Dockerfile, meta.json - Updated source to v1.1, moved cli to src dir,…

… added improved output nodule sorting

models/gc_node21_baseline/dockerfiles/Dockerfile

@@ -10,10 +10,10 @@ RUN pip3 install --no-cache-dir torch==2.0.1+cu118 torchvision==0.15.2+cu118 -f
 RUN apt update && apt install -y --no-install-recommends git-lfs && rm -rf /var/lib/apt/lists/*
 
 # Install node21 baseline algorithm
-#  - Git clone to tmp directory (main branch, tag v1.0addedtag)
+#  - Git clone to tmp directory (main branch, tag v1.1)
 #  - Extract relevant files to /opt/algorithm/
 #  - Remove tmp directory
-RUN git clone --depth 1 --branch v1.0addedtag https://github.com/node21challenge/node21_detection_baseline.git /tmp/algorithm && \
+RUN git clone --depth 1 --branch v1.1 https://github.com/node21challenge/node21_detection_baseline.git /tmp/algorithm && \
     mkdir -p /opt/algorithm && \
     mv /tmp/algorithm/process.py /opt/algorithm/process.py && \
     mv /tmp/algorithm/postprocessing.py /opt/algorithm/postprocessing.py && \

models/gc_node21_baseline/meta.json

@@ -43,7 +43,7 @@
   },
   "details": {
     "name": "NODE21 baseline",
-    "version": "1.0",
+    "version": "1.1",
     "devteam": "DIAGNijmegen (Diagnostic Image Analysis Group, Radboud UMC, The Netherlands)",
     "type": "Faster R-CNN architecture using ResNet50 as the backbone.",
     "date": {

models/gc_node21_baseline/utils/cli.py → models/gc_node21_baseline/src/cli.py

@@ -30,6 +30,17 @@ def run_classifier(input_cxr: Path, output_json_file: Path):
         tmp_path = Path("/app/tmp")
         predictions = Noduledetection(input_dir=tmp_path, output_dir=tmp_path).predict(input_image=input_image)
 
+        # sort predictions on probability first (descending), corner positions second (ascending)
+        # this was implemented because the old sorting only sorts on probability (descending) and can give different
+        # results if two probabilities are the same
+        predictions["boxes"] = list(
+            sorted(
+                predictions["boxes"],
+                key=lambda x : tuple([-x["probability"]] + [tuple(c) for c in x["corners"]]),
+                reverse=False
+            )
+        )
+
         # Export the predictions to a JSON file
         with open(output_json_file, "w") as f:
             json.dump(predictions, f, indent=4)

models/gc_node21_baseline/utils/Node21BaselineRunner.py

@@ -15,7 +15,7 @@
 from mhubio.core import Instance, InstanceData, IO, Module, Meta, ValueOutput, OutputDataCollection
 
 
-CLI_PATH = Path(__file__).parent.absolute() / "cli.py"
+CLI_PATH = Path(__file__).parent.parent.absolute() / "src" / "cli.py"
 
 
 @ValueOutput.Name('noduleprob')