Merge branch 'main' into enable-more-phases-for-budget

Author: koopmant

CITATION.cff

@@ -4,36 +4,70 @@ title: Grand-Challenge.org
 abstract: A platform for end-to-end development of machine learning solutions in biomedical imaging
 license: Apache-2.0
 authors:
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+    # Primary author(s)
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
       family-names: Meakin
       given-names: James
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+
+    # RSEs, alphabetical order
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
       family-names: Gerke
       given-names: Paul K.
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      orcid: https://orcid.org/0000-0003-1473-5705
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
       family-names: Kerkstra
       given-names: Sjoerd
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
-      family-names: Groeneveld
-      given-names: Miriam
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
-      family-names: van Leeuwen
-      given-names: Kicky
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+    - affiliation: Informatics Institute, University of Amsterdam, The Netherlands
+      family-names: Koopman
+      given-names: Thomas
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
       family-names: Mickan
       given-names: Anne
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
-      family-names: Overkamp
-      given-names: Mike
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
       family-names: van Run
       given-names: Chris
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+    - affiliation: Department of Pathology, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
       family-names: van Zeeland
       given-names: Harm
-    - affiliation: Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
-      family-names: van Ginneken
-      given-names: Bram
-      orcid: https://orcid.org/0000-0003-2028-8972
+
+    # Primary stakeholders, alphabetical order
+    - affiliation: Department of Pathology, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Ciompi
+      given-names: Francesco
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Hering
+      given-names: Alessa
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Jacobs
+      given-names: Colin
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Khalili
+      given-names: Nadieh
+    - affiliation: Department of Radiotherapy, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Koopmans
+      given-names: Peter
+    - affiliation: Department of Pathology, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: van der Laak
+      given-names: Jeroen
+    - affiliation: Department of Pathology, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Litjens
+      given-names: Geert
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Quax
+      given-names: Silvan
+    - affiliation: Informatics Institute, University of Amsterdam, The Netherlands
+      family-names: Sánchez
+      given-names: Clara I.
+    - affiliation: Department of Cardiology, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Tannhauser
+      given-names: Jos
+
+    # Product owners
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Groeneveld
+      given-names: Miriam
+    - affiliation: Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands
+      family-names: Huisman
+      given-names: Henkjan
 doi: 10.5281/zenodo.3356819
 repository-code: https://github.com/comic/grand-challenge.org

README.md

@@ -3,7 +3,7 @@
 [![Build Status](https://github.com/comic/grand-challenge.org/workflows/CI/badge.svg)](https://github.com/comic/grand-challenge.org/actions?query=workflow%3ACI+branch%3Amain)
 [![Documentation](https://img.shields.io/badge/docs-published-success)](https://comic.github.io/grand-challenge.org/)
 [![Black Code Style](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
-[![Cite Us with Zenodo](https://zenodo.org/badge/4557968.svg)](https://zenodo.org/badge/latestdoi/4557968)
+[![Cite Us with Zenodo](https://zenodo.org/badge/DOI/10.5281/zenodo.3356819.svg)](https://doi.org/10.5281/zenodo.3356819)
 
 In the era of Deep Learning, developing robust machine learning solutions to problems in biomedical imaging requires access to large amounts of annotated training data, fair comparisons of state of the art machine learning solutions, and clinical validation using real world data. Grand Challenge can assist Researchers, Data Scientists, and Clinicians in collaborating to develop these solutions by providing:
 

amass.lock

@@ -1,15 +1,15 @@
 {
   "lock_version": "1.0",
-  "content_hash": "sha256:dea343037bf43507bc0ebc532063f62a4ede582c20086903f0409b15118c433c",
+  "content_hash": "sha256:ff51ab7b46995da8cedc3a5926630bbaa79c98c9166144c0d879b0dc6a7fa74e",
   "dependencies": [
     {
       "name": "@diagnijmegen/rse-grand-challenge-dicom-de-id-procedure",
-      "version": "2025.8.5",
+      "version": "2025.10.0",
       "provider": "unpkg",
       "assets": [
         {
           "name": "dist/grand-challenge-dicom-de-id-procedure.umd.min.js",
-          "sri": "sha256-77UMyT680wXKkQmsQxLkpXoFIrIokFff81G5PlK4YTQ="
+          "sri": "sha256-up3MoFUrSVqnKhJjbQ/5Lm9pdFBNirwx1sJSUcSbf1s="
         },
         {
           "name": "dist/grand-challenge-dicom-de-id-procedure.umd.min.js.map",

app/config/settings.py

@@ -98,6 +98,7 @@
 }
 
 EMAIL_BACKEND = "grandchallenge.emails.backends.CelerySESBackend"
+SUPPORT_EMAIL = os.environ.get("SUPPORT_EMAIL", "grandchallenge@localhost")
 DEFAULT_FROM_EMAIL = os.environ.get(
     "DEFAULT_FROM_EMAIL", "grandchallenge@localhost"
 )
@@ -201,18 +202,13 @@
 #  - sha256 sums are not implemented
 USING_MINIO = strtobool(os.environ.get("USING_MINIO", "False"))
 
