. + </help> <citations> + <citation type="bibtex"> + @inproceedings{kostrykin2024, + author = {Kostrykin, L. and Rohr, K.}, + title = {Robust Graph Pruning for Efficient Segmentation and Cluster Splitting of Cell Nuclei using Deformable Shape Models}, + booktitle = {Proc. IEEE International Symposium on Biomedical Imaging (ISBI'24)}, + pages = {accepted for presentation}, + year = {2024}, + } + </citation> <citation type="doi">10.1109/TPAMI.2022.3185583</citation> </citations> </tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cfg-full.tsv Wed Dec 17 22:28:28 2025 +0000 @@ -0,0 +1,68 @@ +Hyperparameter Value +AF_scale +c2f-region-analysis/AF_min_atom_radius 0.33 +c2f-region-analysis/enabled True +c2f-region-analysis/max_atom_norm_energy 0.05 +c2f-region-analysis/max_cluster_marker_irregularity 0.2 +c2f-region-analysis/min_atom_radius 30 +c2f-region-analysis/min_norm_energy_improvement 0.1 +c2f-region-analysis/seed_connectivity 8 +dsm/AF_alpha 0.0005 +dsm/AF_background_margin 0.4 +dsm/AF_smooth_amount 0.2 +dsm/AF_smooth_subsample 0.4 +dsm/alpha 2.116 +dsm/background_margin 26 +dsm/cachesize 1 +dsm/cachetest +dsm/cp_timeout 300 +dsm/enabled True +dsm/epsilon 1.0 +dsm/gaussian_shape_multiplier 2 +dsm/init elliptical +dsm/scale 1000 +dsm/smooth_amount 13 +dsm/smooth_mat_dtype float32 +dsm/smooth_mat_max_allocations inf +dsm/smooth_subsample 26 +dsm/sparsity_tol 0 +global-energy-minimization/AF_beta 0.66 +global-energy-minimization/AF_max_seed_distance inf +global-energy-minimization/beta 2793.1200000000003 +global-energy-minimization/enabled True +global-energy-minimization/gamma 0.8 +global-energy-minimization/max_iter 5 +global-energy-minimization/max_seed_distance inf +global-energy-minimization/max_work_amount 1000000 +global-energy-minimization/pruning exact +histological False +postprocess/AF_max_object_radius inf +postprocess/AF_min_glare_radius inf +postprocess/AF_min_object_radius 0.0 +postprocess/contrast_epsilon 0.0001 +postprocess/discard_image_boundary False +postprocess/enabled True +postprocess/exterior_offset 5 +postprocess/exterior_scale 5 +postprocess/fill_holes True +postprocess/glare_detection_min_layer 0.5 +postprocess/glare_detection_num_layers 5 +postprocess/glare_detection_smoothness 3 +postprocess/mask_max_distance 1 +postprocess/mask_smoothness 3 +postprocess/mask_stdamp 2.0 +postprocess/max_boundary_eccentricity inf +postprocess/max_eccentricity 0.99 +postprocess/max_norm_energy 0.2 +postprocess/max_object_radius inf +postprocess/min_boundary_glare_radius inf +postprocess/min_boundary_obj_radius 0 +postprocess/min_contrast 1.35 +postprocess/min_glare_radius inf +postprocess/min_object_radius 0.0 +preprocess/AF_sigma2 1.0 +preprocess/enabled True +preprocess/lower_clip_mean False +preprocess/offset_clip 3 +preprocess/sigma1 1.4142135623730951 +preprocess/sigma2 65.05382386916237
