Merge branch 'main' into FynnBe-patch-2

.github/workflows/auto_update_main.yaml

@@ -73,7 +73,7 @@ jobs:
     - name: update external resources
       id: update_external
       shell: bash -l {0}
-      run: python scripts/update_external_resources.py --max-resource-count 20 ${{ github.event_name == 'pull_request' && '--no-ignore-status-5xx' || '--ignore-status-5xx' }}
+      run: python scripts/update_external_resources.py --max-resource-count 30 ${{ github.event_name == 'pull_request' && '--no-ignore-status-5xx' || '--ignore-status-5xx' }}
     - name: "Upload collection update"
       uses: actions/upload-artifact@v3
       with:

.github/workflows/validate_resources.yaml

@@ -52,7 +52,7 @@ jobs:
           - conda-forge
         create-args: >-  # script dependencies
           bioimageio.core
-          bioimageio.spec
+          bioimageio.spec>=0.4.9.post5
           lxml
           packaging
           typer

adjectives.txt

@@ -143,6 +143,7 @@ shivering
 shy
 sincere
 smart
+sneaky
 sociable
 solitary
 straightforward

animals.yaml

@@ -38,7 +38,7 @@ honeybee: 🐝
 horse: 🐎
 kangaroo: 🦘
 koala: 🐨
-lady beetle: 🐞
+ladybird: 🐞
 leopard: 🐆
 lion: 🦁
 lizard: 🦎

collection/10.5281/zenodo.10366411/resource.yaml

@@ -0,0 +1,28 @@
+doi: 10.5281/zenodo.10366411
+id: 10.5281/zenodo.10366411
+nickname: funny-butterfly
+nickname_icon: 🦋
+owners:
+- 271523
+status: accepted
+type: model
+versions:
+- created: '2024-01-11 15:31:40.010085'
+  doi: 10.5281/zenodo.10492722
+  name: Mitochondria TOM20 artificial labelling - pix2pix
+  status: accepted
+  version_id: '10492722'
+  version_name: version from 2024-01-11
+  rdf_source: https://zenodo.org/api/records/10492722/files/rdf.yaml/content
+  weights:
+    torchscript: 
+      source: latest_net_G_torchscript.pt
+      sha256: 86f7daa11efe1071d3d52e698d462113409ee543827e76f597a60e5a1b6dd71c
+      pytorch_version: '2.1'
+- created: '2023-12-14 12:01:44.656032'
+  doi: 10.5281/zenodo.10366412
+  name: Mitochondria TOM20 artificial labelling - pix2pix
+  status: blocked
+  version_id: '10366412'
+  version_name: version from 2023-12-12
+  rdf_source: https://zenodo.org/api/records/10366412/files/rdf.yaml/content

collection/10.5281/zenodo.5910163/resource.yaml

@@ -15,6 +15,12 @@ versions:
   status: accepted
   version_id: '5942853'
   version_name: revision 1
+  weights:
+    onnx: 
+      authors:
+      - name: Wei OUYANG
+      source: ./densenet_model.onnx
+      sha256: 0cb72ff5e414630de95674a7d523da0de19850b1cada4712201699fdd960c1b0
 - {created: '2022-01-27 10:28:20.092577', doi: 10.5281/zenodo.5910164, name: HPA Bestfitting
     Densenet, rdf_source: 'https://zenodo.org/api/files/5be7a94a-0f23-4658-bee3-d160c6eb1c83/rdf.yaml',
   status: blocked, version_id: '5910164', version_name: revision 1}

collection/10.5281/zenodo.6028097/resource.yaml

@@ -15,3 +15,7 @@ versions:
   training_data: {id: ilastik/platynereis_em_training_data}
   version_id: '6028098'
   version_name: revision 1
+  maintainers:
+  - github_user: constantinpape
+    name: Constantin Pape
+