-AWS_S3_FILE_OVERWRITE = False
-# Note: deprecated in django storages 2.0
-AWS_BUCKET_ACL = "private"
+# Django storages settings, see https://django-storages.readthedocs.io/en/latest/backends/amazon-S3.html
 AWS_DEFAULT_ACL = "private"
+AWS_S3_FILE_OVERWRITE = False
 AWS_S3_MAX_MEMORY_SIZE = 1_048_576  # 100 MB
 AWS_S3_ENDPOINT_URL = os.environ.get("AWS_S3_ENDPOINT_URL")
-AWS_DEFAULT_REGION = os.environ.get("AWS_DEFAULT_REGION", "eu-central-1")
 AWS_S3_REGION_NAME = os.environ.get("AWS_S3_REGION_NAME")
 AWS_S3_URL_PROTOCOL = os.environ.get("AWS_S3_URL_PROTOCOL", "https:")
-AWS_CLOUDWATCH_REGION_NAME = os.environ.get("AWS_CLOUDWATCH_REGION_NAME")
-AWS_CODEBUILD_REGION_NAME = os.environ.get("AWS_CODEBUILD_REGION_NAME")
-AWS_SES_REGION_NAME = os.environ.get("AWS_SES_REGION_NAME")
 
 # This is for storing files that should not be served to the public
 PRIVATE_S3_STORAGE_KWARGS = {
@@ -281,6 +277,26 @@
     os.environ.get("CLOUDFRONT_URL_EXPIRY_SECONDS", "300")  # 5 mins
 )
 
+##############################################################################
+#
+# AWS
+#
+##############################################################################
+
+AWS_DEFAULT_REGION = os.environ.get("AWS_DEFAULT_REGION", "eu-central-1")
+AWS_CLOUDWATCH_REGION_NAME = os.environ.get("AWS_CLOUDWATCH_REGION_NAME")
+AWS_CODEBUILD_REGION_NAME = os.environ.get("AWS_CODEBUILD_REGION_NAME")
+AWS_SES_REGION_NAME = os.environ.get("AWS_SES_REGION_NAME")
+AWS_HEALTH_IMAGING_DATASTORE_ID = os.environ.get(
+    "AWS_HEALTH_IMAGING_DATASTORE_ID"
+)
+AWS_HEALTH_IMAGING_BUCKET_NAME = os.environ.get(
+    "AWS_HEALTH_IMAGING_BUCKET_NAME"
+)
+AWS_HEALTH_IMAGING_IMPORT_ROLE_ARN = os.environ.get(
+    "AWS_HEALTH_IMAGING_IMPORT_ROLE_ARN"
+)
+
 ##############################################################################
 #
 # Caching
@@ -422,8 +438,7 @@ def get_private_ip():
                 "django.template.context_processors.request",
                 "django.contrib.messages.context_processors.messages",
                 "grandchallenge.core.context_processors.challenge",
-                "grandchallenge.core.context_processors.deployment_info",
-                "grandchallenge.core.context_processors.debug",
+                "grandchallenge.core.context_processors.django_settings",
                 "grandchallenge.core.context_processors.sentry_dsn",
                 "grandchallenge.core.context_processors.footer_links",
                 "grandchallenge.core.context_processors.about_page",
@@ -1372,6 +1387,7 @@ def sentry_before_send(event, hint):
     "zl.edu.kg",
     "lw.edu.kg",
     "edumail.edu.pl",
+    "zorrag.com",
     *blocklist,
 }
 

app/grandchallenge/algorithms/forms.py

@@ -78,7 +78,9 @@
 from grandchallenge.components.tasks import assign_tarball_from_upload
 from grandchallenge.core.forms import (
     PermissionRequestUpdateForm,
+    PhaseMixin,
     SaveFormInitMixin,
+    UserMixin,
     WorkstationUserFilterMixin,
 )
 from grandchallenge.core.guardian import filter_by_permission
@@ -106,7 +108,7 @@ class ModelFactsTextField(Field):
     template = "algorithms/model_facts_field.html"
 
 
-class JobCreateForm(AdditionalInputsMixin, Form):
+class JobCreateForm(SaveFormInitMixin, AdditionalInputsMixin, Form):
     algorithm_image = ModelChoiceField(
         queryset=None, disabled=True, required=True, widget=HiddenInput
     )
@@ -123,12 +125,15 @@ class JobCreateForm(AdditionalInputsMixin, Form):
         widget=HiddenInput,
     )
 