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cfg.tsv Wed Dec 17 22:28:28 2025 +0000 @@ -0,0 +1,32 @@ +Hyperparameter Value +AF_scale +c2f-region-analysis/AF_min_atom_radius 0.33 +c2f-region-analysis/max_atom_norm_energy 0.05 +c2f-region-analysis/max_cluster_marker_irregularity 0.2 +c2f-region-analysis/min_atom_radius 30 +c2f-region-analysis/min_norm_energy_improvement 0.1 +dsm/AF_alpha 0.0005 +dsm/AF_background_margin 0.4 +dsm/AF_smooth_amount 0.2 +dsm/AF_smooth_subsample 0.4 +dsm/alpha 2.116 +dsm/background_margin 26 +dsm/smooth_amount 13 +dsm/smooth_subsample 26 +global-energy-minimization/AF_beta 0.66 +global-energy-minimization/AF_max_seed_distance inf +global-energy-minimization/beta 2793.1200000000003 +global-energy-minimization/max_seed_distance inf +global-energy-minimization/pruning exact +postprocess/AF_max_object_radius inf +postprocess/AF_min_glare_radius inf +postprocess/AF_min_object_radius 0.0 +postprocess/mask_max_distance 1 +postprocess/mask_stdamp 2.0 +postprocess/max_norm_energy 0.2 +postprocess/max_object_radius inf +postprocess/min_contrast 1.35 +postprocess/min_glare_radius inf +postprocess/min_object_radius 0.0 +preprocess/AF_sigma2 1.0 +preprocess/sigma2 65.05382386916237
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tests.xml Wed Dec 17 22:28:28 2025 +0000 @@ -0,0 +1,95 @@ +<macros> + + <!-- Macros for verification of image outputs --> + + <xml + name="tests/binary_image_diff" + tokens="name,value,ftype,metric,eps" + token_metric="mae" + token_eps="0.01"> + + <output name="@NAME@" value="@VALUE@" ftype="@FTYPE@" compare="image_diff" metric="@METRIC@" eps="@EPS@" pin_labels="0"> + <assert_contents> + <has_image_n_labels n="2"/> + <yield/> + </assert_contents> + </output> + + </xml> + + <xml + name="tests/label_image_diff" + tokens="name,value,ftype,metric,eps,pin_labels" + token_metric="iou" + token_eps="0.01" + token_pin_labels="0"> + + <output name="@NAME@" value="@VALUE@" ftype="@FTYPE@" compare="image_diff" metric="@METRIC@" eps="@EPS@" pin_labels="@PIN_LABELS@"> + <assert_contents> + <yield/> + </assert_contents> + </output> + + </xml> + + <xml + name="tests/intensity_image_diff" + tokens="name,value,ftype,metric,eps" + token_metric="rms" + token_eps="0.01"> + + <output name="@NAME@" value="@VALUE@" ftype="@FTYPE@" compare="image_diff" metric="@METRIC@" eps="@EPS@"> + <assert_contents> + <yield/> + </assert_contents> + </output> + + </xml> + + <!-- Variants of the above for verification of collection elements --> + + <xml + name="tests/binary_image_diff/element" + tokens="name,value,ftype,metric,eps" + token_metric="mae" + token_eps="0.01"> + + <element name="@NAME@" value="@VALUE@" ftype="@FTYPE@" compare="image_diff" metric="@METRIC@" eps="@EPS@" pin_labels="0"> + <assert_contents> + <has_image_n_labels n="2"/> + <yield/> + </assert_contents> + </element> + + </xml> + + <xml + name="tests/label_image_diff/element" + tokens="name,value,ftype,metric,eps" + token_metric="iou" + token_eps="0.01" + token_pin_labels="0"> + + <element name="@NAME@" value="@VALUE@" ftype="@FTYPE@" compare="image_diff" metric="@METRIC@" eps="@EPS@" pin_labels="@PIN_LABELS@"> + <assert_contents> + <yield/> + </assert_contents> + </element> + + </xml> + + <xml + name="tests/intensity_image_diff/element" + tokens="name,value,ftype,metric,eps" + token_metric="rms" + token_eps="0.01"> + + <element name="@NAME@" value="@VALUE@" ftype="@FTYPE@" compare="image_diff" metric="@METRIC@" eps="@EPS@"> + <assert_contents> + <yield/> + </assert_contents> + </element> + + </xml> + +</macros>