collection/10.5281/zenodo.7274275/resource.yaml

@@ -1,40 +1,70 @@
-doi: 10.5281/zenodo.7274275
-id: 10.5281/zenodo.7274275
-nickname: joyful-deer
-nickname_icon: "\U0001F98C"
-owners: [432585]
-status: accepted
-type: model
-versions:
-- cite:
-  - {doi: 10.1101/2023.04.06.535829, text: 'Hennies et al. 2023, CebraEM: A practical
-      workflow to segment cellular organelles in volume SEM datasets using a transferable
-      CNN-based membrane prediction'}
-  config:
-    bioimageio:
-      test_kwargs:
-        pytorch_state_dict: {decimal: 2}
-        torchscript: {decimal: 2}
-  created: '2023-07-07 10:12:51.478763'
-  doi: 10.5281/zenodo.8123818
-  name: CebraNET Cellular Membranes in Volume SEM
-  parent: {sha256: f19d75e9ea394fd7b0bd9c86276de41b10318245315fa4d2cc6e24e63c6371a1,
-    uri: 'https://doi.org/10.5281/zenodo.7274275'}
-  rdf_source: https://zenodo.org/api/records/8123818/files/rdf.yaml/content
-  status: accepted
-  version_id: '8123818'
-  version_name: version 3
-- {created: '2023-07-06 08:12:02.329226', doi: 10.5281/zenodo.8119068, name: CebraNET
-    Cellular Membranes in Volume SEM, rdf_source: 'https://zenodo.org/api/files/34d12fe0-da40-47f7-9795-3af0e9c1baf6/rdf.yaml',
-  status: blocked, version_id: '8119068', version_name: version 2}
-- config:
-    bioimageio:
-      test_kwargs:
-        pytorch_state_dict: {decimal: 2}
-  created: '2022-11-02 13:52:32.578744'
-  doi: 10.5281/zenodo.7274276
-  name: CebraNET Cellular Membranes in Volume SEM
-  rdf_source: https://zenodo.org/api/files/c95661ca-b06a-464f-810c-5c9804ebe982/rdf.yaml
-  status: accepted
-  version_id: '7274276'
-  version_name: version 1
+doi: 10.5281/zenodo.7274275
+id: 10.5281/zenodo.7274275
+nickname: joyful-deer
+nickname_icon: 🦌
+owners:
+- 432585
+status: accepted
+type: model
+versions:
+- created: '2023-10-27 11:34:30.252675'
+  doi: 10.5281/zenodo.10047226
+  name: CebraNET Cellular Membranes in Volume SEM
+  status: accepted
+  version_id: '10047226'
+  version_name: version from 2023-10-27
+  rdf_source: https://zenodo.org/api/records/10047226/files/rdf.yaml/content
+  config:
+    bioimageio:
+      test_kwargs:
+        pytorch_state_dict:
+          decimal: 2
+        torchscript:
+          decimal: 2
+- created: '2023-10-27 11:32:10.061066'
+  doi: 10.5281/zenodo.10047209
+  name: CebraNET Cellular Membranes in Volume SEM
+  status: blocked
+  version_id: '10047209'
+  version_name: version from 2023-10-27
+  rdf_source: https://zenodo.org/api/records/10047209/files/rdf.yaml/content
+- cite:
+  - doi: 10.1101/2023.04.06.535829
+    text: 'Hennies et al. 2023, CebraEM: A practical workflow to segment cellular
+      organelles in volume SEM datasets using a transferable CNN-based membrane prediction'
+  config:
+    bioimageio:
+      test_kwargs:
+        pytorch_state_dict:
+          decimal: 2
+        torchscript:
+          decimal: 2
+  created: '2023-07-07 10:12:51.478763'
+  doi: 10.5281/zenodo.8123818
+  name: CebraNET Cellular Membranes in Volume SEM
+  parent:
+    sha256: f19d75e9ea394fd7b0bd9c86276de41b10318245315fa4d2cc6e24e63c6371a1
+    uri: https://doi.org/10.5281/zenodo.7274275
+  status: accepted
+  version_id: '8123818'
+  version_name: version 3
+  rdf_source: https://zenodo.org/api/records/8123818/files/rdf.yaml/content
+- created: '2023-07-06 08:12:02.329226'
+  doi: 10.5281/zenodo.8119068
+  name: CebraNET Cellular Membranes in Volume SEM
+  status: blocked
+  version_id: '8119068'
+  version_name: version 2
+  rdf_source: https://zenodo.org/api/files/34d12fe0-da40-47f7-9795-3af0e9c1baf6/rdf.yaml
+- config:
+    bioimageio:
+      test_kwargs:
+        pytorch_state_dict:
+          decimal: 2
+  created: '2022-11-02 13:52:32.578744'
+  doi: 10.5281/zenodo.7274276
+  name: CebraNET Cellular Membranes in Volume SEM
+  status: accepted
+  version_id: '7274276'
+  version_name: version 1
+  rdf_source: https://zenodo.org/api/files/c95661ca-b06a-464f-810c-5c9804ebe982/rdf.yaml

collection_rdf_template.yaml

@@ -39,7 +39,7 @@ config:
       branch: master
       collection_file_name: manifest.bioimage.io.yaml
     - id: deepimagej
-      repository: fynnbe/models
+      repository: deepimagej/models
       branch: master
       collection_file_name: manifest.bioimage.io.yaml
       test_summaries:
@@ -82,5 +82,12 @@ config:
       repository: stardist/stardist-bioimage-io
       branch: main
       collection_file_name: collection.yaml
-
+    - id: biapy
+      repository: BiaPyX/BiaPy-bioimage-io
+      branch: main
+      collection_file_name: collection.yaml
+    - id: dl4miceverywhere
+      repository: HenriquesLab/DL4MicEverywhere-bioimage-io
+      branch: main
+      collection_file_name: collection.yaml
 collection: []

scripts/download_documentation.py

@@ -9,7 +9,8 @@
 
 
 def main(
-    folder: Path = Path(__file__).parent / "../dist",  # nested folders with rdf.yaml files
+    folder: Path = Path(__file__).parent
+    / "../dist",  # nested folders with rdf.yaml files
 ):
     """Download the documentation file for every rdf.yaml found in (subfolders of) folder"""
     if not folder.exists():
@@ -34,9 +35,12 @@ def main(
 
         try:
             resolve_source(
-                doc_uri, output=rdf_path.with_name(f"documentation.{type_ext}"), pbar=partial(tqdm, disable=True)
+                doc_uri,
+                output=rdf_path.with_name(f"documentation.{type_ext}"),
+                pbar=partial(tqdm, disable=True),
             )
-        except ValueError:
+        except Exception as e:
+            warnings.warn(f"failed to resolve doc_ui: {e}")
             _ = rdf_path.with_name("documentation.md").write_text(doc_uri)