-    def __init__(self, *args, algorithm, user, interface, **kwargs):
-        super().__init__(*args, **kwargs)
-
+    def __init__(self, *args, algorithm, interface, **kwargs):
         self._algorithm = algorithm
 
-        self._user = user
+        super().__init__(
+            *args,
+            additional_inputs=interface.inputs.all(),
+            **kwargs,
+        )
+
         self.fields["creator"].queryset = get_user_model().objects.filter(
             pk=self._user.pk
         )
@@ -155,11 +160,6 @@ def __init__(self, *args, algorithm, user, interface, **kwargs):
             )
             self.fields["algorithm_model"].initial = active_model
 
-        self.init_additional_inputs(inputs=interface.inputs.all())
-
-        self.helper = FormHelper(self)
-        self.helper.layout.append(Submit("save", "Save"))
-
     @cached_property
     def jobs_limit(self):
         if self._algorithm_image:
@@ -187,10 +187,8 @@ def clean(self):
                 "please try again after they have completed"
             )
 
-        cleaned_data["inputs"] = self.clean_additional_inputs()
-
         if Job.objects.get_jobs_with_same_inputs(
-            inputs=cleaned_data["inputs"],
+            inputs=cleaned_data["additional_inputs"],
             algorithm_image=cleaned_data["algorithm_image"],
             algorithm_model=cleaned_data["algorithm_model"],
         ):
@@ -212,19 +210,17 @@ def clean(self):
 ]
 
 
-class PhaseSelectForm(Form):
+class PhaseSelectForm(UserMixin, Form):
     phase = ModelChoiceField(
         label="Please select the phase for which you are creating an algorithm",
         queryset=Phase.objects.none(),
         required=True,
         widget=Select2Widget,
     )
 
-    def __init__(self, *args, user, **kwargs):
+    def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 
-        self._user = user
-
         self.fields["phase"].queryset = filter_by_permission(
             queryset=Phase.objects.filter(
                 submission_kind=SubmissionKindChoices.ALGORITHM
@@ -256,8 +252,8 @@ def clean_phase(self):
 
 
 class AlgorithmForm(
-    WorkstationUserFilterMixin,
     SaveFormInitMixin,
+    WorkstationUserFilterMixin,
     ViewContentExampleMixin,
     ModelForm,
 ):
@@ -346,9 +342,8 @@ class Meta:
             "workstation_config": "Viewer Configuration",
         }
 
-    def __init__(self, *args, user, **kwargs):
-        super().__init__(*args, user=user, **kwargs)
-        self._user = user
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
 
         self.fields["contact_email"].required = True
         self.fields["display_editors"].required = True
@@ -440,11 +435,7 @@ def maximum_settable_memory_gb(self):
         return value
 
 
-class UserAlgorithmsForPhaseMixin:
-    def __init__(self, *args, user, phase, **kwargs):
-        super().__init__(*args, **kwargs)
-        self._user = user
-        self._phase = phase
+class UserAlgorithmsForPhaseMixin(UserMixin, PhaseMixin):
 
     @cached_property
     def user_algorithms_for_phase(self):
@@ -567,6 +558,7 @@ def __init__(
         **kwargs,
     ):
         super().__init__(*args, user=user, phase=phase, **kwargs)
+
         self.fields["workstation_config"].initial = workstation_config
         self.fields["workstation_config"].disabled = True
         self.fields["hanging_protocol"].initial = hanging_protocol

app/grandchallenge/algorithms/migrations/0080_alter_algorithmimage_options_and_more.py

@@ -0,0 +1,31 @@
+# Generated by Django 4.2.24 on 2025-10-02 13:06
+
+from django.db import migrations
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ("algorithms", "0079_alter_algorithm_time_limit_alter_job_time_limit"),
+    ]
+
+    operations = [
+        migrations.AlterModelOptions(
+            name="algorithmimage",
+            options={
+                "ordering": ("created",),
+                "permissions": [
+                    ("download_algorithmimage", "Can download algorithm image")
+                ],
+            },
+        ),
+        migrations.AlterModelOptions(
+            name="algorithmmodel",
+            options={
+                "ordering": ("created",),
+                "permissions": [
+                    ("download_algorithmmodel", "Can download algorithm model")
+                ],
+            },
+        ),
+    ]

app/grandchallenge/algorithms/migrations/0081_job_signing_key.py

@@ -0,0 +1,22 @@
+# Generated by Django 4.2.25 on 2025-10-20 14:20
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ("algorithms", "0080_alter_algorithmimage_options_and_more"),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name="job",
+            name="signing_key",
+            field=models.BinaryField(
+                help_text="The key used to sign the inference result file",
+                max_length=32,
+                null=True,
+            ),
+        ),
+    ]